Method and related device for improving the observation accuracy of sensorless control of permanent magnet synchronous motor

Abstract

Method and related device for improving the observation accuracy of sensorless control of permanent magnet synchronous motors, including: establishing a mathematical model of a permanent magnet synchronous linear motor; estimating back electromotive force information by using a sliding mode observer according to the mathematical model of the permanent magnet synchronous linear motor; filtering out low-order harmonics and DC offset components in the estimated back electromotive force information; realizing the tracking of speed during the filtering process of a cascaded third-order generalized integrator and improving the tracking accuracy for ramp speed changes; estimating the position and speed through a phase-locked loop with the filtered estimated back electromotive force. The present invention proposes a method for improving the observation accuracy of sensorless control of permanent magnet synchronous motors. By adopting a multi-stage cross-feedback third-order generalized integrator (TOGI) structure, the 5th and 7th harmonics and DC offset components mainly contained in the estimated back electromotive force are filtered out, and the improvement of the observer estimation accuracy is realized.

Description

Technical Field

[0001] The present invention belongs to the technical field of sensorless control of permanent magnet synchronous linear motors, and particularly relates to a method and related device for improving the observation accuracy of sensorless control of permanent magnet synchronous motors. Background Art

[0002] Linear motors have the advantages of simple structure, large acceleration, high positioning accuracy, low friction, and convenient maintenance. Compared with other linear motors, permanent magnet synchronous linear motors also have the advantages of strong controllability, high power density, and high efficiency, and thus are widely used in modern industry. The traditional driving method of permanent magnet synchronous linear motors mostly uses mechanical sensors, which are expensive, have high requirements for the working environment, and require additional installation space, restricting the in-depth application of permanent magnet synchronous linear motors. Therefore, the research on the sensorless control method for permanent magnet synchronous linear motors has recently attracted much attention.

[0003] The sensorless control of permanent magnet synchronous linear motors essentially uses electrical quantities such as voltage and current to estimate the speed and position of the motor mover. According to different principles, the sensorless control methods can be divided into two categories: signal injection-based methods and model-based methods. Signal injection-based methods include low-frequency signal injection method, high-frequency signal injection method, etc. Model-based methods first perform back electromotive force or flux linkage observation, and then estimate the speed and position of the mover based on the observed back electromotive force or flux linkage. The methods for observing back electromotive force or flux linkage include direct calculation method, model reference adaptive method, observer method, etc. The estimation of mover speed and position is usually completed by a phase-locked loop.

[0004] The sliding mode observer belongs to the observer method. It uses the difference between the state variable and the actual value as feedback, and controls the state variable to move on the set sliding mode surface through a switching function to achieve the estimation of the state variable. Compared with other observers, the sliding mode observer has a simple structure and high robustness, and is widely used in the sensorless control of motors. During the sensorless control process of permanent magnet synchronous linear motors, the nonlinearity of the inverter and the harmonic distortion phenomenon of the permanent magnet magnetic field caused by cogging effect, etc. will generate 6k±1 harmonics in the back electromotive force, resulting in 6k harmonics in the position estimation error of the sliding mode observer. The current detection error will also cause a DC bias in the estimated quantity, thus reducing the observation accuracy and affecting the performance of the control system. Summary of the Invention

[0005] The purpose of the present invention is to provide a method and related device for improving the observation accuracy of sensorless control of permanent magnet synchronous motors, so as to solve the problem of the decrease in the observation accuracy of the sliding mode observer caused by back electromotive force harmonic error and DC bias in the existing sensorless control technology.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions:

[0007] In a first aspect, the present invention provides a method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor, including:

[0008] Establishing a mathematical model of a permanent magnet synchronous linear motor;

[0009] Estimating the back electromotive force information using a sliding mode observer according to the mathematical model of the permanent magnet synchronous linear motor;

[0010] Adopting a multi-stage cross-feedback third-order generalized integrator structure to filter out low-order harmonics and DC bias components in the estimated back electromotive force information;

[0011] Adopting an enhanced frequency-locked loop structure to achieve the tracking of speed during the filtering process of the cascaded third-order generalized integrator and improve the tracking accuracy for ramp speed changes;

[0012] The estimated back electromotive force after filtering estimates the position and speed through a phase-locked loop.

[0013] Further, the mathematical model of the permanent magnet synchronous linear motor:

[0014]

[0015] In Equation (1), u α , u β are respectively the components of the excitation voltage on the α and β axes; R is the excitation resistance; i α , i β are respectively the components of the excitation current on the α and β axes; L is the excitation inductance of the permanent magnet synchronous linear motor; τ is the permanent magnet pole pitch, v is the linear velocity of the mover, ψ f is the permanent magnet flux linkage; θ is the mover position.

[0016] Optionally, estimating the back electromotive force information using a sliding mode observer according to the mathematical model of the permanent magnet synchronous linear motor:

[0017] Rewriting the mathematical model of the permanent magnet synchronous linear motor into a current state equation:

[0018]

[0019] In Equation (2), e α , e β are the back electromotive forces:

[0020]

[0021] Designing a sliding mode observer from Equation (2), the observer and the control generator are as follows:

[0022]

[0023] In Equation (3), is the estimated value of the excitation current, z α , z β are the back electromotive force values estimated by the traditional sliding mode observer SMO:

[0024]

[0025] In Equation (4), sgn() is the sign function;

[0026] Subtracting Equation (3) from Equation (2) gives the current estimation error state equation:

[0027]

[0028] Construct the sliding mode surface s(x):

[0029]

[0030] From the reachability condition of the sliding mode observer, the switching gain k in the sliding mode observer satisfies:

[0031] k > max(|e α |, |e β |) (8)

[0032] Select a low-pass filter to filter out the high-frequency harmonics in the estimated back electromotive force:

[0033]

[0034] In Equation (9), is the estimated value of the back electromotive force after passing through the low-pass filter, ω c = 2πf c , f c is the cut-off frequency of the low-pass filter, and s is the Laplace operator.

[0035] Optionally, a multi-stage cross-feedback third-order generalized integrator structure is adopted to filter out the low-order harmonics and DC bias components in the estimated back electromotive force information:

[0036] The transfer function of the output and input of the third-order generalized integrator TOGI is as follows:

[0037]

[0038]

[0039]

[0040] where k is the gain coefficient, ω f is the center frequency, and s is the Laplace operator;

[0041] When the center frequency ω of the third-order generalized integrator TOGI f is equal to the fundamental frequency of the input signal, the output signal v1(t) only contains an AC component; the output signal v2(t) contains a DC component, and its AC component has the same amplitude as the input signal and a 90° phase lag; the output signal v3(t) only contains a DC component;

[0042] The multi-stage cross-feedback third-order generalized integrator MCF-TOGI structure is adopted to suppress low-order harmonics, and the cross-feedback relationship of each output signal is as follows:

[0043]

[0044]

[0045]

[0046] Among them

[0047]

[0048] Optionally, an enhanced phase-locked loop EFLL is used in cooperation with the multi-stage cross-feedback TOGI structure to achieve speed tracking during the filtering process:

[0049] The open-loop transfer function of the EFLL is:

[0050]

[0051] Then the speed error transfer function is as follows:

[0052]

[0053] 2 The speed error transfer function for a speed ramp change (c / s ) is:

[0054]

[0055] The steady-state speed error value is obtained:

[0056]

[0057] While using the EFLL in cooperation with the multi-stage cross-feedback TOGI structure to achieve speed tracking during the filtering process, the EFLL also ensures accurate speed tracking during the speed ramp change process.

[0058] The estimated back electromotive force after filtering estimates the position and speed through a phase-locked loop, realizing the closed-loop of sensorless control.

[0059] In a second aspect, the present invention provides a system for improving the observation accuracy of sensorless control of a permanent magnet synchronous linear motor, which is characterized by including:

[0060] A model establishment module for establishing a mathematical model of the permanent magnet synchronous linear motor;

[0061] An electromotive force information acquisition module for estimating the electromotive force information by using a sliding mode observer according to the mathematical model of the permanent magnet synchronous linear motor;

[0062] A filtering module for filtering out low-order harmonics and DC offset components in the estimated electromotive force information by using a multi-stage cross-feedback third-order generalized integrator structure;

[0063] A speed tracking module for realizing the tracking of speed during the cascaded third-order generalized integrator filtering process and improving the tracking accuracy of ramp speed changes by using an enhanced frequency-locked loop structure;

[0064] An output module for estimating the position and speed through a phase-locked loop after the filtered estimated electromotive force.

[0065] In a third aspect, the present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps of the method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor are realized.

[0066] In a fourth aspect, the present invention provides a computer-readable storage medium storing a computer program, and when the computer program is executed by a processor, the steps of the method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor are realized.

[0067] Compared with the prior art, the present invention has the following technical effects:

[0068] The present invention proposes a method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor. By using a multi-stage cross-feedback third-order generalized integrator (TOGI) structure, the 5th and 7th harmonics and DC offset components mainly contained in the estimated electromotive force are filtered out, and the observation accuracy of the observer is improved. By using an enhanced frequency-locked loop (EFLL) structure, the tracking of speed during the cascaded third-order generalized integrator filtering process is realized, and the tracking accuracy of ramp speed changes is improved. It can effectively solve the problem of the decline in the observation accuracy of the sliding mode observer caused by electromotive force harmonic errors and DC offsets in the sensorless control of the permanent magnet synchronous linear motor, so as to improve the performance of the sensorless control of the permanent magnet synchronous linear motor. Description of the Drawings

[0069] Figure 1 is a block diagram of third-order generalized integration (TOGI);

[0070] Figure 2 It is the block diagram of enhanced phase-locked loop (EFLL);

[0071] Figure 3 It is a simplified EFLL model;

[0072] Figure 4 This is the block diagram of the MCF-TOGI collaborative EFLL structure;

[0073] Figure 5 It is a block diagram of the sensorless control of the permanent magnet synchronous linear motor of the present invention. DETAILED DESCRIPTION

[0074] The present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0075] like Figure 5 As shown, the method for improving the observation accuracy of sensorless control of permanent magnet synchronous motor is specifically implemented according to the following steps.

[0076] Step 1: In the α-β coordinate system, obtain the voltage equation and back electromotive force equation of the permanent magnet synchronous linear motor;

[0077] Step 2: Rewrite the voltage equation in step 1 into a current state equation, and design a sliding mode observer based on it. Use a low-pass filter to filter out high-frequency harmonics and estimate the back electromotive force.

[0078] Step 3: If Figure 1 and Figure 4 As shown in the figure, a multi-stage cross-feedback third-order generalized integrator (MCF-TOGI) structure is used to filter out the 5th and 7th harmonics and DC bias components contained in the estimated back EMF, thereby improving the estimation accuracy of the observer.

[0079] Step 4: If Figure 2 and Figure 4 As shown in FIG, an enhanced frequency-locked loop (EFLL) structure is used to achieve speed tracking during the filtering process of the cascaded third-order generalized integrator and to improve the tracking accuracy of the ramp speed change;

[0080] Step 5: The filtered estimated back electromotive force is passed through a phase-locked loop to estimate the position and speed, thereby realizing closed-loop control without position sensor.

[0081] The following describes in detail a method for improving the sensorless control observation accuracy of a permanent magnet synchronous motor according to the present invention through a specific example.

[0082] The method for improving the sensorless control observation accuracy of a permanent magnet synchronous motor according to the present invention mainly comprises five parts: a current loop, a speed loop, a sliding mode observer, an MCF-TOGI-EFLL and a phase-locked loop.

[0083] This system adopts the i d =0 vector control method. The three-phase exciting currents i a , i b , i c output by the permanent magnet synchronous linear motor are measured by Hall sensors, and then the exciting currents i α , i β in the stationary two-phase coordinate system are obtained through 3s / 2s transformation. Then, the exciting currents i d , i q in the rotating two-phase coordinate system are obtained through 2s / 2r transformation. The sliding mode observer estimates the back electromotive force through the exciting voltage reference vectors u α , u β in the stationary two-phase coordinate system and the current vectors i α , i β output by the motor in the stationary two-phase coordinate system. After being filtered by MCF-TOGI-EFLL, the speed of the mover is estimated through a phase-locked loop. The difference between the estimated speed value and the speed reference value is taken, and the q-axis current reference value is obtained through the speed loop PI controller. Then, the difference between the q-axis current reference value and the actual q-axis current value is taken, and the q-axis voltage reference value is obtained through the PI controller. The difference between the d-axis current reference value and the actual value is taken, and the d-axis voltage reference value is obtained through the PI controller, that is, the exciting voltage reference vectors u d , u q in the rotating two-phase coordinate system are obtained. After 2r / 2s transformation, the exciting voltage reference vectors u α , u β in the stationary two-phase coordinate system are obtained. Finally, PWM signals are output through space vector pulse width modulation to drive the motor.

[0084] Step 1 is specifically as follows:

[0085] Step 1.1 The voltage equation of the permanent magnet synchronous linear motor in the α-β coordinate system is shown in Equation (21):

[0086]

[0087] In Equation (21), u α , u β are the components of the exciting voltage on the α and β axes respectively; R is the exciting resistance; i α , i β are the components of the exciting current on the α and β axes respectively; L is the exciting inductance of the permanent magnet synchronous linear motor; τ is the permanent magnet pole pitch, v is the mover linear velocity, ψ f is the permanent magnet flux linkage; θ is the mover position.

[0088] The back electromotive force equation of the permanent magnet synchronous linear motor is:

[0089]

[0090] Step 2 is specifically as follows:

[0091] Step 2.1 Rewrite the voltage equation of the permanent magnet synchronous linear motor into a current state equation:

[0092]

[0093] Step 2.2 Design a sliding mode observer from Equation (23), and the observer and control generator are as follows:

[0094]

[0095] In Equation (24), is the estimated value of the field current, and z α , z β are the back electromotive force values estimated by the traditional sliding mode observer SMO.

[0096]

[0097] In Equation (25), sgn() is the sign function;

[0098] Subtract Equation (24) from Equation (23) to obtain the current estimation error state equation:

[0099]

[0100] Construct the sliding mode surface s(x):

[0101]

[0102] According to the reachability condition of the sliding mode observer, the switching gain k in the sliding mode observer satisfies:

[0103] k > max(|e α |, |e β |) (28)

[0104] The switching function in the sliding mode observer will bring high-frequency interference to the estimated back electromotive force during high-frequency switching, affecting the estimation accuracy. Therefore, a low-pass filter is selected to filter out the high-frequency harmonics in the estimated back electromotive force:

[0105]

[0106] In Equation (30), is the estimated value of the back electromotive force after passing through the low-pass filter, ω c = 2πf c , f c is the cut-off frequency of the low-pass filter, and s is the Laplace operator.

[0107] Step 3 specifically is as follows:

[0108] In Step 3.1, the structural block diagram of the third-order generalized integrator (TOGI) is as Figure 1 shown, and the transfer function between the output and the input is as follows:

[0109]

[0110]

[0111]

[0112] In the formula, k is the gain coefficient, ω f is the center frequency, and s is the Laplace operator.

[0113] When the center frequency ω f of the TOGI is equal to the fundamental frequency of the input signal, the output signal v1(t) only contains the AC component. Due to the first-order differential term in the numerator of its transfer function, it has the same amplitude and phase as the AC fundamental component of the input signal and does not contain the DC component; the output signal v2(t) contains the DC component, and its AC component has the same amplitude as the input signal, with a phase lag of 90°; the output signal v3(t) only contains the DC component. It can be seen that the TOGI can suppress the influence of the DC component and harmonics in the input signal and extract the AC signal with the same frequency and phase as the fundamental component of the input signal.

[0114] In Step 3.2, if the gain k of the TOGI is too small, a large phase delay will be generated between the estimated value and the actual value of the back electromotive force, while a large gain k will make it difficult to filter out the 5th and 7th harmonic components with lower orders. Therefore, the MCF-TOGI structure as Figure 4 shown is proposed to mainly achieve the suppression of the 5th and 7th harmonics. The relationship of cross-feedback of each output signal is as follows:

[0115]

[0116]

[0117]

[0118] where

[0119]

[0120] Step 4 specifically is as follows:

[0121] The EFLL collaborative multi-stage cross-feedback TOGI structure is adopted to achieve the tracking of the speed during the filtering process. As Figure 4 shown, compared with the traditional frequency-locked loop, the EFLL can ensure the accurate tracking of the speed during the speed ramp change process, and the structure is asFigure 2 as shown

[0122] A simplified model of EFLL is as shown Figure 3 as shown, with an additional integral unit compared to the traditional frequency-locked loop. The open-loop transfer function of EFLL is:

[0123]

[0124] Then the speed error transfer function is as follows:

[0125]

[0126] For the speed error transfer function with respect to the speed ramp change (c / s 2 ), it is:

[0127]

[0128] The steady-state speed error value is obtained as:

[0129]

[0130] It can be seen that while using EFLL to cooperate with the multi-stage cross-feedback TOGI structure to achieve speed tracking during the filtering process, EFLL can also ensure accurate speed tracking during the speed ramp change process.

[0131] Step 5: The estimated back electromotive force after filtering is used by the phase-locked loop to estimate the position and speed, realizing the closed-loop of sensorless control.

[0132] Through the above process, the problem of the reduced observation accuracy of the sliding mode observer caused by the back electromotive force harmonic error and DC offset in the sensorless control of the permanent magnet synchronous linear motor can be efficiently solved, so as to improve the performance of the sensorless control of the permanent magnet synchronous linear motor.

[0133] In another embodiment of the present invention, a system for improving the observation accuracy of the sensorless control of the permanent magnet synchronous linear motor is provided, which can be used to implement the method for improving the observation accuracy of the sensorless control of the permanent magnet synchronous motor. Specifically, the system includes:

[0134] A model establishment module for establishing a mathematical model of the permanent magnet synchronous linear motor;

[0135] A back electromotive force information acquisition module for estimating the back electromotive force information using a sliding mode observer according to the mathematical model of the permanent magnet synchronous linear motor;

[0136] A filtering module for filtering out the low-order harmonics and DC offset components in the estimated back electromotive force information using a multi-stage cross-feedback third-order generalized integrator structure;

[0137] A speed tracking module, which uses an enhanced frequency-locked loop structure to achieve the tracking of speed during the filtering process of a cascaded third-order generalized integrator and improve the tracking accuracy for ramp speed changes;

[0138] An output module, which estimates the position and speed through a phase-locked loop after the filtered estimated back electromotive force.

[0139] The division of modules in the embodiments of the present invention is illustrative. It is only a logical function division. In actual implementation, there may be other division methods. In addition, in each embodiment of the present invention, each functional module may be integrated in a processor, may exist separately physically, or two or more modules may be integrated in one module. The above integrated modules may be implemented in the form of hardware or in the form of software functional modules.

[0140] In another embodiment of the present invention, a computer device is provided. The computer device includes a processor and a memory. The memory is used to store a computer program. The computer program includes program instructions. The processor is used to execute the program instructions stored in the computer storage medium. The processor may be a Central Processing Unit (CPU), or may also be other general-purpose processors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), Field-Programmable Gate Arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. It is the computing core and control core of the terminal, and is suitable for implementing one or more instructions. Specifically, it is suitable for loading and executing one or more instructions in the computer storage medium to implement the corresponding method flow or corresponding function; the processor described in the embodiments of the present invention can be used for the operation of the method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor.

[0141] In another embodiment of the present invention, the present invention further provides a storage medium, specifically a computer-readable storage medium (Memory). The computer-readable storage medium is a memory device in a computer device and is used to store programs and data. It can be understood that the computer-readable storage medium here can include both the built-in storage medium in the computer device and, of course, the extended storage medium supported by the computer device. The computer-readable storage medium provides a storage space, and the operating system of the terminal is stored in this storage space. Moreover, one or more instructions suitable for being loaded and executed by the processor are stored in this storage space, and these instructions can be one or more computer programs (including program codes). It should be noted that the computer-readable storage medium here can be a high-speed RAM memory or a non-volatile memory, such as at least one disk memory. One or more instructions stored in the computer-readable storage medium can be loaded and executed by the processor to implement the corresponding steps of the method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor in the above embodiments.

[0142] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes.

[0143] The present invention is described with reference to the flowcharts and / or block diagrams of methods, apparatuses (systems), and computer program products according to embodiments of the present invention. It should be understood that each flow and / or block in the flowchart and / or block diagram, as well as the combination of flows and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate a device for implementing the functions specified in Figure 1 one or more of the flows Figure 1 or a plurality of flows and / or blocks

[0144] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured article including an instruction device, and the instruction device implements the functions in Figure 1 one or more of the flowsFigure 1 The functions specified in one or more boxes.

[0145] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide for implementing the steps of the functions specified in one or more processes and / or boxes Figure 1 One process or more processes and / or boxes Figure 1 The steps of the functions specified in one or more boxes.

[0146] 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 them. Although the present invention has been described in detail with reference to the above embodiments, those of ordinary skill in the art should understand that: the specific implementation manners of the present invention can still be modified or equivalently replaced, and any modification or equivalent replacement that does not depart from the spirit and scope of the present invention should be covered by the protection scope of the claims of the present invention.

Claims

1. A method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor, characterized in that, Including: Establishing the mathematical model of a permanent magnet synchronous linear motor; Estimating the back electromotive force information using a sliding mode observer according to the mathematical model of the permanent magnet synchronous linear motor; Adopting a multi-stage cross-feedback third-order generalized integrator structure to filter out low-order harmonics and DC bias components in the estimated back electromotive force information; Adopting an enhanced frequency-locked loop structure to achieve speed tracking during the filtering process of the cascaded third-order generalized integrator and improve the tracking accuracy for ramp speed changes; Estimating the position and speed through a phase-locked loop for the filtered estimated back electromotive force; Adopting a multi-stage cross-feedback third-order generalized integrator structure to filter out low-order harmonics and DC bias components in the estimated back electromotive force information: The transfer function of the output and input of the third-order generalized integrator TOGI is as follows: where k is the gain coefficient, ω f is the center frequency, and s is the Laplace operator; When the center frequency ω of the third-order generalized integrator TOGI f equals the fundamental frequency of the input signal, the output signal v1(t) only contains an AC component; the output signal v2(t) contains a DC component, and its AC component has the same amplitude as the input signal and a phase lag of 90°; the output signal v3(t) only contains a DC component; Adopting a multi-stage cross-feedback third-order generalized integrator MCF-TOGI structure to achieve suppression of low-order harmonics, and the cross-feedback relationship of each output signal is as shown below: Where Adopting an enhanced phase-locked loop EFLL in cooperation with the multi-stage cross-feedback TOGI structure to achieve speed tracking during the filtering process: The open-loop transfer function of EFLL is: Then the speed error transfer function is as follows: For the speed ramp change (c / s 2 ), the speed error transfer function is as follows: The steady-state speed error value is obtained: While adopting the EFLL in cooperation with the multi-stage cross-feedback TOGI structure to achieve speed tracking during the filtering process, EFLL also ensures accurate speed tracking during the speed ramp change process.

2. The method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor according to claim 1, characterized in that, The mathematical model of the permanent magnet synchronous linear motor: In Equation (1), u α and u β are the components of the excitation voltage on the α and β axes respectively; R is the excitation resistance; i α and i β are the components of the excitation current on the α and β axes respectively; L is the excitation inductance of the permanent magnet synchronous linear motor; τ is the pole pitch of the permanent magnet; v is the linear velocity of the mover; ψ f is the magnetic flux linkage of the permanent magnet; θ is the mover position.

3. The method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor according to claim 1, characterized in that, Estimating the back electromotive force information using a sliding mode observer according to the mathematical model of the permanent magnet synchronous linear motor: Rewriting the mathematical model of the permanent magnet synchronous linear motor into a current state equation: In formula (2), e α and e β are back electromotive forces: Designing a sliding mode observer from Equation (2), and the observer and control generator are as follows: In Equation (3), is the estimated value of the excitation current, and z α , z β are the back electromotive force values estimated by the traditional sliding mode observer SMO: In Equation (4), sgn() is the sign function; Subtracting Equation (3) from Equation (2) to obtain the current estimation error state equation: Constructing the sliding mode surface s(x): From the reachability condition of the sliding mode observer, it is obtained that the switching gain k in the sliding mode observer satisfies: k > max(|e α |, |e β |) (8) Selecting a low-pass filter to filter out high-frequency harmonics in the estimated back electromotive force; In Equation (9), is the estimated back electromotive force after passing through the low-pass filter, ω c = 2πf c , f c is the cut-off frequency of the low-pass filter, and s is the Laplace operator.

4. The method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor according to claim 1, characterized in that, Estimating the position and speed through a phase-locked loop for the filtered estimated back electromotive force to complete the closed loop of sensorless control.

5. A system for improving the observation accuracy of sensorless control of a permanent magnet synchronous linear motor, characterized in that Including: A model establishment module for establishing the mathematical model of a permanent magnet synchronous linear motor; A back electromotive force information acquisition module for estimating the back electromotive force information using a sliding mode observer according to the mathematical model of the permanent magnet synchronous linear motor; A filtering module for filtering out low-order harmonics and DC bias components in the estimated back electromotive force information by adopting a multi-stage cross-feedback third-order generalized integrator structure; A speed tracking module for achieving speed tracking during the filtering process of the cascaded third-order generalized integrator and improving the tracking accuracy for ramp speed changes by adopting an enhanced frequency-locked loop structure; An output module for estimating the position and speed through a phase-locked loop for the filtered estimated back electromotive force; Adopting a multi-stage cross-feedback third-order generalized integrator structure to filter out low-order harmonics and DC bias components in the estimated back electromotive force information: The transfer function of the output and input of the third-order generalized integrator TOGI is as follows: where k is the gain coefficient, ω f is the center frequency, and s is the Laplace operator; When the center frequency ω of the third-order generalized integrator TOGI f is equal to the fundamental frequency of the input signal, the output signal v1(t) only contains an AC component; the output signal v2(t) contains a DC component, and its AC component has the same amplitude as the input signal and a phase lag of 90°; the output signal v3(t) only contains a DC component; The multi - stage cross - feedback third - order generalized integrator MCF - TOGI structure is adopted to suppress low - order harmonics, and the cross - feedback relationship of each output signal is as follows: Among them The enhanced frequency - locked loop EFLL is used in cooperation with the multi - stage cross - feedback TOGI structure to track the speed during the filtering process: The open - loop transfer function of EFLL is: Then the speed error transfer function is as follows: For the speed ramp change (c / s 2 ), the speed error transfer function is as follows: The speed error value in the steady - state situation is obtained: While using the EFLL in cooperation with the multi - stage cross - feedback TOGI structure to track the speed during the filtering process, the EFLL also ensures accurate speed tracking during the speed ramp change process.

6. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, the steps of the method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor as described in any one of claims 1 to 4 are implemented.

7. A computer-readable storage medium storing a computer program, characterized in that, When the computer program is executed by the processor, the steps of the method for improving the observation accuracy of sensorless control of a permanent magnet synchronous motor as described in any one of claims 1 to 4 are implemented.

Images