A real-time estimation method, recording medium and system for permanent magnet synchronous motor rotor position

Abstract

The present invention belongs to the field of electric motor control technology, and particularly relates to a real-time method for estimating the rotor position of a permanent magnet synchronous motor. The method extracts the effective flux phase information of the motor and performs differential processing on the effective flux phases of two adjacent samples to obtain a feedforward estimated speed component. A position error signal is constructed and sent to a phase-locked loop for proportional-integral closed-loop regulation. After low-pass filtering, a closed-loop estimated speed component is obtained. The two speed components are added and low-pass filtered to obtain an estimated speed #imgabs0#. This is then integrated to obtain the estimated rotor position #imgabs2# of the permanent magnet motor. This method optimizes speed estimation and is highly portable. It is applicable to various implementations of back-electromotive force models in position sensorless control methods for permanent magnet synchronous motors, significantly improving the dynamic response of traditional position sensorless control methods. The present invention also provides a non-transitory readable recording medium storing a program for the method and a system containing the medium. The program can be called through a processing circuit to execute the method.

Description

Technical Field

[0001] The invention belongs to the technical field of motor control and discloses a real-time estimation method, recording medium and system for the rotor position of a permanent magnet synchronous motor. Background Art

[0002] Permanent magnet synchronous motor position sensorless control technology has the advantages of simplifying the physical structure of the drive system, improving the anti-interference ability of the drive system, and saving the cost of the drive system. It has become one of the indispensable core technologies in the application of electric drive engineering.

[0003] When the motor's operating speed is higher than 5% of the rated speed, the signal-to-noise ratio of the back-EMF signal at the motor port is significantly improved. In this case, the back-EMF can be used to obtain rotor flux information. Then, a phase-locked loop (PLL) is used to lock the phases of the rotor fluxes, which are orthogonal to each other in the stationary coordinate system, thereby achieving real-time estimation of the permanent magnet synchronous motor's rotor position and speed.

[0004] However, using a traditional phase-locked loop (PLL) to lock orthogonal rotor flux phases in a stationary coordinate system requires a closed-loop negative feedback control mechanism. Whenever the PLL's input signal changes, the PLL requires a certain adjustment time to reach steady state, which affects the dynamic response performance of the motor rotor position estimation. For example, in practical applications, when the motor's set speed undergoes a sudden and significant change, the estimated position lags behind the actual position due to the limitations of the PLL's adjustment process. The instantaneous deviation between the estimated and set speeds increases significantly, reducing the motor's speed and torque responsiveness, easily causing severe current fluctuations, and in severe cases, even leading to drive system instability.

[0005] The response speed of conventional phase-locked loops (PLLs) limits the high acceleration capability of position-free electric drive systems and their ability to control step commands. This limitation severely degrades the speed regulation performance of certain permanent magnet synchronous motor (PMSM) drive systems with high dynamic speed regulation requirements.

[0006] How to obtain accurate motor rotor position estimation results in real time when the motor speed undergoes a large sudden change is a problem that technicians in this field urgently need to solve. Summary of the Invention

[0007] In view of the above problems, the present invention provides a real-time estimation method for the rotor position of a permanent magnet synchronous motor, comprising the following steps:

[0008] The effective flux is extracted using the voltage and current signal data of the motor port, and normalized to obtain the effective flux phase information with unit amplitude and orthogonal phase.

[0009] The effective flux phase of two adjacent samples is differentiated and then the feedforward estimated speed component is obtained through low-pass filtering.

[0010] Construct a position error signal and send it to the phase-locked loop for proportional-integral closed-loop regulation. After low-pass filtering, the closed-loop estimated speed component is obtained.

[0011] The feedforward estimated speed component With closed-loop estimated speed component Add, low-pass filter the addition result to get the final estimated speed right After integration, the estimated rotor position of the permanent magnet motor is obtained

[0012] Preferably, extracting the effective flux linkage includes integrating the back electromotive force using a first-order inertia filter, and performing amplitude and phase compensation on the obtained stator flux linkage data.

[0013] Preferably, the first-order inertial filter is composed of a high-pass filter connected in series with an integrator, and its transfer function is:

[0014] Where, ω H Represents the cutoff frequency of the high-pass filter, and S represents the complex frequency variable in the Laplace transform.

[0015] Preferably, the calculation of the compensation amount in the amplitude and phase compensation uses the following method:

[0016]

[0017] Where Amp com Represents the stator flux amplitude compensation, Pha com Represents the compensation amount of the stator flux phase, ω e Represents the rotor speed.

[0018] Preferably, the normalization method is to first square the effective magnetic flux components of the α-axis and the β-axis respectively, take the sum and then take the square root to obtain the amplitude of the effective magnetic flux vector, and then divide the effective magnetic flux components of the α-axis and the β-axis by the amplitude of the effective magnetic flux vector respectively, thereby realizing the normalization of the effective magnetic flux components of the α-axis and the β-axis, and obtaining the normalized magnetic flux phase information of the α-axis and the normalized magnetic flux phase information of the β-axis.

[0019] Preferably, the differential processing of the effective flux phase of two adjacent samples includes taking the difference between the current sampled flux phase information and the last sampled flux phase information, and then dividing it by the sampling time to obtain the feedforward estimated speed component.

[0020]

[0021] Where, is the feedforward estimated speed component, and It represents the phase of the effective flux method at the current time n and the previous time n-1, and ΔT is the time interval between the two estimated times.

[0022] Preferably, the method for constructing the position error signal is: according to the principle of heterodyne method, the position error signal

[0023]

[0024] Where Δθ e is the original position error, θ re is the true phase information of the effective flux, is the estimated phase information of the effective flux method.

[0025] Another embodiment of the present invention provides a non-transitory readable recording medium for storing one or more programs including a plurality of instructions. When the instructions are executed, the processing circuit will execute the above-mentioned method for real-time estimation of the rotor position of a permanent magnet synchronous motor.

[0026] Another embodiment of the present invention provides a real-time estimation system for the rotor position of a permanent magnet synchronous motor, comprising a processing circuit and a memory electrically coupled thereto, wherein the memory is configured to store at least one program, the program comprising a plurality of instructions, and the processing circuit executes the program to perform the above-mentioned method for real-time estimation of the rotor position of a permanent magnet synchronous motor.

[0027] Compared with the prior art, the present invention provides a method, recording medium, and system for real-time estimation of the rotor position of a permanent magnet synchronous motor, which have the following beneficial effects:

[0028] 1. Wide applicability and high portability: This method is applicable to various implementations of the back-EMF model in position sensorless control methods for permanent magnet synchronous motors or induction motors. It can significantly improve the dynamic response of traditional position sensorless control methods, enabling them to exhibit high efficiency and applicability in a variety of application scenarios.

[0029] 2. Optimized speed estimation mechanism: The speed estimation process uses a speed feedforward combined with a phase-locked loop to estimate the speed. Among them, the feedforward estimated speed component is obtained by differential processing of the flux phase information. The speed component can be understood as the coarse adjustment component of the estimated speed, which makes the estimated speed quickly approach the actual speed; the phase-locked loop adjusts the position error signal in a closed loop to obtain the closed-loop estimated speed component. This speed component can be understood as a fine-tuning component of the estimated speed, eliminating the static error of the estimated speed. With closed-loop estimated speed component The sum is taken as the final estimated speed right After integration, the estimated rotor position of the permanent magnet motor is obtained The proposed method realizes real-time and accurate estimation of the motor rotor position when the motor speed undergoes a large sudden change, which is beneficial to the high dynamic and high precision speed regulation of the permanent magnet synchronous motor drive system, and significantly improves the high acceleration capability of the drive system and the control ability of step instructions.

[0030] 3. Simple and practical design: This method has a simple structure and excellent dynamic performance, which can meet the engineering requirements for high dynamic speed regulation of permanent magnet synchronous motors. This advantage makes the present invention more applicable in practical engineering applications. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 This is a block diagram of the principle of extracting effective magnetic flux using a first-order inertial integrator in an embodiment of the present invention;

[0032] Figure 2 This is a block diagram of the principle of constructing an effective flux normalization signal in an embodiment of the present invention;

[0033] Figure 3 Extracting the feedforward estimated speed component in the embodiment of the present invention Principle block diagram;

[0034] Figure 4 Extracting the closed-loop estimated speed component in the embodiment of the present invention Principle block diagram;

[0035] Figure 5 An overall principle block diagram of a method for estimating the position of a permanent magnet motor according to an embodiment of the present invention;

[0036] Figure 6 This is a performance verification diagram of an embodiment of the present invention on an 80kW permanent magnet drive platform;

[0037] Figure 7 This is a performance verification diagram of an embodiment of the present invention on a high-speed air compressor permanent magnet drive platform. DETAILED DESCRIPTION

[0038] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions in the embodiments of the present invention will be described below in conjunction with the accompanying drawings. The described embodiments are part of the embodiments of the present invention, but not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without making any innovative efforts shall fall within the scope of protection of the present invention.

[0039] like Figure 5 As shown, an embodiment of a method for real-time estimation of the rotor position of a permanent magnet synchronous motor provided by the present invention includes the following steps:

[0040] Step A) Extract the effective flux of the motor through back EMF: The voltage and current signals at the motor port are combined with the concept of effective flux, and the effective flux is extracted using a first-order inertia integrator. The amplitude and phase of the effective flux are then compensated (see Figure 1 ).

[0041] Step B) Normalize the effective flux signal: After obtaining the effective flux, perform a normalization operation on it. The purpose of the normalization operation is to obtain flux phase information with unit amplitude and phase quadrature. This eliminates the effects of flux amplitude and rotor speed variations on the phase-locked loop feedforward gain, thereby improving the stability of the position estimation closed loop.

[0042] Step C) Extracting the feedforward speed component by flux phase differential The differential link is used to perform differential processing on the normalized flux phase of two adjacent samples, and then the feedforward estimated speed component is obtained through the low-pass filtering link. Make the estimated speed approach the actual speed quickly.

[0043] Step D) Phase-locked loop extraction of closed-loop estimated speed component First, the position error signal Δθ is constructed based on the concept of trigonometric function equivalent infinitesimal, and then the phase-locked loop is used to adjust the position error signal to obtain the closed-loop estimated speed component. Eliminate static errors in estimated speed.

[0044] Step E) Feedforward estimation of speed component With closed-loop estimated speed component Add together to form the final estimated speed The feedforward estimated speed component With closed-loop estimated speed component Add and perform appropriate low-pass filtering on the addition result to obtain the final estimated speed right After integration, the estimated rotor position of the permanent magnet motor is obtained

[0045] In step A) of this embodiment, the specific implementation of extracting the effective flux of the motor through the back electromotive force is as follows: in the two-phase stationary α-β coordinate system, the relationship between the stator flux, stator current and rotor permanent magnet flux of the permanent magnet synchronous motor can be expressed as: ψ r =ψ s -L αβ I s

[0046] Where, ψ r represents the rotor permanent magnet flux vector; ψ s represents the stator flux vector; L αβ and I s Represent the inductance matrix and current matrix respectively. For salient pole permanent magnet synchronous motor, the scalar form of the inductance matrix can be expressed as

[0047]

[0048] Where, L α 、L β Represents the α and β axis inductance respectively; L d 、L q Represents the d-axis and q-axis inductances respectively; θ e Represents the rotor position angle.

[0049] At this time, the stator flux vector ψ s The scalar form of can be expressed as:

[0050]

[0051] Where, ψ sα , ψ sβ Represent the magnitude of the stator flux mapped to the α and β axes respectively; i d 、i q Represent the d-axis and q-axis currents respectively; ψ f Represents the modulus of the rotor permanent magnet excitation flux. Performing an equivalent transformation on the above formula, we can obtain:

[0052]

[0053] In the above formula, the stator flux on the left side of the equal sign can be obtained by integrating the back electromotive force of the motor port, and the coefficient on the right side of the equal sign is is the effective flux vector The modulus, as a scalar, reflects the effective magnetic flux size.

[0054] The effective flux vector is Its expression is Although its amplitude is similar to the rotor permanent magnet flux vector ψ r The amplitudes are different, but their directions are the same, so the effective flux can be used to make an equivalent estimate of the rotor position.

[0055] In order to extract the effective magnetic flux of the motor through the back electromotive force, a first-order inertia filter is used to integrate the back electromotive force. The principle block diagram is as follows: Figure 1 As shown. The first-order inertial filter is composed of a high-pass filter connected in series with an integrator, and its transfer function can be expressed as

[0056]

[0057] Where, ω H Represents the cutoff frequency of the high-pass filter. S represents the complex frequency variable in the Laplace transform. G FOIF (s) represents the transfer function of the first-order inertial filter FOIF.

[0058] Compared to a pure integrator, the advantage of a first-order inertia filter is that it uses a front-end high-pass filter to suppress the DC offset of the input back-EMF signal, thus preventing the motor from generating DC bias magnetization. However, ideally, the stator flux is obtained by integrating the back-EMF with a pure integrator. When a first-order inertia filter is used for integration, the obtained stator flux suffers from amplitude attenuation and phase delay, which need to be compensated. The compensation for the stator flux amplitude and phase can be expressed as

[0059]

[0060] Where Amp com Represents the stator flux amplitude compensation, Pha com Represents the compensation amount of the stator flux phase, ω e Represents the rotor speed.

[0061] In step B), the effective flux signal is normalized, such as Figure 2 As shown. The principle of normalization is to first square the effective flux components of the α-axis and β-axis respectively, take the sum and then take the square root, and finally get the amplitude of the effective flux vector. Then divide the effective flux components of the α-axis and β-axis by the amplitude of the effective flux vector respectively, and then realize the normalization of the effective flux components of the α-axis and β-axis, and get the normalized flux phase information cosθ of the α-axis re , and obtain the normalized magnetic flux phase information sinθ of the β axis re .

[0062] In step C), the feedforward estimated speed component is extracted based on the flux phase differential The principle block diagram is as follows Figure 3 The mathematical principle is to use the difference between the current sampled flux phase information and the last sampled flux phase information, and then divide it by the sampling time, that is, to perform differential processing on the flux information to obtain the feedforward estimated speed component Right now

[0063]

[0064] Where, is the feedforward estimated speed component, and It represents the phase information of the effective flux method at the current moment (n) and the previous moment (n-1), and ΔT is the time interval between the two estimated moments.

[0065] In step D), the closed-loop estimated speed component is extracted based on the phase-locked loop The principle block diagram is as follows Figure 4 First, based on the concept of infinitesimal equivalent of trigonometric functions, the position error signal is constructed. Its mathematical principle can be expressed as

[0066]

[0067] Where Δθ e is the original position error, θ re is the true phase information of the effective flux, is the estimated phase information of the effective flux method, f(Δθ e ) is the original position error signal. The position error signal f(Δθ e ) is sent to PI regulation, and then appropriate filtering is added to obtain the closed-loop estimated speed component

[0068] In step E), the feedforward estimated speed component With closed-loop estimated speed component Add and perform appropriate low-pass filtering on the addition result to obtain the final estimated speed

[0069]

[0070] Where, is the feedforward estimated speed component, is the closed-loop estimated speed component, is the estimated speed that will eventually participate in the speed closed-loop control. After integration, the estimated rotor position of the permanent magnet motor is obtained

[0071] Finally combined Figure 6 and Figure 7 The experimental waveforms further illustrate the control performance of the method.

[0072] Figure 6The following figure demonstrates the verification of this invention on an 80kW permanent magnet synchronous motor drive platform, showing the speed curve and DQ current when the motor is operating with a speed ramp of 1000 rpm / s. The experimental results show that the estimated speed closely tracks the actual speed without significant error, the Q-axis current can be quickly adjusted, and the drive system exhibits excellent dynamic performance.

[0073] Figure 7 The figure shows the verification results of the present invention on the high-speed air compressor permanent magnet synchronous motor drive platform, which respectively shows the speed curve and DQ current when the speed ramp used by the motor is 30000rpm / s. Figure 4 Similar to the experiment, when the motor is running, the estimated speed strictly tracks the actual speed, there is no obvious error in the estimated speed, and the q-axis current can be adjusted quickly, and the drive system has good dynamic performance.

[0074] These two test scenarios verified the effectiveness and reliability of the method of the present invention in different applications, and further demonstrated the engineering applicability of the technical solution and its superior dynamic adjustment capabilities.

[0075] Compiling the above-mentioned method steps into a program and then storing it on a hard disk or other non-transitory storage medium constitutes an embodiment of the present invention's "a non-transitory readable recording medium"; and electrically connecting the storage medium to a computer processor and completing real-time estimation of the permanent magnet synchronous motor rotor position through data processing constitutes an embodiment of the present invention's "a real-time estimation system for the permanent magnet synchronous motor rotor position".

[0076] It will be understood by those skilled in the art that embodiments of the present invention may be provided as methods, systems, or computer program products. Thus, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present invention may take the form of a computer program product implemented on one or more computers containing computer-usable program code, or on available storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.).

[0077] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, as well as combinations of processes and / or blocks in the flowcharts and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts and / or block diagrams. Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in a block or multiple blocks.

[0078] These computer program instructions may 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 produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0079] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0080] Finally, it should be noted that the above descriptions are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A real-time estimation method for the rotor position of a permanent magnet synchronous motor, characterized in that: The following steps are involved: The effective flux is extracted using the voltage and current signal data of the motor port, and normalized to obtain the effective flux phase information with unit amplitude and orthogonal phase. The effective flux phase of two adjacent samples is differentiated and then the feedforward estimated speed component is obtained through low-pass filtering. Construct a position error signal and send it to the phase-locked loop for proportional-integral closed-loop regulation. After low-pass filtering, the closed-loop estimated speed component is obtained. The feedforward estimated speed component With closed-loop estimated speed component Add, low-pass filter the addition result to get the final estimated speed right After integration, the estimated rotor position of the permanent magnet motor is obtained Extracting the effective flux linkage includes integrating the back EMF using a first-order inertial filter and performing amplitude and phase compensation on the obtained stator flux linkage data; The first-order inertial filter is composed of a high-pass filter connected in series with an integrator, and its transfer function is: Where, ω H Represents the cutoff frequency of the high-pass filter, and S represents the complex frequency variable in the Laplace transform.

2. The method for real-time estimation of the rotor position of a permanent magnet synchronous motor according to claim 1, characterized in that: The calculation of the compensation amount in amplitude and phase compensation uses the following method: Where Amp com Represents the stator flux amplitude compensation, Pha com Represents the compensation amount of the stator flux phase, ω e Represents the rotor speed.

3. The method for real-time estimation of the rotor position of a permanent magnet synchronous motor according to claim 2, characterized in that: The normalization method is to first square the effective magnetic flux components of the α-axis and the β-axis respectively, take the sum and then take the square root to obtain the amplitude of the effective magnetic flux vector, and then divide the effective magnetic flux components of the α-axis and the β-axis by the amplitude of the effective magnetic flux vector respectively, thereby realizing the normalization of the effective magnetic flux components of the α-axis and the β-axis, and obtaining the normalized magnetic flux phase information of the α-axis and the normalized magnetic flux phase information of the β-axis.

4. The method for real-time estimation of the rotor position of a permanent magnet synchronous motor according to claim 3, characterized in that: Differentiation of the effective flux phase of two adjacent samples includes taking the difference between the current sampled flux phase information and the last sampled flux phase information, and then dividing it by the sampling time to obtain the feedforward estimated speed component. Where, is the feedforward estimated speed component, and It represents the phase of the effective flux method at the current time n and the previous time n-1, and ΔT is the time interval between the two estimated times.

5. The method for real-time estimation of the rotor position of a permanent magnet synchronous motor according to claim 4, characterized in that: The method of constructing the position error signal is as follows: According to the principle of heterodyne method, the position error signal Where Δθ e is the original position error, θ re is the true phase information of the effective flux, is the estimated phase information of the effective flux method.

6. A non-transitory readable recording medium for storing one or more programs comprising a plurality of instructions, characterized in that: When the instruction is executed, the processing circuit is caused to execute the real-time estimation method for the rotor position of a permanent magnet synchronous motor according to any one of claims 1 to 5.

7. A real-time estimation system for the rotor position of a permanent magnet synchronous motor, comprising a processing circuit and a memory electrically coupled thereto, characterized in that: The memory configuration stores at least one program, the program including a plurality of instructions, and the processing circuit runs the program to execute a real-time estimation method for the rotor position of a permanent magnet synchronous motor according to any one of claims 1-5.

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