Online identification method and system for rotor time constant of sensorless induction motor

Abstract

The present invention belongs to the field of AC servo systems and discloses a method and system for online identification of the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer. The method comprises: estimating the rotor flux using a complex coefficient rotor flux estimator; injecting a biased sinusoidal excitation into the d-axis to obtain the rotor flux and filtered stator current along the dq axes through park transformation; online identification of the rotor time constant using a designed rotor time constant estimator based on a sliding mode observer; and estimating the stator frequency and rotor position using a phase-locked loop. The present invention decouples rotor time constant identification from rotor speed estimation, enabling parallel estimation of the two. The designed rotor flux estimator effectively suppresses DC bias and higher harmonics in back electromotive force. Compared to the traditional least squares method, the designed rotor time constant estimator based on a sliding mode observer improves the robustness of the estimation algorithm while ensuring convergence speed.

Description

Technical Field

[0001] The present invention belongs to but is not limited to the technical field of AC servo systems, and in particular relates to a method and system for online identification of the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer. Background Art

[0002] Induction motors, due to their low price, high reliability, and durability, have found widespread application in manufacturing equipment, rail transit, and new energy. Compared to control methods with speed sensors, sensorless control systems eliminate the need for encoders mounted on the motor shaft, avoiding interference between encoder signals and the control board, thus reducing control system costs and improving reliability. However, during operation of sensorless induction motor control systems, the rotor time constant often changes with rotor temperature. This change in the rotor time constant can affect the estimation of slip frequency and speed. Therefore, online identification of the rotor time constant is crucial for achieving high-performance sensorless control of induction motors.

[0003] Traditional rotor time constant estimation methods often require speed feedback, making them difficult to apply to sensorless vector control systems. Furthermore, rotor speed and rotor time constant are strongly coupled in the electrical model, making it difficult to satisfy sufficient excitation conditions for the parallel identification of rotor speed and rotor time constant when the flux amplitude is constant. Flux estimation is a key step in sensorless vector control. However, the voltage model used for flux observation, due to its pure integration component, is susceptible to DC bias in the back-EMF, causing the estimated flux to drift. Traditional methods often use low-pass filtering instead of pure integrators to suppress the influence of DC bias. However, low-pass filtering results in amplitude attenuation and phase lag in the estimated flux, thus affecting the accuracy of the rotor time constant and rotor position estimation. In practical sensorless control systems, noise can easily affect the accuracy of rotor time constant estimation. Improving the robustness of rotor time constant identification algorithms to noise is crucial for achieving accurate identification. Therefore, further exploration of simple and effective identification strategies is needed to improve the performance of rotor time constant estimation in sensorless induction motors.

[0004] In view of the above analysis, the technical problems that need to be solved urgently in the existing technology are:

[0005] (1) Traditional induction motor rotor time constant identification schemes require speed feedback. However, the rotor speed and rotor time constant are strongly coupled in the sensorless environment, making parallel identification impossible.

[0006] (2) The pure integrator in the traditional voltage model is easily affected by DC bias, which causes the estimated flux to saturate and shift;

[0007] (3) The traditional rotor time constant estimation method has poor robustness and is easily affected by noise. The proposed scheme designs a rotor time constant estimator based on a sliding mode observer. Summary of the Invention

[0008] In view of the problems existing in the prior art, the present invention provides a method and system for online identification of the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer.

[0009] The present invention is achieved by providing an online identification method for the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer, characterized in that the online identification method for the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer specifically comprises:

[0010] S1: Apply complex coefficient rotor flux estimator to estimate rotor flux;

[0011] S2: Inject a biased sinusoidal excitation into the d-axis, and obtain the rotor flux and filtered stator current in the dq-axis through park transformation;

[0012] S3: Apply the designed rotor time constant estimator based on sliding mode observer to identify the rotor time constant online;

[0013] S4: Apply a phase-locked loop to estimate the stator frequency and rotor position.

[0014] Furthermore, in S1, a complex coefficient rotor flux estimator is designed, and the expression of the applied complex coefficient rotor flux observer is as follows:

[0015]

[0016] Where L m is the mutual inductance, L r is the rotor inductance, j is the complex vector symbol, ω e is the stator frequency, calculated by the phase-locked loop, k f is the gain of the complex coefficient flux observer, u sα ,u sβ is the stator voltage, i sα ,i sβ is the stator current, ψ rα ,ψ rβ is the rotor flux, R s is the stator resistance, L s is the stator inductance, and σ is the leakage inductance coefficient.

[0017] Furthermore, the current-type flux observer expression of S2 in the rotating coordinate system is as follows:

[0018]

[0019] Where T r is the rotor time constant, i sd is the d-axis current, ψ rd is the d-axis magnetic flux. The current signal shown in formula (3) is injected into the d-axis:

[0020]

[0021] Where i d_rated is the d-axis rated current, is the d-axis reference current. The stator current is filtered with the following complex coefficients:

[0022]

[0023] Perform the Park transform on the flux observation value and the filtered current value as follows:

[0024]

[0025] Where i α_filter ,i β_filter ,i d_filter ,i q_filter are the filtered alpha-axis current, beta-axis current, d-axis current and q-axis current respectively.

[0026] Furthermore, the estimated rotor flux and filtered stator current are substituted into equation (7) to obtain S3:

[0027]

[0028] According to formula (8), the sliding mode observer is designed as follows:

[0029]

[0030] In the formula for The estimated value of 1 / T r The estimated value of ε1 is The estimation error, ε2 is 1 / T r Assume that the rotor time constant is a slowly varying parameter, that is, p(1 / T r )=0,

[0031] Furthermore, in S4, after completing the online identification of the rotor time constant, a phase-locked loop is further applied to obtain the rotor speed. The phase-locked loop expression is as follows:

[0032]

[0033] Where k p 、ki is the phase-locked loop gain, To estimate the running frequency, To estimate the rotor position.

[0034] Another object of the present invention is to provide an online identification system for the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer, the system specifically comprising:

[0035] A flux estimation module is used to estimate the rotor flux;

[0036] Sliding mode observation module, used to estimate the rotor time constant;

[0037] Phase-locked loop module, used to estimate stator frequency and rotor position.

[0038] In combination with the above technical solutions and the technical problems solved, the advantages and positive effects of the technical solutions to be protected by the present invention are as follows:

[0039] First, the present invention provides a sensorless induction motor rotor time constant online identification method based on a complex coefficient flux observer. The traditional induction motor rotor time constant identification scheme requires speed feedback, and the rotor speed and rotor time constant are strongly coupled in the sensorless state, making parallel identification impossible. The present invention injects a biased sinusoidal current into the d-axis to meet the sufficient excitation conditions for parallel identification of the rotor speed and rotor time constant. The pure integrator in the traditional voltage model is easily affected by the DC bias, causing the estimated flux to saturate and offset. The present invention proposes a complex coefficient rotor flux estimator that effectively suppresses the influence of the DC bias and high-order harmonics in the back electromotive force. The traditional rotor time constant estimation method has poor robustness and is easily affected by noise. The present invention designs a rotor time constant estimator based on a sliding mode observer, which can effectively improve the robustness of the estimator while ensuring the parameter convergence speed.

[0040] Second, the technical solution of the present invention solves a technical problem that people have long been eager to solve but have never been able to successfully solve:

[0041] The present invention provides a technical solution for sensorless vector control of an induction motor, which can accurately identify the rotor time constant without loading, thereby improving the accuracy of speed estimation when the resistance value drifts under long-term operation, and has high practical value.

[0042] Third, the present invention addresses the difficulty of accurately estimating the rotor time constant in real time in conventional induction motor control systems by employing an online identification method for the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer. Traditional induction motor control methods, lacking accurate rotor time constant identification methods, result in poor dynamic response and steady-state performance under various operating conditions. This makes it difficult to ensure accurate motor control, especially under conditions of large load variations and speed fluctuations.

[0043] This invention combines a complex-coefficient rotor flux estimator with a sliding-mode observer, significantly improving the dynamic response capability and steady-state control accuracy of induction motors by identifying the rotor time constant online in real time. The complex-coefficient flux observer more accurately estimates the rotor flux and offers enhanced interference immunity compared to traditional methods, while the sliding-mode observer offers significant advantages in handling system nonlinearities and uncertainties. Furthermore, by injecting a sinusoidal excitation signal and applying phase-locked loop technology, this invention enables stable estimation of rotor position and stator frequency under complex operating conditions, further enhancing the robustness and response speed of the control system.

[0044] Therefore, the technical solution of the present invention has made significant technical progress in solving the problem of online identification of rotor time constant. It not only improves the control accuracy and stability of the induction motor, but also enhances the adaptability and anti-interference ability of the system, providing reliable technical guarantee for high-performance sensorless motor control.

[0045] Fourth, the technical solution of the present invention solves the problem of online identification of the rotor time constant in induction motor control systems in industrial applications, significantly improving the performance and stability of the motor control system. Traditional induction motor control systems typically rely on sensors to obtain rotor position information, which not only increases the complexity and cost of the system, but also poses significant difficulties and limitations in the installation and maintenance of sensors in practical applications. In addition, traditional methods have difficulty in accurately estimating the rotor time constant in real time, especially under conditions of large changes in operating conditions or load fluctuations, which affects the control accuracy and response speed of the motor.

[0046] This invention addresses these technical challenges by employing a sensorless induction motor rotor time constant online identification method based on a complex coefficient flux observer. The complex coefficient flux observer estimates the rotor flux in real time without relying on physical sensors. Combined with the robustness of a sliding mode observer, this method enables accurate online identification of the rotor time constant. This technological advancement significantly enhances the dynamic response capability and steady-state control accuracy of the motor control system, ensuring stable operation under a variety of complex operating conditions.

[0047] Furthermore, the present invention utilizes phase-locked loop technology to further improve system stability and accuracy, enabling motor control to better adapt to the diverse operating conditions of practical applications, thereby enhancing the system's adaptability and reliability. This technical solution has broad application prospects and significant technological advancements in industrial applications, particularly in the field of high-performance motor control, providing strong support for the widespread application of sensorless motor control technology. BRIEF DESCRIPTION OF THE DRAWINGS

[0048] Figure 1 This is a flow chart of a method for online identification of rotor time constant of a sensorless induction motor based on a complex coefficient flux observer provided by an embodiment of the present invention;

[0049] Figure 2 This is a block diagram of a sensorless vector controller based on rotor time constant adaptation provided by an embodiment of the present invention;

[0050] Figure 3 This is a structural block diagram of a flux observer provided by an embodiment of the present invention;

[0051] Figure 4 This is a block diagram of a rotor time constant adaptive structure provided by an embodiment of the present invention;

[0052] Figure 5 This is a block diagram of a speed estimation structure based on a phase-locked loop provided by an embodiment of the present invention;

[0053] Figure 6 This is a module diagram of an online identification system for a sensorless induction motor rotor time constant based on a complex coefficient flux observer provided by an embodiment of the present invention;

[0054] Figure 7 This is a simulation diagram of rotor time constant estimation provided by an embodiment of the present invention;

[0055] Figure 8 This is a simulation diagram of magnetic flux estimation provided by an embodiment of the present invention;

[0056] Figure 9 This is a rotation speed estimation simulation diagram provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] like Figure 1 As shown, an embodiment of the present invention provides a method for online identification of the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer, the method specifically comprising:

[0059] S1: Apply complex coefficient rotor flux estimator to estimate rotor flux;

[0060] S2: Inject a biased sinusoidal excitation into the d-axis, and obtain the rotor flux and filtered stator current in the dq-axis through park transformation;

[0061] S3: Apply the designed rotor time constant estimator based on sliding mode observer to identify the rotor time constant online;

[0062] S4: Apply a phase-locked loop to estimate the stator frequency and rotor position.

[0063] The online identification method of the rotor time constant of a sensorless induction motor provided by the embodiment of the present invention is implemented through the following four steps:

[0064] **Step 1: Complex coefficient rotor flux estimation**

[0065] First, the system applies a complex-coefficient rotor flux estimator to estimate the induction motor's rotor flux. This estimator can handle the dynamic behavior of induction motors and accurately estimate the rotor flux amplitude and phase information under different operating conditions. This estimation lays the foundation for the subsequent identification of the rotor time constant, as accurate rotor flux estimation is crucial for online identification of the rotor time constant.

[0066] **Step 2: d-axis sinusoidal excitation injection and Park transform**

[0067] Next, a biased sinusoidal excitation signal is injected into the d-axis, and the stator current and rotor flux are converted to the dq coordinate system using the Park transform. This yields the rotor flux and filtered stator current components along the dq axes. The goal of this step is to extract characteristic information related to the rotor time constant using frequency domain methods, facilitating identification in subsequent steps.

[0068] **Step 3: Online identification of rotor time constant based on sliding mode observer**

[0069] After acquiring the dq-axis current and flux signals, the designed rotor time constant estimator based on a sliding mode observer is applied to online identify the rotor time constant of the induction motor. The sliding mode observer is highly robust to system uncertainties and can accurately estimate the rotor time constant in complex operating environments, thereby improving the stability and response speed of the motor control system.

[0070] **Step 4: Phase-locked loop stator frequency and rotor position estimation**

[0071] Finally, a phase-locked loop (PLL) is used to estimate the stator frequency and rotor position. This PLL accurately tracks the stator frequency under dynamic conditions and simultaneously estimates the relative position of the rotor. This information is crucial for speed estimation and accurate control of the rotor flux direction in the sensorless control algorithm, ensuring efficient operation of the entire induction motor control system.

[0072] The online identification method of the rotor time constant of the sensorless induction motor based on the complex coefficient flux observer is shown in the control structure diagram. Figure 2 shown.

[0073] The S1, voltage-type flux observer does not include the rotor time constant. The present invention uses a voltage-type flux estimator to estimate the rotor flux. The traditional voltage-type flux estimator is shown as follows:

[0074]

[0075] Where u sα ,u sβ is the stator voltage, i sα ,i sβ is the stator current, ψ rα ,ψ rβ is the rotor flux, R s is the stator resistance, L s is the stator inductance, σ is the leakage inductance coefficient, L m is the mutual inductance, L r is the rotor inductance. The pure integral operation in formula (1) will be affected by the DC bias and cause the rotor flux estimation value to drift. The traditional low-pass filtering solution will cause phase delay and amplitude attenuation. In this invention, a complex coefficient rotor flux estimator is designed. The flux estimation block diagram is shown in the figure. Figure 3 As shown, the expression of the applied complex coefficient rotor flux observer is as follows.

[0076]

[0077] Where j is the complex vector symbol, ω e is the stator frequency, calculated by the phase-locked loop, k f is the gain of the complex coefficient flux observer.

[0078] The expression of S2, the current type flux observer in the rotating coordinate system is as follows:

[0079]

[0080] Where T r is the rotor time constant, i sd is the d-axis current, ψ rd is the d-axis magnetic flux. From the above formula, it can be seen that when a constant value is injected into the d-axis, pψ r=0, so L m i sd / T r -ψ r / T r = 0, the rotor time constant cannot be identified. In order to meet the sufficient excitation conditions for identifying the rotor time constant, a current signal as shown in formula (3) is injected into the d-axis

[0081]

[0082] Where i d_rated is the d-axis rated current, The complex coefficient flux observer ensures the amplitude-frequency characteristics of the fundamental component, and the phase-frequency characteristics are consistent with the pure integrator, but it will produce amplitude attenuation and phase shift at non-center frequencies. Since the high-frequency component of the rotor flux will produce a certain amplitude attenuation and phase shift, in order to ensure the accurate identification of the rotor time constant, the stator current is subjected to the following complex coefficient filtering:

[0083]

[0084] Perform the Park transform on the flux linkage observation value and the filtered current value as follows.

[0085]

[0086] Where i α_filter ,i β_filter ,i d_filter ,i q_filter are the filtered alpha-axis current, beta-axis current, d-axis current and q-axis current respectively.

[0087] S3, design the rotor time constant estimator. The rotor time constant identification block diagram is as follows Figure 4 As shown, the estimated rotor flux and filtered stator current are substituted into equation (7) to obtain:

[0088]

[0089] According to formula (8), the sliding mode observer is designed as follows:

[0090]

[0091] In the formula for The estimated value of 1 / T r The estimated value of ε1 is The estimation error, ε2 is 1 / T r Assume that the rotor time constant is a slowly varying parameter, that is, p(1 / T r )=0, In order to prove the stability of the designed parameter estimator, the following Lyapunov function is defined:

[0092]

[0093] The derivative of formula (10) can be obtained:

[0094]

[0095] Substituting formula (9) into the above formula, we can get

[0096]

[0097] Pick It can be guaranteed that the Lyapunov function is negative definite, that is, the state error system is stable.

[0098] In step S4, after completing the online identification of the rotor time constant through the above steps, a phase-locked loop is further applied to obtain the rotor speed. The phase-locked loop expression is as follows:

[0099]

[0100] Where k p 、k i is the phase-locked loop gain, To estimate the running frequency, To estimate the rotor position. The speed estimation block diagram based on the phase-locked loop is as follows Figure 5 shown.

[0101] like Figure 6 As shown, an embodiment of the present invention provides an online identification system for the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer, specifically comprising:

[0102] A flux estimation module is used to estimate the rotor flux;

[0103] Sliding mode observation module, used to estimate the rotor time constant;

[0104] Phase-locked loop module, used to estimate stator frequency and rotor position.

[0105] The present invention verifies the proposed online identification of the rotor time constant of the induction motor without sensor by building a simulation model. The main parameters set for the simulation model motor include: rated power P = 1.5Kw, rated current I rated =6.3A, pole pair number p=2, stator resistance R s =1.3Ω, rotor time constant T r =0.156s, mutual inductance L m =0.11H, stator leakage inductance L σ=0.00528H, speed command is 300rpm, load is 8N.m. The online identification process of rotor time constant is as follows: Figure 7 As shown in Figure 1, the initial value is set to 0.1s, the rotor time constant estimation is enabled at 2s, and the rotor time constant gradually converges to the true value. Figure 8 It can be seen that the designed complex coefficient flux observer can effectively estimate the rotor flux. Figure 9 It can be seen that before the rotor time constant converges to the true value, there is a large error between the estimated speed and the true speed due to the deviation in slip estimation. When the rotor time constant estimator is enabled, the error gradually decreases to 0, verifying the effectiveness of the online identification of the rotor time constant.

[0106] It should be noted that the embodiments of the present invention can be implemented by hardware, software, or a combination of software and hardware. The hardware portion can be implemented using dedicated logic; the software portion can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art will appreciate that the above-mentioned devices and methods can be implemented using computer-executable instructions and / or contained in processor control code, for example, such as a carrier medium such as a disk, CD or DVDROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. Such code is provided on a carrier medium such as a disk, CD or DVDROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The device and its modules of the present invention can be implemented by hardware circuits such as very large-scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or can be implemented by software executed by various types of processors, or can be implemented by a combination of the above-mentioned hardware circuits and software, such as firmware.

[0107] The above description is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Any modifications, equivalent substitutions and improvements made by any technician familiar with this technical field within the technical scope disclosed by the present invention and within the spirit and principles of the present invention should be covered by the scope of protection of the present invention.

Claims

1. An online identification method for the rotor time constant of a sensorless induction motor based on a complex coefficient flux observer, characterized in that: The method specifically includes: S1: Apply complex coefficient rotor flux estimator to estimate rotor flux; S2: Inject a biased sinusoidal excitation into the d-axis, and obtain the rotor flux and filtered stator current in the dq-axis through park transformation; S3: Apply the designed rotor time constant estimator based on sliding mode observer to identify the rotor time constant online; S4: Apply a phase-locked loop to estimate the stator frequency and rotor position; In S1, a complex coefficient rotor flux estimator is designed. The expression of the applied complex coefficient rotor flux observer is as follows: Where L m is the mutual inductance, L r is the rotor inductance, j is the complex vector symbol, ω e is the stator frequency, calculated by the phase-locked loop, k f is the gain of the complex coefficient flux observer, u sα ,u sβ is the stator voltage, i sα ,i sβ is the stator current, ψ rα ,ψ rβ is the rotor flux, R s is the stator resistance, L s is the stator inductance, σ is the leakage inductance coefficient; The expression of S2, the current type flux observer in the rotating coordinate system is as follows: Where T r is the rotor time constant, i sd is the d-axis current, ψ rd is the d-axis flux; the current signal shown in formula (4) is injected into the d-axis: Where i d_rated is the d-axis rated current, is the d-axis reference current; the stator current is filtered with the following complex coefficients: Perform the Park transform on the flux observation value and the filtered current value as follows: Where i α_filter ,i β_filter ,i d_filter ,i q_filter are the filtered alpha-axis current, beta-axis current, d-axis current and q-axis current respectively; The S3 is obtained by substituting the estimated rotor flux and the filtered stator current into formula (3): According to formula (8), the sliding mode observer is designed as follows: In the formula for The estimated value of 1 / T r The estimated value of ε1 is The estimation error, ε2 is 1 / T r The estimated error is: Assuming that the rotor time constant is a slowly varying parameter, that is, p(1 / T r )=0, After completing the online identification of the rotor time constant in S4, a phase-locked loop is further applied to obtain the rotor speed. The phase-locked loop expression is as follows: Where k p 、k i is the phase-locked loop gain, To estimate the running frequency, To estimate the rotor position.

2. A sensorless induction motor rotor time constant online identification system based on a complex coefficient flux observer based on the sensorless induction motor rotor time constant online identification method based on a complex coefficient flux observer as claimed in claim 1, characterized in that: The system specifically includes: Complex coefficient rotor flux estimator, used to estimate the rotor flux of induction motor; A d-axis sinusoidal excitation injection module is used to inject a biased sinusoidal excitation signal into the d-axis; Park transformation module, used to convert the rotor flux and filtered stator current into the dq coordinate system; Sliding mode observer for online identification of rotor time constant based on estimated rotor flux and filtered stator current; Phase-locked loop module to estimate stator frequency and rotor position.

3. The online identification system for rotor time constant of sensorless induction motor based on complex coefficient flux observer according to claim 2, characterized in that: The complex coefficient rotor flux estimator is designed to estimate the rotor flux through the stator voltage, stator current, stator frequency, and stator and rotor parameters, providing a more accurate flux estimation result to ensure accurate identification of the rotor time constant.

4. The online identification system for rotor time constant of sensorless induction motor based on complex coefficient flux observer according to claim 2, characterized in that: The d-axis sinusoidal excitation injection module and Park transformation module are used to convert the stator current and rotor flux signals into a rotating coordinate system and perform filtering processing to obtain the current and flux signals under the dq axes. These signals will be used to identify the rotor time constant.

5. The online identification system for rotor time constant of sensorless induction motor based on complex coefficient flux observer according to claim 2, characterized in that: The sliding mode observer in the system is designed to identify the rotor time constant online based on the estimated rotor flux and filtered stator current, and the phase-locked loop module is further used to estimate the rotor position and stator frequency after the rotor time constant is identified to ensure the accuracy and stability of the motor control system.

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