Self-adaptive control method, system and equipment for rotor time constant of induction motor

Abstract

The invention relates to the technical field of motor control, and discloses an induction motor rotor time constant adaptive control method, system and device, and the method comprises the steps: obtaining the current operation condition of a motor; determining a current angle threshold according to the current operation condition; dividing the running state of the motor into a first state and a second state based on a given current angle and a current angle threshold value of the motor; according to the divided operation states, a corresponding rotor time constant control strategy is executed so as to carry out indirect vector control of the induction motor, in the first state, a reactive power-based model reference adaptive algorithm is started, and a first rotor time constant is identified and output online; and in the second state, forbidding a reactive power-based model reference adaptive algorithm, and generating a second rotor time constant based on the first rotor time constant locked in the first state, thereby realizing reliable and accurate application of the reactive power MRAS scheme in a full working condition range.

Description

Technical Field

[0001] This application relates to the field of motor control technology, and in particular to an adaptive control method, system and device for the rotor time constant of an induction motor. Background Technology

[0002] Indirect vector control technology for induction motors enables decoupled control of motor torque and flux linkage, achieving dynamic performance comparable to that of DC motors. In this technology, the rotor time constant (Tr) is a crucial control parameter, its accuracy directly determining the system's current and torque control performance. In actual operation, the motor's rotor inductance is affected by magnetic saturation, while the rotor resistance drifts due to rotor temperature rise, skin effect, and slip frequency changes, causing the rotor time constant to deviate significantly from its nominal value. Numerous studies and experiments have shown that this deviation can exceed 50%, and without compensation, it will directly lead to decreased motor torque control accuracy, reduced efficiency, and even system oscillations. To identify and compensate for changes in the rotor time constant online, various adaptive identification algorithms have been proposed. Among them, the reactive power-based model reference adaptive system method has received widespread attention due to its simple structure and ease of engineering implementation.

[0003] However, this reactive power-based MRAS method has an inherent and serious drawback: its convergence and stability are highly dependent on the operating conditions of the motor, especially in regions with small or large current angles, where the method may fail or even diverge. Summary of the Invention

[0004] This application provides an adaptive control method, system, and device for the rotor time constant of an induction motor, which solves the technical problem of identification divergence in related reactive power MRAS schemes and achieves the technical effect of reliable and accurate application of the reactive power MRAS scheme in the entire operating range.

[0005] To achieve the above objectives, the main technical solutions adopted in this application include: In a first aspect, embodiments of this application provide an adaptive control method for the rotor time constant of an induction motor. The method includes: acquiring the current operating condition of the motor; determining a current angle threshold based on the current operating condition, wherein the current angle threshold is used to define the current angle operating region in which a reactive power-based model reference adaptive algorithm can stably converge; dividing the operating state of the motor into a first state and a second state based on a given current angle of the motor and the current angle threshold; and executing a corresponding rotor time constant control strategy according to the divided operating states to perform indirect vector control of the induction motor, wherein: in the first state, the reactive power-based model reference adaptive algorithm is enabled to identify and output a first rotor time constant online; in the second state, the reactive power-based model reference adaptive algorithm is disabled, and a second rotor time constant is generated based on the first rotor time constant locked in the first state.

[0006] The adaptive control method for rotor time constant of induction motors provided in this application determines the stability boundary of the adaptive algorithm based on the current operating conditions, and performs operating state division and strategy switching accordingly. This solves the inherent defect that the traditional single reactive power MRAS algorithm cannot be stably applied under all operating conditions. It can fully utilize the high-precision online identification advantage of the adaptive algorithm in the stable region to ensure control accuracy, and in the unstable region, it can prevent system divergence by disabling the algorithm and inheriting and locking the rotor resistance estimate, thus ensuring absolute control stability. This achieves reliable, accurate, and safe application of rotor time constant identification technology based on reactive power MRAS across the entire operating range.

[0007] Optionally, the current angle threshold includes a lower threshold angle and a critical current angle. Based on the given current angle of the motor and the current angle threshold, the operating state of the motor is divided into a first state and a second state, including: if the given current angle is greater than the lower threshold angle and less than the critical current angle, the operating state of the motor is divided into the first state; if the given current angle is less than the lower threshold angle or the given current angle is greater than the critical current angle, the operating state of the motor is divided into the second state.

[0008] By introducing the lower threshold angle and critical current angle, the complex operating domain of the motor is accurately divided into convergence and divergence regions. This not only provides a clear decision basis for the intelligent switching of control strategies, but also ensures that the system can proactively and timely identify high-risk operating conditions that may lead to divergence, achieving the optimal balance between control performance and operational robustness across the entire operating range.

[0009] Optionally, the method further includes: determining the critical current angle corresponding to the operating condition according to the operating condition-current angle mapping table, wherein the operating condition-current angle mapping table is constructed as follows: obtaining multiple preset operating condition points, the preset operating condition points including motor speed and stator current amplitude; for any preset operating condition point, generating multiple candidate current angles within a preset current angle range according to a preset step size; calculating the motor reactive power value corresponding to each candidate current angle based on the motor speed and stator current amplitude of the preset operating condition point; extracting the minimum value among the various motor reactive power values, and determining the candidate current angle corresponding to the minimum value as the critical current angle of the preset operating condition point; constructing the operating condition-current angle mapping table based on each preset operating condition point and the corresponding critical current angle.

[0010] By scanning and calculating the reactive power of each candidate current angle within a preset current angle range with fine step sizes, the minimum reactive power point characterizing the system's convergence boundary is accurately captured, thereby defining the critical current angle under different operating conditions. Based on this pre-generated operating condition-current angle mapping table, the system can quickly and reliably obtain the safe operating boundary of the current operating condition in real-time control, fundamentally avoiding functional divergence of rotor time constant adaptive identification in the high current angle region, and ensuring stable operation of the system under all operating conditions.

[0011] Optionally, the method further includes: determining the preset current angle range based on the lower threshold angle and the upper threshold angle, wherein the lower threshold angle ranges from 20 to 30 degrees; and the preset step size is set to 0.1 degrees.

[0012] Setting the lower threshold angle within the range of 20° to 30° systematically avoids convergence hysteresis in the low current angle region, while preventing excessive compression of the effective working range of the stable convergence region (first state), ensuring the robustness and effectiveness of the switching control strategy in practice. By determining the scan step size to 0.1 degrees, this step size is sufficient to accurately capture the subtle trends of reactive power changes with the current angle, ensuring the high reliability of the critical current angle boundary determined accordingly, and effectively distinguishing between stable and potentially unstable regions. Simultaneously, it avoids unnecessary expansion of computational load and mapping table size due to excessively fine step sizes, guaranteeing the engineering practicality and efficiency of offline calculation and online table lookup processes.

[0013] Optionally, the reactive power-based model reference adaptive algorithm is enabled to identify and output the first rotor time constant online, including: determining the power deviation based on the difference between the actual reactive power and the expected reactive power of the motor; and adjusting the estimated value of the first rotor time constant based on the power deviation.

[0014] By enabling a reactive power-based model reference adaptive algorithm and dynamically adjusting the rotor time constant based on the deviation between the expected and actual reactive power, real-time online tracking and compensation of rotor parameter changes are achieved. A closed-loop adaptive observation system is constructed, which can automatically correct rotor time constant drift caused by factors such as temperature rise and magnetic saturation, thereby improving the parameter robustness and torque control accuracy of the vector control system.

[0015] Optionally, adjusting the estimated value of the first rotor time constant based on the power deviation includes: decreasing the estimated value of the first rotor time constant if the power deviation is greater than zero; and increasing the estimated value of the first rotor time constant if the power deviation is less than zero.

[0016] When the estimated rotor time constant deviates from the true value, the system can automatically generate a reverse correction force to drive the estimated value to continuously approach the true value, thereby ensuring that the reactive power-based model reference adaptive system (MRAS) has globally stable convergence characteristics, which is beneficial for achieving online accurate identification of the rotor time constant.

[0017] Optionally, generating a second rotor time constant based on a first rotor time constant locked in the first state includes: determining a corresponding rotor resistance estimate based on the first rotor time constant locked in the first state; and generating the second rotor time constant based on the rotor resistance estimate and the rotor inductance corresponding to the current operating condition.

[0018] By converting the locked first rotor time constant into an estimated rotor resistance value and combining it with the rotor inductance under real-time operating conditions to generate a second rotor time constant, the system can save the accurate identification results obtained under stable operating conditions as rotor resistance parameters that are more sensitive to temperature and change more slowly after exiting adaptive identification. The rotor inductance, which only responds to changes in magnetic saturation, is then dynamically corrected. This allows the system to continue to provide a high-precision and smoothly changing rotor time constant even in unstable operating conditions where divergence risks are avoided. Ultimately, the system balances stability and torque control accuracy across the entire operating range.

[0019] Secondly, embodiments of this application provide an adaptive control system for the rotor time constant of an induction motor. The system includes: an acquisition module for acquiring the current operating condition of the motor; a determination module for determining a current angle threshold based on the current operating condition, wherein the current angle threshold is used to define the current angle operating region in which a reactive power-based model reference adaptive algorithm can stably converge; a partitioning module for partitioning the operating state of the motor into a first state and a second state based on a given current angle of the motor and the current angle threshold; and an execution module for executing a corresponding rotor time constant control strategy according to the partitioned operating state to perform indirect vector control of the induction motor, wherein: in the first state, the reactive power-based model reference adaptive algorithm is enabled to identify and output a first rotor time constant online; in the second state, the reactive power-based model reference adaptive algorithm is disabled, and a second rotor time constant is generated based on the first rotor time constant locked in the first state.

[0020] Thirdly, embodiments of this application provide a computer device, including: a memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the above-described adaptive control method for the rotor time constant of an induction motor by executing the computer instructions.

[0021] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer instructions, which are used to cause a computer to execute the above-described adaptive control method for the rotor time constant of an induction motor.

[0022] Fifthly, embodiments of this application provide a computer program product, including computer instructions, which are used to cause a computer to execute the above-described adaptive control method for the rotor time constant of an induction motor. Attached Figure Description

[0023] To more clearly illustrate the technical solutions in the specific embodiments or related technologies of this application, the drawings used in the description of the specific embodiments or related technologies will be briefly introduced below. Obviously, the drawings described below are some embodiments of this application. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0024] Figure 1 A flowchart of an adaptive control method for the rotor time constant of an induction motor provided in an embodiment of this application; Figure 2 This is a schematic diagram illustrating the change in reactive power provided in an embodiment of this application; Figure 3This is a schematic diagram of the control strategy provided in the embodiments of this application; Figure 4 A schematic diagram of an adaptive control system for the rotor time constant of an induction motor provided in an embodiment of this application; Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application. Detailed Implementation

[0025] To make the objectives, technical solutions, and advantages of the embodiments of this application clearer, the technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, not all embodiments. Based on the embodiments of this application, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this application.

[0026] Indirect vector control technology for induction motors enables decoupled control of motor torque and flux linkage, achieving dynamic performance comparable to that of DC motors. In this technology, the rotor time constant (Tr) is a crucial control parameter, its accuracy directly determining the system's current and torque control performance. However, in actual operation, the motor's rotor inductance is affected by magnetic saturation, and the rotor resistance drifts due to rotor temperature rise, skin effect, and slip frequency changes, causing the rotor time constant to deviate significantly from its nominal value. Numerous studies and experiments have shown that this deviation can exceed 50%. Without compensation, this will directly lead to decreased motor torque control accuracy, reduced efficiency, and even system oscillations.

[0027] To identify and compensate for changes in the rotor time constant online, various adaptive identification algorithms have been proposed. Among them, the Model Reference Adaptive System (MRAS) based on reactive power has attracted widespread attention and is considered to have high engineering application prospects due to its simple structure, ease of engineering implementation, and the fact that its reference model does not include stator resistance parameters susceptible to temperature influence. This method constructs a reference model and an adjustable model based on instantaneous reactive power, and uses the error signals output by both to adaptively adjust the estimated value of the rotor time constant through a proportional-integral controller, thereby achieving tracking of changes in actual parameters.

[0028] However, traditional reactive power MRAS schemes lack global convergence in the DQ current plane and may diverge in regions where the current angle is close to 90° or 0°. Under high-speed, high-load conditions, the current angle becomes significantly larger after magnetic weakening adjustment, potentially exceeding this convergence region. Furthermore, some special operating conditions require maintaining a low current angle, which can also lead to convergence difficulties and ultimately cause system malfunctions.

[0029] The reasons for the divergence in traditional reactive power MRAS schemes are analyzed as follows: The reactive power of a motor is defined as the cross product of the stator voltage and the stator current. In a two-phase synchronous rotating coordinate system along the dq axis, the actual reactive power of the motor can be expressed as: In the formula, Q1 is the actual reactive power of the motor, and U s I is the phase voltage vector. s i is the phase current vector. ds i qs For the d-axis and q-axis stator currents, u ds u qs These are the d-axis and q-axis stator voltages.

[0030] When the rotor time constant is equal to the true value, the rotor magnetic field orientation is accurate. Based on the stator voltage formula and the rotor flux linkage formula, equation (1) can be derived into another calculation form: In the formula, Q2 is called the expected reactive power, which is the actual reactive power under the condition of accurate orientation. If there is a deviation in the rotor time constant, resulting in inaccurate orientation, then the actual reactive power Q1 calculated according to formula (1) will deviate from the expected value Q2. This reactive power deviation is expressed as: The reactive power deviation ΔQ reflects the deviation between the used rotor time constant and the true value. Therefore, the rotor time constant can be adjusted online based on this reactive power deviation. In practical engineering, the current loop adjustment error can be ignored. The d-axis and q-axis stator voltages and currents in equation (2) can be represented by known given values, and the inductance parameter L... s L a The values ​​are obtained by looking up a table based on the given currents along the d and q axes.

[0031] The formula for estimating the rotor time constant based on Lyapunov stability theory is as follows: In the formula, k ω =1 / ω e In order to prevent ω during the project e A value of 0 results in a denominator of 0, for kω Amplitude limiting is applied; T r0 This is the initial value of the rotor time constant set in the program, in order to reduce the adjustment margin.

[0032] The above is the identification process of the traditional reactive power MRAS scheme. The reason why the rotor time constant estimate calculated by equation (4) can converge to the true value is that in most current operating regions of the first or fourth quadrant, the reactive power of the motor is negatively correlated with the dq axis current angle. Under the same stator current amplitude, the larger the current angle value, the smaller the reactive power, and vice versa. When the rotor time constant used in the program is smaller than the true value, the actual current angle value is greater than the given current angle. Based on the negative correlation between the current angle and reactive power, the calculated actual reactive power Q1 will be less than the expected value Q2, and the deviation ΔQ is less than 0. Then the value calculated by equation (4) is less than the expected value Q2. Decrease Increasing it brings it closer to the true value; conversely, decreasing it only happens when... When the value equals the true value, the deviation ΔQ is zero, and the calculated result of PI in equation (4) remains unchanged, thus achieving steady-state convergence. Based on the above reasoning, only when the current angle and reactive power satisfy a negative correlation can steady-state convergence be achieved. Only then can the estimated value converge. However, in the current angle region close to 90° or close to 0°, the current angle and reactive power do not satisfy a negative correlation, or the negative correlation is very weak. This leads to inefficiency or even divergence in the traditional reactive power MRAS scheme in this current region.

[0033] Therefore, although the reactive power MRAS method has many theoretical advantages, its application in practical products is severely limited by the aforementioned convergence range issue. Related technologies have not provided a complete engineering solution that can effectively define and safely cross its convergence boundary, which has become a pressing technical problem to be solved in this field.

[0034] This application provides an adaptive control method for the rotor time constant of an induction motor, which ensures stable operation of the rotor time constant adaptive identification function based on reactive power MRAS under all operating conditions. It should be noted that the steps shown in the flowcharts of the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowcharts, in some cases, the steps shown or described may be executed in a different order than that shown here.

[0035] Please refer to Figure 1 , Figure 1 A flowchart of an adaptive control method for the rotor time constant of an induction motor, as provided in an embodiment of this application, is shown below. Figure 1 As shown, the process includes the following steps: S1, obtain the current operating condition of the motor.

[0036] The current operating condition characterizes the current operating point of the induction motor. Based on the current operating condition, the set of parameters that determine the stable convergence boundary of the reactive power-based model reference adaptive algorithm can be determined. The current operating condition includes at least the motor speed and stator current amplitude.

[0037] S3. Based on the current operating conditions, determine the current angle threshold. The current angle threshold is used to define the current angle operating region in which the reactive power-based model reference adaptive algorithm can converge stably.

[0038] For any given combination of motor speed and stator current amplitude, the corresponding current angle threshold can be calculated. By calculating the current angle threshold, the accuracy of Tr identification can be ensured under all operating conditions.

[0039] S5, based on the given current angle of the motor and the current angle threshold, the operating state of the motor is divided into a first state and a second state.

[0040] In an indirect vector control system for an induction motor, the given current angle is the desired phase angle of the stator current vector relative to the d-axis of the rotor field-oriented coordinate system, determined by the upper-level optimization control strategy (such as MTPA control or field weakening control). By comparing the given current angle with a dynamically determined current angle threshold, the continuously changing motor operating domain is clearly divided into two control stages: "stable convergence" and "potential divergence." This provides a reliable decision-making basis for subsequently switching between two distinctly different rotor time constant control strategies, avoiding the divergence risk of traditional single adaptive algorithms under unstable conditions, and ensuring the stability and reliability of the control system across the entire operating range.

[0041] S7. Based on the divided operating states, execute the corresponding rotor time constant control strategy to perform indirect vector control of the induction motor, wherein: in the first state, the reactive power-based model reference adaptive algorithm is enabled to identify and output the first rotor time constant online; in the second state, the reactive power-based model reference adaptive algorithm is disabled, and a second rotor time constant is generated based on the rotor resistance estimate locked in the first state.

[0042] When the motor is operating in the first state, it is in the stable convergence region. The system uses a reactive power-based model reference adaptive algorithm to identify the high-precision first rotor time constant in real time. Based on this, the system calculates the rotor resistance estimate in real time. The instant the system is about to switch or has just switched to the second state (non-convergence region), the system immediately captures and fixes the rotor resistance estimate calculated at that moment. This captured and fixed value is the locked rotor resistance estimate.

[0043] By enabling high-precision online adaptive identification in the first state (stable convergence region) and decisively disabling the algorithm when switching to the second state (unstable region), and instead using the rotor resistance parameters inherited and locked from the first state to generate the rotor time constant, the reactive power-based model reference adaptive system is ultimately ensured to operate safely, stably, and with high precision across the entire operating range.

[0044] The adaptive control method for rotor time constant of induction motors provided in this application determines the stability boundary of the adaptive algorithm based on the current operating conditions, and performs operating state division and strategy switching accordingly. This solves the inherent defect that the traditional single reactive power MRAS algorithm cannot be stably applied under all operating conditions. It can fully utilize the high-precision online identification advantage of the adaptive algorithm in the stable region to ensure control accuracy, and in the unstable region, it can prevent system divergence by disabling the algorithm and inheriting and locking the rotor resistance estimate, thus ensuring absolute control stability. This achieves reliable, accurate, and safe application of rotor time constant identification technology based on reactive power MRAS across the entire operating range.

[0045] In some specific embodiments, the current angle threshold includes a lower threshold angle and a critical current angle. Based on the given current angle of the motor and the current angle threshold, the operating state of the motor is divided into a first state and a second state, including: if the given current angle is greater than the lower threshold angle and less than the critical current angle, the operating state of the motor is divided into the first state; if the given current angle is less than the lower threshold angle or the given current angle is greater than the critical current angle, the operating state of the motor is divided into the second state.

[0046] By introducing the lower threshold angle and critical current angle, the complex operating domain of the motor is accurately divided into convergence and divergence regions. This not only provides a clear decision basis for the intelligent switching of control strategies, but also ensures that the system can proactively and timely identify high-risk operating conditions that may lead to divergence, achieving the optimal balance between control performance and operational robustness across the entire operating range.

[0047] In some specific embodiments, the critical current angle corresponding to the operating condition is determined according to the operating condition-current angle mapping table. The operating condition-current angle mapping table is constructed as follows: Multiple preset operating condition points are obtained, including motor speed and stator current amplitude; for any preset operating condition point, multiple candidate current angles are generated within a preset current angle range according to a preset step size; based on the motor speed and stator current amplitude of the preset operating condition points, the motor reactive power value corresponding to each candidate current angle is calculated; the minimum value among the various motor reactive power values ​​is extracted, and the candidate current angle corresponding to the minimum value is determined as the critical current angle of the preset operating condition point; the operating condition-current angle mapping table is constructed based on each preset operating condition point and its corresponding critical current angle.

[0048] By scanning and calculating the reactive power of each candidate current angle within a preset current angle range with fine step sizes, the minimum reactive power point characterizing the system's convergence boundary is accurately captured, thereby defining the critical current angle under different operating conditions. Based on this pre-generated operating condition-current angle mapping table, the system can quickly and reliably obtain the safe operating boundary of the current operating condition in real-time control, fundamentally avoiding functional divergence of rotor time constant adaptive identification in the high current angle region, and ensuring stable operation of the system under all operating conditions.

[0049] Specifically, the critical current angle is obtained as follows.

[0050] According to the reactive power calculation formula: It can be seen that the reactive power of the motor consists of two parts, which are named q1 and q2 respectively, and defined as follows: In induction motor control, the given current angle range is (-90°, 90°). In practical applications, the given current amplitude I is usually obtained based on different operating conditions such as speed, voltage, and given torque. s Given a current angle, ignoring the current closed-loop control error, the actual output current amplitude is also expressed using the given quantity I. s The actual current angle is represented by θ, and equation (6) can be written as: During the rotor time constant convergence process, the adaptive scheme achieves zero reactive power deviation by adjusting the true current angle. This process can adjust the current amplitude I. s Rotational speed ω r Assuming it remains constant, therefore in equation (7), the inductance term L... s L a It varies only with respect to the current angle θ, and also with the synchronization frequency ω. e The expression is To make the synchronization frequency ω e To make it a quantity that varies only with respect to the current angle θ, the rotor resistance R in equation (8) needs to be changed. r Represented by known offline identification values. According to equations (7-8), during the convergence process of Tr, the reactive power can be expressed as a function of the current angle θ. If this function is monotonically decreasing in the domain |θ|∈[0, 90), then the reactive power is negatively correlated with the current angle, and the system can achieve convergence. However, as the current angle increases, the synchronization frequency ω... e The current will increase, which has a reverse effect on the monotonically decreasing trend of the function. In addition, as the q-axis current increases, it will also limit the decrease of the function value.

[0051] In some specific embodiments, a certain automotive induction motor was tested; please refer to [the documentation / reference]. Figure 2 , Figure 2 This is a schematic diagram illustrating the change in reactive power provided in an embodiment of this application. Figure 2 As shown, under a representative current / speed condition, the reactive power Q2 and the trends of q1 and q2 with respect to the current angle θ are observed. Figure 2 In the figure, the curve of reactive power Q2 with respect to the current angle first decreases and then increases. Angle 2 represents the critical current angle when the reactive power curve changes from decreasing to increasing under this current / speed condition. Here, the derivative of reactive power with respect to the current angle is 0. Angle 3 represents the limiting current angle corresponding to the maximum slip (the given current angle will not exceed this limiting current angle).

[0052] In the Tr identification system, angle 1 is the lower threshold angle, and angle 2 is the upper threshold angle. The system operating conditions are divided into three segments: 1) Current angle between angle 1 and angle 2: In this segment, reactive power is negatively correlated with the current angle and the rate of change is large, satisfying the convergence condition of the rotor time constant identification system. 2) Current angle between angle 2 and angle 3: In this segment, reactive power is positively correlated with the current angle, causing the rotor time constant identification system to fail. 3) Current angle between 0 degrees and angle 1: In this segment, the rate of change of reactive power with respect to the current angle is small or even tends to 0, posing a risk of decreased or even divergent rotor time constant identification performance, and cannot meet the needs of operating conditions with drastic parameter changes.

[0053] When the current angle is between angle 1 and angle 2, the rotor time constant adaptive identification system can operate normally. However, when the current angle is between angle 2 and angle 3, the system needs to exit the adaptive identification phase and switch to other control schemes to avoid the risk of divergence. Considering that the current angle operating range of the induction motor is at or above the MTPA angle in most operating conditions, and that angle 1 does not directly affect the divergence of the system (mainly affecting the convergence speed), the specific value of angle 1 can be selected through actual debugging, with an empirical range of 20-30 degrees.

[0054] Regarding the acquisition of the critical current angle (angle 2), theoretically, the critical current angle can be obtained by setting the derivative of reactive power with respect to the current angle to 0. However, the nonlinear function of the inductance parameter in formula (5) with respect to the current angle is difficult to obtain. In engineering, the inductance is usually obtained by looking up a table based on the current angle. Therefore, the critical current angle under each specific working condition is searched by offline numerical calculation, and then the critical current angle is obtained by looking up a table online according to the actual working condition. This method has the advantages of high efficiency and reliability. The specific method is as follows: Based on the motor's speed range and current amplitude range, multiple specific speed and current points are selected to cover the entire speed / current operating condition. For example, if the motor speed range is 0-20000 RPM and the current amplitude range is 0-600 A, the following values ​​can be selected as specific speed points: 0, 1000, 2000, 3000, ..., 20000 RPM; and the following values ​​can be selected as specific current points: 100, 200, 300, ..., 600 A. The number of points selected needs to consider the load rate of the lookup program to avoid excessive calculation. After selecting the specific points, the operating condition-current angle mapping table shown in Table 1 below is obtained: Table 1 Rotation point 1 Rotation point 2 Rotation point 3 …… Current point 1 <![CDATA[θ 11 ]]> <![CDATA[θ 21 ]]> <![CDATA[θ 31 ]]> …… Current point 2 <![CDATA[θ 12 ]]> <![CDATA[θ 22 ]]> <![CDATA[θ 32 ]]> …… Current point 3 <![CDATA[θ 13 ]]> <![CDATA[θ 23 ]]> <![CDATA[θ 33 ]]> …… …… …… …… …… …… In Table 1, θ nm This represents the critical current angle corresponding to the preset operating conditions at speed point n and current point m. The critical current angle for each preset operating condition is calculated, typically offline using a computer script. Taking one of these preset operating conditions as an example, let the current point for that condition be I. s1 The rotational speed point is ω r1 (Converted to electrical angle), the system limiting current angle is θ. max The critical current angle for this preset operating condition is calculated as follows: Select θ step As the current angle step size (e.g., 0.1° for motoring and -0.1° for generator), the current angle array elements are 0 and θ. step 2*θ step 、…、θ max Then, based on formula (5), 0-θ is obtained by traversal calculation. max The absolute value of the reactive power Q2 corresponding to each specific current angle within the range is obtained. The absolute values ​​of the current angles are arranged from smallest to largest to obtain the corresponding reactive power calculation result array. Finally, the critical current angle is found according to the index number of the minimum value Min(Q2) of the array element.

[0055] The above method allows for the pre-calculation of the critical current angle corresponding to each current amplitude under various operating speeds. These angle values ​​are then imported into the project code in the form of a two-dimensional Map as shown in Table 1, and the two-dimensional lookup table function func(ω) is used to perform the lookup. rI s By performing an online two-dimensional lookup table, the critical current angle value under actual working conditions can be obtained in real time.

[0056] In some specific embodiments, the preset current angle range is determined based on the lower threshold angle and the upper threshold angle, wherein the value range of the lower threshold angle is 20-30 degrees; and the preset step size is set to 0.1 degrees.

[0057] The determination of the lower threshold angle relies on engineering experience and debugging optimization. The upper threshold angle needs to cover the maximum current angle that the motor may reach, such as 85°, which can be determined based on the motor's maximum field weakening capability. The upper and lower threshold angles together determine the preset current angle range.

[0058] Through repeated debugging, it was found that setting the lower threshold angle in the range of 20° to 30° can systematically avoid the convergence hysteresis problem in the low current angle region, while avoiding excessive compression of the effective working range of the stable convergence region (first state), thus ensuring the robustness and effectiveness of the switching control strategy in practice.

[0059] By setting the scan step size to 0.1 degrees, this step size is sufficient to accurately capture the subtle trends in reactive power variation with the current angle, ensuring the high reliability of the critical current angle boundary determined accordingly, and effectively distinguishing between stable and potentially unstable regions. Simultaneously, it avoids unnecessary expansion of computational load and mapping table size due to excessively fine step sizes, guaranteeing the engineering practicality and efficiency of both offline calculations and online table lookups.

[0060] In some specific embodiments, the reactive power-based model reference adaptive algorithm is enabled to identify and output the first rotor time constant online, including: determining the power deviation based on the difference between the actual reactive power and the expected reactive power of the motor; and adjusting the estimated value of the first rotor time constant based on the power deviation.

[0061] The power deviation between the actual reactive power and the desired reactive power is calculated and input into the PI controller. The output of the PI controller is used to dynamically adjust the estimated value Tr of the first rotor time constant, so that the actual current angle tracks the desired current angle, achieving adaptive control.

[0062] By enabling a reactive power-based model reference adaptive algorithm and dynamically adjusting the rotor time constant based on the deviation between the expected and actual reactive power, real-time online tracking and compensation of rotor parameter changes are achieved. A closed-loop adaptive observation system is constructed, which can automatically correct rotor time constant drift caused by factors such as temperature rise and magnetic saturation, thereby improving the parameter robustness and torque control accuracy of the vector control system.

[0063] In some specific embodiments, adjusting the estimated value of the first rotor time constant based on the power deviation includes: if the power deviation is greater than zero, decreasing the estimated value of the first rotor time constant; if the power deviation is less than zero, increasing the estimated value of the first rotor time constant.

[0064] If the power deviation is greater than zero, the estimated value of Tr is decreased; if it is less than zero, the estimated value of Tr is increased. By establishing this explicit negative feedback regulation law, the abstract parameter identification problem is transformed into a well-directed closed-loop control problem. When the estimated value of the rotor time constant deviates from the true value, the system can automatically generate a reverse correction force to drive the estimated value to continuously approach the true value. This ensures that the reactive power-based model reference adaptive system (MRAS) has globally stable convergence characteristics, which is beneficial for achieving accurate online identification of the rotor time constant.

[0065] In some specific embodiments, generating a second rotor time constant based on a first rotor time constant locked in the first state includes: determining a corresponding rotor resistance estimate based on the first rotor time constant locked in the first state; and generating the second rotor time constant based on the rotor resistance estimate and the rotor inductance corresponding to the current operating condition.

[0066] By converting the locked first rotor time constant into an estimated rotor resistance value and combining it with the rotor inductance under real-time operating conditions to generate a second rotor time constant, the system can save the accurate identification results obtained under stable operating conditions as rotor resistance parameters that are more sensitive to temperature and change more slowly after exiting adaptive identification. The rotor inductance, which only responds to changes in magnetic saturation, is then dynamically corrected. This allows the system to continue to provide a high-precision and smoothly changing rotor time constant even in unstable operating conditions where divergence risks are avoided. Ultimately, the system balances stability and torque control accuracy across the entire operating range.

[0067] Specifically, when a given current angle θ ref When the current angle exceeds the upper and lower threshold angles θ1 and θ2 of the operating condition and is in the unstable region, the system needs to exit the adaptive identification calculation to avoid divergence. However, even after exiting the adaptive calculation, it still needs to output a rotor time constant T to the indirect vector control module. r The value is used to calculate the slip, and if a T is used in the unstable region... r The initial setting is used to replace the adaptive identification result, so T is used for slip calculation. r The value will exhibit a jump at the convergence boundary, leading to a slip jump and torque judder; if locked when exiting adaptive operating conditions... The estimated value is used for slip calculation in the unstable region, as the actual slip T varies under different current conditions. rThe value will change, and this approach will introduce T. r Errors reduce torque accuracy.

[0068] The control strategy adopted in this application for the unstable region employs a locked rotor resistance method, which can continue to track T after exiting the adaptive identification condition. r The actual value. Based on the rotor time constant T. r The definition here introduces the intermediate variable, the estimated rotor resistance value. In each calculation cycle under adaptive operating conditions, the rotor time constant estimation result for that cycle is used. Rotor inductance lookup table value L r Online computing The formula is as follows: After entering the unstable region (|θ) ref |≥λ2 or|θ ref |≤θ1), Stop calculating and updating. Since the rotor resistance value is mainly affected by rotor temperature, and rotor temperature changes relatively slowly, the update will be stopped after this point. The value will not deviate significantly from the actual value in the short term. However, after entering the unstable region, the rotor time constant T used for slip calculation will change. r The value is switched from the adaptive identification result to that based on rotor resistance. Rotor inductance lookup table value L r The calculation is performed as follows: Please refer to Figure 3 , Figure 3 This is a schematic diagram of the control strategy provided in an embodiment of this application.

[0069] Additionally, please refer to Figure 4 , Figure 4 This is a schematic diagram of an adaptive control system for the rotor time constant of an induction motor provided in an embodiment of this application, as shown below. Figure 4As shown, the system includes: an acquisition module for acquiring the current operating condition of the motor; a determination module for determining a current angle threshold based on the current operating condition, wherein the current angle threshold is used to define the current angle operating region in which the reactive power-based model reference adaptive algorithm can stably converge; a partitioning module for partitioning the operating state of the motor into a first state and a second state based on the given current angle of the motor and the current angle threshold; and an execution module for executing a corresponding rotor time constant control strategy according to the partitioned operating state to perform indirect vector control of the induction motor, wherein: in the first state, the reactive power-based model reference adaptive algorithm is enabled to identify and output a first rotor time constant online; in the second state, the reactive power-based model reference adaptive algorithm is disabled, and a second rotor time constant is generated based on the first rotor time constant locked in the first state.

[0070] Further functional descriptions of the above modules and units are the same as those in the corresponding embodiments described above, and will not be repeated here.

[0071] In this embodiment, the adaptive control system for the rotor time constant of the induction motor is presented in the form of a functional unit. Here, a unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that execute one or more software or fixed programs, and / or other devices that can provide the above functions.

[0072] Please see Figure 5 , Figure 5 This is a schematic diagram of the structure of a computer device provided in an embodiment of this application, such as... Figure 5 As shown, the computer device includes one or more processors 10, memory 20, and interfaces for connecting the components, including high-speed interfaces and low-speed interfaces. The components communicate with each other via different buses and can be mounted on a common motherboard or otherwise installed as needed. The processors can process instructions executed within the computer device, including instructions stored in or on memory to display graphical information of a GUI on external input / output devices (such as display devices coupled to the interfaces). In some alternative implementations, multiple processors and / or multiple buses can be used with multiple memories and multiple memory modules, if desired. Similarly, multiple computer devices can be connected, each providing some of the necessary operations (e.g., as a server array, a group of blade servers, or a multiprocessor system). Figure 5 Take a processor 10 as an example.

[0073] Processor 10 may be a central processing unit, a network processor, or a combination thereof. Processor 10 may further include a hardware chip. The hardware chip may be an application-specific integrated circuit (ASIC), a programmable logic device (PLD), or a combination thereof. The programmable logic device may be a complex programmable logic device (CAMP), a field-programmable gate array (FPGA), a general-purpose array logic (GDA), or any combination thereof.

[0074] The memory 20 stores instructions executable by at least one processor 10 to cause the at least one processor 10 to perform the method shown in the above embodiments.

[0075] The memory 20 may include a program storage area and a data storage area. The program storage area may store the operating system and applications required for at least one function; the data storage area may store data created based on the use of the computer device. Furthermore, the memory 20 may include high-speed random access memory and may also include non-transitory memory, such as at least one disk storage device, flash memory device, or other non-transitory solid-state storage device. In some alternative embodiments, the memory 20 may optionally include memory remotely located relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of such networks include, but are not limited to, the Internet, intranets, local area networks, mobile communication networks, and combinations thereof.

[0076] The memory 20 may include volatile memory, such as random access memory; the memory may also include non-volatile memory, such as flash memory, hard disk or solid-state drive; the memory 20 may also include a combination of the above types of memory.

[0077] The computer device also includes a communication interface 30 for communicating with other devices or communication networks.

[0078] This application also provides a computer-readable storage medium. The methods described in this application can be implemented in hardware or firmware, or implemented as recordable on a storage medium, or implemented as computer code downloaded over a network and originally stored on a remote storage medium or a non-transitory machine-readable storage medium and subsequently stored on a local storage medium. Thus, the methods described herein can be processed by software stored on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. The storage medium can be a magnetic disk, optical disk, read-only memory, random access memory, flash memory, hard disk, or solid-state drive, etc.; further, the storage medium can also include combinations of the above types of memory. It is understood that computers, processors, microprocessor controllers, or programmable hardware include storage components capable of storing or receiving software or computer code. When the software or computer code is accessed and executed by the computer, processor, or hardware, the methods shown in the above embodiments are implemented.

[0079] This application provides a computer program product including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method of any embodiment of this application.

[0080] The systems and modules described in the above embodiments can be implemented by computer chips or physical entities, or by products with certain functions. A typical implementation device is a computer. Specifically, a computer can be, for example, a personal computer, laptop computer, cellular phone, camera phone, smartphone, personal digital assistant, media player, navigation device, email device, game console, tablet computer, wearable device, or any combination of these devices.

[0081] For ease of description, the above devices are described separately by function as various units. Of course, in implementing this application, the functions of each unit can be implemented in one or more software and / or hardware.

[0082] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0083] This application is described with reference to flowchart illustrations and / or block diagrams of methods, systems, and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations 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, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0084] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0085] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0086] It should also be noted that the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0087] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0088] The above description is merely an embodiment of this application and is not intended to limit the scope of this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the scope of the claims of this application.

[0089] Although embodiments of this application have been described in conjunction with the accompanying drawings, those skilled in the art can make various modifications and variations without departing from the spirit and scope of this application, and such modifications and variations all fall within the scope defined by the appended claims.

Claims

1. A method for adaptive control of time constant of an induction motor rotor, characterized in that, The method comprises: acquiring a current operating condition of the motor; determining a current angle threshold value according to the current operating condition, the current angle threshold value being used to define a current angle operating region in which a reactive power-based model reference adaptive algorithm is able to stably converge; dividing the operating state of the motor into a first state and a second state based on a given current angle of the motor and the current angle threshold value; performing a corresponding rotor time constant control strategy according to the divided operating state to conduct indirect vector control of the induction motor, wherein: in the first state, the reactive power-based model reference adaptive algorithm is enabled to identify and output a first rotor time constant online; and in the second state, the reactive power-based model reference adaptive algorithm is disabled, and a second rotor time constant is generated based on the first rotor time constant locked in the first state.

2. The method of claim 1, wherein, The current angle threshold value comprises a lower threshold angle and a critical current angle, and dividing the operating state of the motor into the first state and the second state based on the given current angle of the motor and the current angle threshold value comprises: if the given current angle is greater than the lower threshold angle and less than the critical current angle, the operating state of the motor is divided into the first state; if the given current angle is less than the lower threshold angle or the given current angle is greater than the critical current angle, the operating state of the motor is divided into the second state.

3. The method of claim 2, wherein, The method further comprises: determining a critical current angle corresponding to the operating condition according to an operating condition-current angle mapping table, wherein the operating condition-current angle mapping table is constructed in the following manner: acquiring a plurality of preset operating condition points, the preset operating condition points comprising motor speed and stator current amplitude; for any preset operating condition point, a plurality of candidate current angles are generated in a preset current angle range at a preset step size; based on the motor speed and the stator current amplitude of the preset operating condition point, a motor reactive power value corresponding to each candidate current angle is calculated; the minimum value among the motor reactive power values is extracted, and the candidate current angle corresponding to the minimum value is determined as the critical current angle of the preset operating condition point; based on each preset operating condition point and the corresponding critical current angle, the operating condition-current angle mapping table is constructed.

4. The method of claim 3, wherein, The method further comprises: determining the preset current angle range according to the lower threshold angle and an upper threshold angle, wherein the value range of the lower threshold angle is 20-30 degrees, and the preset step size is set to 0.1 degrees.

5. The method of claim 1, wherein, Enabling the reactive power-based model reference adaptive algorithm to identify and output the first rotor time constant online comprises: determining a power deviation based on the difference between the actual reactive power of the motor and the expected reactive power; adjusting the estimated value of the first rotor time constant based on the power deviation.

6. The method of claim 5, wherein, Adjusting the estimated value of the first rotor time constant based on the power deviation comprises: if the power deviation is greater than zero, decreasing the estimated value of the first rotor time constant; if the power deviation is less than zero, increasing the estimated value of the first rotor time constant.

7. The method of claim 1, wherein, Generating the second rotor time constant based on the first rotor time constant locked in the first state comprises: determine a corresponding rotor resistance estimation value based on the locked first rotor time constant in the first state; generate the second rotor time constant based on the rotor resistance estimation value and a rotor inductance corresponding to the current operating condition.

8. An induction motor rotor time constant adaptive control system characterized by, The system comprises: an acquisition module configured to acquire a current operating condition of the motor; a determination module configured to determine a current angle threshold based on the current operating condition, the current angle threshold being used to define a current angle operating region in which a reactive power based model reference adaptive algorithm is able to stably converge; a division module configured to divide an operating state of the motor into a first state and a second state based on a given current angle of the motor and the current angle threshold; an execution module configured to execute a corresponding rotor time constant control strategy based on the divided operating state to perform indirect vector control of the induction motor, wherein: in the first state, the reactive power based model reference adaptive algorithm is enabled to identify and output a first rotor time constant online; and in the second state, the reactive power based model reference adaptive algorithm is disabled, and a second rotor time constant is generated based on a first rotor time constant locked in the first state.

9. A computer device, comprising: comprise: a memory and a processor in communication connection with each other, the memory storing computer instructions, and the processor executing the computer instructions to perform the induction motor rotor time constant adaptive control method of any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for causing a computer to perform the induction motor rotor time constant adaptive control method of any one of claims 1 to 7.

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