Dynamic speed control system based on permanent magnet synchronous motor speed feedback

Abstract

This invention discloses a dynamic speed control system based on the speed feedback of a permanent magnet synchronous motor, relating to the field of motor speed control technology. It includes: a data acquisition module for acquiring three-phase stator current data, raw physical speed feedback data, and stator voltage command data of the motor, and inputting the stator voltage command data into a preset motor mathematical model to obtain model-estimated speed data; and a real-time deviation calculation module for calculating the real-time deviation divergence between the raw physical speed feedback data and the model-estimated speed data, obtaining residual fluctuation based on the three-phase stator current data, and mapping the real-time deviation divergence and residual fluctuation to obtain a dynamic feedback reliability factor. Its beneficial effects include reducing the fluctuation of the speed loop output torque current, extending the mechanical life of the motor, and improving the overall energy efficiency stability of the system.

Description

Technical Field

[0001] This invention relates to the field of motor speed control technology, and in particular to a dynamic speed control system based on speed feedback of a permanent magnet synchronous motor. Background Technology

[0002] Permanent magnet synchronous motors, with their high power density, high efficiency and excellent speed regulation performance, have been widely used in high-performance speed regulation fields such as CNC machine tools, industrial robots and new energy vehicle drives. In traditional dynamic speed regulation control systems, sensors are usually used to obtain the original physical speed as the feedback signal of the speed loop. In order to improve the robustness of the system under the condition of sensor interference or failure, existing technologies often introduce state observers or motor mathematical models to generate estimated speeds and attempt to fuse physical feedback with model estimates to achieve smoother closed-loop speed control.

[0003] However, existing speed control systems typically allocate weights based solely on static deviation indices when fusing physical feedback data and model-estimated data, neglecting the dynamic evolution of the feedback signal when encountering sudden load changes or instantaneous pulse interference. Because current technology lacks a closed-loop feedback mechanism for real-time rate-of-change monitoring of the fused composite speed feedback signal, the system cannot identify and eliminate abnormal disturbances caused by external random environments, making it difficult to dynamically correct key parameters in the weight generation logic. This results in the system continuing to use the weight allocation parameters under normal operating conditions even when experiencing severe oscillations, leading to severe overshoot or spurious fluctuations in the generated speed feedback signal. This, in turn, causes instability in the speed regulator output, ultimately resulting in a significant decrease in the dynamic speed regulation accuracy of the motor. Summary of the Invention

[0004] In view of the above-mentioned prior art, this application is made. Embodiments of this application provide a dynamic speed control system based on the speed feedback of a permanent magnet synchronous motor, which reduces the fluctuation of the output torque current of the speed loop, extends the mechanical life of the permanent magnet synchronous motor, and improves the overall energy efficiency and stability of the speed control system.

[0005] According to one aspect of this application, a dynamic speed control system based on permanent magnet synchronous motor speed feedback is provided, comprising:

[0006] Data acquisition module: used to acquire the three-phase stator current data, raw physical speed feedback data and stator voltage command data of the motor, and input the stator voltage command data into the preset motor mathematical model to obtain the model estimated speed data;

[0007] Real-time deviation calculation module: used to calculate the real-time deviation divergence between the original physical speed feedback data and the model estimated speed data, obtain the residual fluctuation based on the three-phase stator current data, and correlate and map the real-time deviation divergence and the residual fluctuation to obtain the dynamic feedback reliability factor;

[0008] Weighted fusion module: used to perform weighted fusion of the original physical speed feedback data and the model estimated speed data according to the weight allocation ratio generated by the dynamic feedback credibility factor, and generate a composite feedback speed signal;

[0009] Speed ​​regulation module: used to input the composite feedback speed signal as a speed loop feedback quantity into the speed regulator, generate torque command current, and combine it with the three-phase stator current data to generate pulse width modulation command;

[0010] Change rate judgment module: used to perform time series sampling on the composite feedback speed signal, calculate the change rate of the composite feedback speed signal based on the sampled values ​​at the current time and the historical time, and determine whether the change rate exceeds a preset threshold;

[0011] If the judgment result is yes, then the rate of change exceeding the preset threshold is fed back as an abnormal disturbance to the generation logic of the dynamic feedback credibility factor for parameter correction.

[0012] If the judgment result is negative, then the generation parameters of the dynamic feedback credibility factor remain unchanged.

[0013] According to another aspect of this application, an electronic device is provided, including a memory and a processor, the memory being used to store computer-executable instructions, and the processor being used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the method described above.

[0014] According to another aspect of this application, a computer storage medium is provided that stores computer-executable instructions thereon, which, when executed by a processor, implement the steps of the method described above.

[0015] Compared with existing technologies, the dynamic speed control system based on permanent magnet synchronous motor speed feedback according to the embodiments of this application uses a weighted fusion method that dynamically generates a weight allocation ratio based on a reliability factor. Compared with fixed weights or simple mean fusion, this invention can dynamically favor more reliable feedback sources based on real-time operating quality, significantly improving the convergence speed of the composite feedback speed signal in transient processes. The invention also introduces the monitoring of the "rate of change of the composite feedback speed signal" and feeds it back as an abnormal disturbance to the reliability factor generation logic for parameter correction, ensuring that the evaluation logic will not fail when the system encounters extreme shocks. This greatly enhances the system's dynamic anti-disturbance performance and filters out false abrupt changes in the feedback signal. Because the feedback quantity input to the speed regulator is smooth and accurate, it directly reduces the fluctuation of the speed loop output torque current, extends the mechanical life of the motor, and improves the overall energy efficiency stability of the system. Attached Figure Description

[0016] The above and other objects, features, and advantages of this application will become more apparent from the more detailed description of the embodiments of this application in conjunction with the accompanying drawings. The drawings are provided to further illustrate the embodiments of this application and form part of the specification. They are used together with the embodiments of this application to explain this application and do not constitute a limitation thereof. In the drawings, the same reference numerals generally represent the same components or steps.

[0017] Figure 1 This is a schematic diagram of the overall framework of the dynamic speed control system based on the speed feedback of a permanent magnet synchronous motor according to the present invention.

[0018] Figure 2 This is a schematic diagram of the target oscillation characteristic component judgment logic of the dynamic speed regulation control system based on permanent magnet synchronous motor speed feedback of the present invention.

[0019] Figure 3 This is a schematic diagram illustrating the generation of comprehensive evaluation indicators for the dynamic speed control system based on permanent magnet synchronous motor speed feedback according to the present invention. Detailed Implementation

[0020] Hereinafter, exemplary embodiments according to this application will be described in detail with reference to the accompanying drawings. Obviously, the described embodiments are merely some embodiments of this application, and not all embodiments of this application. It should be understood that this application is not limited to the exemplary embodiments described herein.

[0021] Application Overview

[0022] In traditional permanent magnet synchronous motor dynamic speed control systems, speed feedback signals are primarily acquired through single feedback from physical sensors or static fusion with model estimates. This approach exhibits significant limitations under complex operating conditions. Due to electromagnetic interference and sudden load changes in the motor's operating environment, the speed data fed back by physical sensors often contains random noise, while the drift of motor model parameters with temperature rise leads to steady-state deviations in the model's estimated speed. For example, in high-performance industrial drive scenarios, when the motor encounters external impact loads, traditional weighted fusion strategies, with fixed weight coefficients or allocation based solely on simple static deviations, cannot dynamically identify fluctuations in the reliability of the feedback source, resulting in feedback signals that fail to accurately represent the true operating state. When the composite feedback signal experiences abnormal jumps due to disturbances, the speed regulator, lacking a closed-loop correction mechanism for the rate of change of the feedback signal, generates erroneous torque and current commands, causing severe system oscillations. If these problems are not addressed, false speed feedback will lead to instability in the speed closed-loop control, significantly reducing the motor's dynamic speed control accuracy, accelerating motor winding aging due to current overshoot, and even causing hardware failures in the drive system, threatening the continuity of industrial operations.

[0023] Faced with the aforementioned problems, this application first recognizes that traditional systems cannot effectively combine the physical characteristics of stator current with the statistical characteristics of speed deviation for multi-dimensional reliability assessment, leading to inaccurate feedback fusion ratios. To address this, this application attempts to establish a correlation mapping framework between the residual fluctuation of three-phase stator current and the real-time deviation divergence. By calculating the dynamic feedback reliability factor, it achieves refined weighted fusion of physical feedback and model estimation data. Furthermore, this application finds that a single static weight allocation cannot cope with extreme disturbance scenarios, necessitating the introduction of a monitoring mechanism based on the rate of change of the composite feedback speed signal, defining dynamic changes exceeding a threshold as abnormal disturbances. By comparing the characteristic differences between normal fluctuations and abnormal disturbances, this application ultimately chooses to inject the abnormal disturbance into the reliability factor generation logic for parameter correction, constructing a closed-loop feedback evaluation system with self-correcting capabilities. This method can offset the interference of non-stationary operating conditions on reliability assessment in real time, significantly improving the robustness of the composite feedback speed signal, thereby ensuring that the speed regulator can still output stable and accurate control commands under high dynamic loads, achieving high-performance and stable operation of the motor speed control system.

[0024] Example 1:

[0025] Reference Figures 1-3 As an embodiment of the present invention, a dynamic speed control system based on the speed feedback of a permanent magnet synchronous motor is provided, including: a data acquisition module, a real-time deviation calculation module, a weighted fusion module, a speed adjustment module, and a rate of change judgment module.

[0026] Figure 1The figure illustrates a dynamic speed control system based on permanent magnet synchronous motor speed feedback according to an embodiment of this application, specifically including:

[0027] Data acquisition module: used to acquire the three-phase stator current data, raw physical speed feedback data and stator voltage command data of the motor, and input the stator voltage command data into the preset motor mathematical model to obtain the model estimated speed data.

[0028] In this embodiment, the system utilizes current transformers arranged at the stator winding terminals of the permanent magnet synchronous motor to capture three-phase stator current data in real time. Simultaneously, the original physical speed feedback data is obtained through a rotary encoder installed at the end of the rotor. Simultaneously, the stator voltage command data at the current moment is extracted from the output of the system's current loop controller, including the d-axis stator voltage command. and q-axis stator voltage command After acquiring the above multidimensional data, the system will output the stator voltage command data ( , The input is fed into a preset motor mathematical model, which is constructed based on the coupling logic of electromagnetic conversion and mechanical motion. The model estimates the rotational speed data through the following deterministic physical formula. Solving for;

[0029] The system will capture three-phase stator current data ( The data is transformed into measured stator current data in a rotating coordinate system through a preset rotating coordinate transformation logic, i.e., the d-axis stator current. and q-axis stator current Based on the voltage equation, using the input voltage command and the current stator current feedback value, the rate of change of current over time is calculated. The specific formula is as follows:

[0030] ;

[0031] ;

[0032] in, and These are the rates of change of the stator current along the d and q axes, respectively. These are stator resistance parameters. For flux linkage parameters, The electric angular velocity of the motor is obtained from the estimated rotational speed at the previous sampling time using the formula... The calculation yields p, where p is the number of pole pairs of the motor.

[0033] Based on the current stator current data, calculate the theoretical electromagnetic torque generated by the motor in the magnetic field. The specific formula is as follows:

[0034] ;

[0035] The calculated electromagnetic torque Substitute the mechanical dynamics equations and solve the model to estimate the rotational speed data. The specific formula is as follows:

[0036] ;

[0037] in, This represents the moment of inertia of the rotor. For mechanical angular acceleration, The system's preset load torque can be used to obtain the model-estimated rotational speed data at the current moment by performing numerical integration of the above differential equation in the time dimension. (rad / s), B is the coefficient of viscous friction ( This process constructs the complete physical logic from voltage commands to mechanical motion, and generates... Depends only on the model's internal parameters and This provides a reference free of observation noise for subsequent deviation divergence calculations.

[0038] Real-time deviation calculation module: used to calculate the real-time deviation divergence between the original physical speed feedback data and the model estimated speed data. Based on the three-phase stator current data, the residual fluctuation is obtained. The real-time deviation divergence and the residual fluctuation are correlated and mapped to obtain the dynamic feedback reliability factor.

[0039] In this embodiment of the application, the original physical rotational speed feedback data is first calculated. Compared with model-estimated speed data The instantaneous deviation is determined, and a sliding window is introduced to extract the statistical characteristics of this instantaneous deviation, namely the real-time deviation divergence. The specific formula is as follows:

[0040] ;

[0041] in, Let $\frac{i}{i}$ be the instantaneous rotational speed deviation term at the $i$-th sampling time, and its calculation formula is: ,in This is the original physical rotational speed feedback data at time i. Estimate the rotational speed data for the model at time i. This is the arithmetic mean of all instantaneous speed deviation terms within the current sliding window, calculated using the following formula: , where N is the total number of samples sampled in the preset sliding window;

[0042] The system synchronously calculates the residual fluctuation, reflecting the degree of electromagnetic state deviation, based on the Euclidean distance between the measured quantum current and the model predicted current. The specific calculation formula is as follows:

[0043] ;

[0044] in, Predict the current term for the d-axis model. Predict the current term for the q-axis model;

[0045] The system uses a preset normalized mapping function to correlate the speed domain feature terms with the current domain feature terms, and calculates the dynamic feedback reliability factor. The specific formula is as follows:

[0046] ;

[0047] in, The normalized speed deviation divergence term is given by, where, The preset speed deviation reference constant, This is the normalized current residual fluctuation term. This is a preset current residual reference constant;

[0048] By normalizing and correlating the speed divergence with current residuals of different dimensions, an evaluation index (i.e., dynamic feedback reliability factor) capable of real-time sensing of system operating quality is constructed. When excessive sensor noise or model inaccuracy leads to an increase in the normalized component in the denominator, the dynamic feedback reliability factor... The value is reduced, thereby achieving joint constraints on feedback reliability at both the physical and statistical levels.

[0049] Weighted fusion module: This module is used to weight and fuse the original physical speed feedback data and the model-estimated speed data according to the weight allocation ratio generated by the dynamic feedback confidence factor, generating a composite feedback speed signal. The aim is to deeply integrate physical feedback data with different error characteristics and model-estimated data by dynamically adjusting the weight allocation ratio. The specific implementation is as follows:

[0050] In this embodiment, based on dynamic feedback credibility factor Generate feedback data for the original physical rotation speed respectively. First weight allocation ratio and the speed data estimated by the model Second weight allocation ratio The specific calculation formula is as follows:

[0051] ;

[0052] ;

[0053] It achieves a direct mapping of credibility, when the credibility factor is dynamically fed back. When the value approaches 1, it indicates high quality of the physical sensor signal, and the system increases the weight of physical feedback; when the dynamic feedback reliability factor... When the value approaches 0, it indicates severe environmental disturbance or sensor malfunction, and the system automatically switches to using the estimated value from the motor mathematical model.

[0054] The calculated weighting ratios are used to linearly weight and sum the two speed signals to obtain the final composite feedback speed signal used for speed closed-loop control. The specific formula is as follows:

[0055] ;

[0056] in, Contributions to physical feedback Estimate contribution terms for the model.

[0057] Speed ​​regulation module: Used to input the composite feedback speed signal as the speed loop feedback quantity into the speed regulator to generate torque command current, and combine it with the three-phase stator current data to generate pulse width modulation command.

[0058] The system will use composite feedback speed signals As the sole feedback quantity of the speed loop, it is related to the preset speed command signal. Perform the difference operation to obtain the speed deviation. , will speed deviation The torque command current is calculated by inputting it into a preset speed regulator (a proportional-integral regulator is used in this embodiment). The specific formula is as follows:

[0059] ;

[0060] in, This is the proportional gain coefficient of the speed regulator. The integral gain coefficient of the speed regulator. This is the cumulative integral term of the rotational speed deviation over the time dimension;

[0061] Obtaining torque command current Then, the system combines the acquired three-phase stator current data ( To perform current loop regulation, firstly, the d-axis and q-axis voltage commands are calculated using the current regulator. Subsequently, the system uses a space vector pulse width modulation algorithm to convert the voltage command into a final pulse width modulation command. The specific logic is as follows: based on the measured current obtained from the transformation of the three-phase stator current... With command current (in The current deviation is usually preset to 0, and then transformed to obtain the three-phase command voltage. The final generated pulse width modulation command Define the switching duty cycle of the inverter power devices ( The specific formula is as follows:

[0062] ;

[0063] in, For the j-phase stator command voltage term, The inverter DC bus voltage constant is... As the voltage ratio, the system completes the closed-loop link from the fused speed feedback to the physical drive execution, ensuring that the high-precision characteristics of the composite feedback speed signal can be directly converted into real-time correction of the stator current waveform, thereby realizing the dynamic response of speed control.

[0064] Rate of change judgment module: It is used to perform time series sampling of composite feedback speed signal, calculate the rate of change of composite feedback speed signal based on the sampled values ​​at the current time and the historical time, and determine whether the rate of change exceeds the preset threshold. It aims to identify and capture abnormal disturbances caused by external random environment.

[0065] The system uses a preset sampling period For composite feedback speed signal Continuous sampling is performed to construct a time series dataset. In this embodiment, the system retains at least the sampled value at the current time k. and the adjacent previous historical moment Sample values Based on the numerical differences between adjacent sampling times, the rate of change of the composite feedback speed signal is calculated using a differential algorithm. The specific formula is as follows:

[0066] .

[0067] If the judgment result is yes, the rate of change exceeding the preset threshold will be fed back as an abnormal disturbance to the generation logic of the dynamic feedback credibility factor for parameter correction.

[0068] Specifically, parameter adjustments include:

[0069] Based on the amplitude of abnormal disturbance The absolute value of is used to calculate the dynamic attenuation operator used to adjust the sensitivity of the generated logic. The specific formula is as follows:

[0070] ;

[0071] in, It is the absolute value of the amplitude of the abnormal disturbance. is the preset attenuation gain constant, and exp is an exponential function with the natural logarithm as the base;

[0072] Using dynamic decay operator Gain reconstruction is performed on the real-time bias divergence to obtain the corrected divergence discrimination criterion. The specific formula is as follows:

[0073] ;

[0074] Since the dynamic decay operator Γat decreases as the absolute value of the amplitude of the anomalous disturbance increases, the reconstructed divergence criterion... The original divergence value is effectively amplified, thus exerting a stronger penalty on the bias in subsequent confidence calculations.

[0075] The dynamic feedback reliability factor is limited by a divergence discrimination criterion, and the abnormal disturbance is simultaneously mapped to a deviation cancellation gain with opposite polarity to the three-phase stator current data. The generation parameters of the dynamic feedback reliability factor are corrected by superimposing the bias to offset the gain, as shown in the following formula:

[0076] ;

[0077] in, The sign function term is the average value of the three-phase stator current, used to characterize the physical polarity of the current electromagnetic torque. For the preset disturbance-current mapping coefficients, the system cancels the gain by superimposing the deviation. The generation parameters of the dynamic feedback credibility factor are modified; specifically, the parameters generated are adjusted. Compensation to residual fluctuation In this process, the abnormal fluctuations in current residual caused by abnormal disturbances are offset by the gain characteristics with opposite polarities, thereby achieving closed-loop correction of the dynamic feedback credibility factor generation logic.

[0078] If the judgment result is negative, the generation parameters of the current dynamic feedback confidence factor remain unchanged, that is, the dynamic decay operator is not triggered. Calculation and gain superposition process.

[0079] In the process of conceiving this invention, it was considered that the speed signal of a permanent magnet synchronous motor often contains high-frequency pulse interference or transient step noise under complex electromagnetic environments or sudden load conditions. Traditional dynamic feedback reliability factor generation logic mainly relies on the amplitude characteristics of deviation divergence and current residual. However, in the initial stage of interference, the accumulation of these amplitude characteristics requires a certain time window, resulting in a lag in reliability adjustment. Based on this, this invention monitors the rate of change of the composite feedback speed signal (i.e., the first derivative characteristic of the signal) and uses abnormal jumps in the signal slope to predict the trend of signal quality deterioration. The logic of this operation is that the actual mechanical inertia of the motor will limit… The instantaneous rate of change of rotational speed is calculated, and once the calculated rate of change exceeds the physical limit or a preset threshold, it can be determined that there is a non-physical abnormal disturbance in the signal. By feeding back this abnormal disturbance to the generation logic in real time, the dynamic feedback reliability factor can be adjusted forward at the moment the disturbance occurs, thereby completing the smooth switching of the feedback source before the noise fully enters the speed loop regulator. Compared with traditional low-pass filtering technology, this operation eliminates the impact of phase lag on system bandwidth. Compared with fixed threshold removal technology, it ensures the continuity and stability of control commands through parameterized gain reconstruction, significantly improving the anti-interference performance and robustness of the system under extreme conditions.

[0080] For example, let's take a set of continuously sampled data sequences as an example; assume the system has a preset sampling period. Preset rate of change threshold Preset attenuation gain constant ,exist At any given moment, the system acquires the composite feedback speed signal. ;to At time k, the motor is subjected to an external electromagnetic pulse, and the data is sampled. At this point, the rate of change judgment module calculates the rate of change. If the absolute value of the rate of change |8000| > 5000, and the judgment result is "yes", then the abnormal disturbance is determined. Subsequently, the system enters the parameter correction procedure to calculate the absolute value of the amplitude of the abnormal disturbance. Based on this, the dynamic decay operator is calculated. Furthermore, the system utilizes this dynamic decay operator to analyze the real-time deviation divergence at the current moment. (Assuming the initial value is) Gain reconstruction is performed to obtain the corrected divergence criterion. Due to the divergence criterion Increasing the dynamic feedback reliability factor The denominator of the generated result increases significantly, leading to a decrease in the reliability factor of the dynamic feedback. The reliability factor quickly dropped from 0.95 (high confidence) to 0.42 (low confidence). At this point, the weighted fusion module automatically reduced the weight of the physical rotation speed feedback based on the adjusted dynamic feedback reliability factor, thus avoiding the problem. Abnormal fluctuations impact the speed regulator, ensuring the smooth operation of the speed control system; conversely, if... The sampled value at time is The calculated rate of change for It did not exceed the threshold. If the result is "no", the system will maintain dynamic feedback of the credibility factor. The generation parameters remain unchanged to ensure that the normal acceleration process is not interfered with.

[0081] This application further proposes that the system also includes the following corrective steps:

[0082] Determine whether the dynamic feedback credibility factor is in the preset high range;

[0083] If the judgment result is yes, then the stator resistance parameters and flux linkage parameters inside the motor mathematical model are corrected online based on the real-time deviation divergence, dynamic feedback reliability factor and composite feedback speed signal, so as to eliminate the model deviation caused by temperature rise or magnetic saturation.

[0084] If the judgment result is negative, then skip the online correction step of the internal parameters of the motor mathematical model.

[0085] The system first determines the reliability factor of the generated dynamic feedback. Whether it is within a preset high-level range, in this embodiment, the high-level threshold is set to... If the judgment conditions are met If the result is "yes", the online correction process for stator resistance and flux linkage parameters is triggered. Parameter identification is only performed when the speed feedback signal is highly reliable and the system is running smoothly, to avoid noise contaminating the model parameters. If the result is "no", the correction step is skipped.

[0086] Specifically, the online correction of stator resistance and flux linkage parameters includes:

[0087] Based on the mapping correlation results between real-time deviation divergence and dynamic feedback reliability factor, the comprehensive correction gain for stator resistance parameters and flux linkage parameters is determined. The specific formula is as follows:

[0088] ;

[0089] in, These are preset baseline correction coefficients used to adjust the parameter convergence speed;

[0090] The real-time operating frequency of the motor is calculated based on the composite feedback speed signal, using the following formula:

[0091] ;

[0092] And based on the real-time operating frequency, the stator resistance parameters and flux linkage parameters are dynamically decoupled and updated in the comprehensive correction gain, including:

[0093] Extract the real-time amplitude change rate of the three-phase stator current data, and determine the current disturbance intensity index based on the real-time amplitude change rate, specifically including:

[0094] The system uses coordinate transformation or vector synthesis logic to calculate the instantaneous composite amplitude of the three-phase stator current. The calculation formula is as follows:

[0095] ;

[0096] in, The magnitude of the stator current vector represents the current electromagnetic load level of the motor;

[0097] The system is based on a preset sampling period. Using the amplitude of m at the current time Compared to the previous moment amplitude Calculate the real-time amplitude change rate The specific formula is as follows:

[0098] ;

[0099] By real-time amplitude change rate Mapping to a dimensionless region to determine the current disturbance intensity index The specific formula is as follows:

[0100] ;

[0101] in, This is a preset current change rate reference constant term;

[0102] Based on the real-time operating frequency, a first weighted mapping function for the stator resistance parameters with respect to the comprehensive correction gain, and a second weighted mapping function for the flux linkage parameters with respect to the comprehensive correction gain are determined; the current disturbance intensity index is then used to map the first weighted function. Mapping function with second weight The output value is cross-corrected, and the specific formula is as follows:

[0103] ;

[0104] ;

[0105] in, The preset corner frequency constant is then used, and the current disturbance intensity index is then applied. The above output values ​​are cross-corrected to obtain the final stator resistance update weights. Update weights with magnet link The specific formula is as follows:

[0106] ;

[0107] ;

[0108] When the motor is operating at high frequency, increase the update weight of the flux linkage parameters. It also constrains the correction step size of the stator resistance parameter, which conforms to the physical characteristics of permanent magnet synchronous motors where the back EMF dominates and the resistance voltage drop is negligible at high frequencies.

[0109] Combining the amplitude characteristics of three-phase stator current data Dynamically adjust stator resistance parameters update slope The specific formula is as follows:

[0110] ;

[0111] in, Using a preset rated current reference, this mapping increases the update slope of the stator resistance parameters when the current amplitude is large (severe heat generation), thereby tracking the resistance change trend with temperature rise in real time. Through the decoupling and cross-correction of the aforementioned multi-dimensional weights, the system achieves high-precision closed-loop calibration of the internal parameters of the motor mathematical model, ensuring the accuracy of the model's estimated speed data. It maintains extremely high static accuracy across the entire frequency range.

[0112] Figure 3 This is a schematic diagram illustrating the generation of comprehensive evaluation indicators for the dynamic speed control system based on permanent magnet synchronous motor speed feedback according to the present invention.

[0113] This application further proposes that the system also includes:

[0114] To obtain comprehensive environmental stress characterization parameters that synergize with the dynamic feedback reliability factor, this system further introduces an environmental monitoring dimension. Through a comprehensive assessment of environmental stress, it achieves dynamic correction of the feedback logic evaluation criteria and generates a health index reflecting the system's operational quality. The specific formula is as follows:

[0115] ;

[0116] in, These are parameters that comprehensively characterize environmental stress. The motor ambient temperature value is obtained in real time. This is the preset ambient temperature reference value. To obtain the vibration intensity value of the motor housing in real time, For the preset vibration intensity benchmark value, The preset weighting coefficients;

[0117] While generating the composite feedback speed signal, the fluctuation of the composite feedback speed signal is correlated and mapped with the comprehensive environmental stress characterization parameters to obtain the stress influence feature vector. The specific formula is as follows:

[0118] ;

[0119] in, This is the stress influence eigenvector. The standard deviation of the composite feedback speed signal within the current sampling period. The term represents the rate of change of environmental stress over time. This vector quantifies the degree of influence of the environment on stress from two dimensions: static strength and dynamic trend.

[0120] Based on the deviation of the stress influence feature vector from the preset steady-state standard, the current steady-state level of the system is determined. According to the steady-state level, the preset high-level interval corresponding to the dynamic feedback reliability factor and the preset threshold corresponding to the rate of change are dynamically adjusted. The system then calculates the stress influence feature vector. With the preset steady-state standard vector The Euclidean distance is used as the deviation degree D, and the current steady-state level L of the system is determined based on the range of values ​​for the deviation degree D. Subsequently, the system dynamically adjusts the preset high-level interval threshold corresponding to the dynamic feedback reliability factor based on the steady-state level L. Preset threshold corresponding to the rate of change The specific formula is as follows:

[0121] ;

[0122] ;

[0123] in, The high-order interval threshold for the steady-state level L. , The preset threshold for the steady-state level L. , and These are the basic high threshold and the basic rate of change threshold, respectively. and For the correction function related to the steady-state level L, To implement the correction function for the steady-state level L, To implement the correction function for the steady-state level L, the system automatically shrinks the high-level threshold when environmental stress surges (the steady-state level decreases). And relax the preset threshold To adapt to more demanding operating environments and avoid accidentally triggering correction logic;

[0124] By coupling the dynamic feedback reliability factor with the steady-state operational level, a comprehensive evaluation index for system health is generated. The specific formula is as follows:

[0125] ;

[0126] in, The system health comprehensive evaluation index is the preset highest steady-state level constant. The reliability of feedback signals and the stability of the external environment were comprehensively evaluated, and the overall health evaluation index of the system was used. When the level remains low, the system issues a maintenance warning.

[0127] Figure 2 This is a schematic diagram of the target oscillation characteristic component judgment logic of the dynamic speed control system based on permanent magnet synchronous motor speed feedback of the present invention.

[0128] This application further proposes that the system also includes:

[0129] Determine whether a target oscillation characteristic component exists under the current operating conditions. The target oscillation characteristic component is obtained by extracting the energy distribution characteristics of the composite feedback speed signal in different frequency bands and defining the components in the energy distribution characteristics that exceed a preset energy threshold.

[0130] Specifically, the system uses composite feedback speed signals Perform Discrete Fourier Transform or bandpass filtering to extract its values ​​in different frequency bands. Energy distribution characteristics The system will identify energy distribution characteristics that exceed a preset energy threshold. The component is defined as the target oscillation characteristic component. :

[0131] ,in, ;

[0132] in, For frequency The power spectral density term at that location; For the preset energy threshold item, if there exists a condition that meets the requirements... If the result is "yes", the subsequent self-damping constraint logic will be triggered.

[0133] If the judgment result is yes, then the difference between the torque command current at the current time and the previous sampling time is obtained to get the output rate of change of the torque command current. After determining that there is a target oscillation characteristic component, the system obtains the torque command current. At the current time k and the previous sampling time The difference is used to obtain the output rate of change of the torque command current. The specific formula is as follows:

[0134] ;

[0135] in, and These are the torque command current sample values ​​at the current time and the previous time, respectively. The preset control sampling period;

[0136] Then calculate the target oscillation characteristic components. The energy proportion in the composite feedback speed signal is determined, and the self-damping constraint coefficient is generated based on the energy proportion. The specific formula is as follows:

[0137] ;

[0138] ;

[0139] in, This is the energy percentage item. This represents the total energy of the composite feedback speed signal across the entire frequency band. The preset damping adjustment gain constant, This is the self-damping constraint coefficient, when the proportion of the oscillating component in the signal... When the value is higher, the self-damping constraint coefficient is higher. The smaller;

[0140] The output rate of change of torque command current is limited and corrected using a self-damping constraint coefficient, as shown in the following formula:

[0141] ;

[0142] in, To correct the rate of change of the output, the system reconstructs the torque command output value at the current moment based on the corrected rate of change. This operation reduces the rate of change of the torque command current output. This achieves physical suppression of oscillating energy.

[0143] If the judgment result is negative, the current torque command current output logic remains unchanged.

[0144] It should be noted that the limit adjustment also includes:

[0145] The system acquires the phase deviation characteristics between the composite feedback speed signal and the torque command current in real time, and performs a time-series correlation mapping between the phase deviation characteristics and the target oscillation characteristic components to determine the elastic load coefficient characterizing the mechanical flexibility of the system. Specifically, the system acquires the composite feedback speed signal in real time. With torque command current Phase deviation characteristics between Specifically, the system uses correlation analysis or phase-locked logic to extract the phase difference between two sets of signals on the same time axis. Subsequently, the system analyzes the phase deviation characteristics. With respect to the target oscillation characteristic components mentioned above Perform a correlation mapping on the time series and calculate the elastic load coefficient, which characterizes the mechanical flexibility of the system. The specific formula is as follows:

[0146] ;

[0147] in, The phase deviation reference constant, The reference constant for oscillation energy is the elastic load coefficient. This reflects the phase lag strength generated per unit disturbance energy, and the elastic load coefficient. The higher the value, the greater the phase shift generated by the system under the same energy oscillation, that is, the more significant the flexibility (elastic load characteristics) of the transmission system.

[0148] Determine whether the elastic load factor exceeds the preset stability boundary value;

[0149] If the judgment result is yes, then based on the center frequency of the target oscillation characteristic component, a compensation gain for the torque command current is dynamically generated, and the compensation gain is superimposed on the torque command current to suppress the amplitude of the target oscillation characteristic component.

[0150] ;

[0151] in, To compensate for the gain, As a reference for compensating current amplitude, This is a dimensionless modulation term;

[0152] If the judgment result is negative, the current compensation state of the torque command current remains unchanged.

[0153] Example 2:

[0154] In one embodiment of the present invention, which differs from the previous embodiment, the electronic device includes one or more processors and a memory.

[0155] A processor can be a central processing unit (CPU) or other form of processing unit with data processing and / or instruction execution capabilities, and can control other components in an electronic device to perform desired functions.

[0156] The memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Non-volatile memory may include, for example, read-only memory (ROM), hard disk, flash memory, etc.

[0157] In one example, the electronic device may also include input devices and output devices, which are interconnected via a bus system and / or other forms of connection mechanisms (not shown). In addition, depending on the specific application, the electronic device may include any other suitable components.

[0158] Example 3:

[0159] Embodiments of this application may also be computer-readable storage media storing computer program instructions thereon, which, when executed by a processor, cause the processor to perform the steps described in the "Exemplary Methods" section above according to the various embodiments of this application.

[0160] Computer-readable storage media may take the form of any combination of one or more readable media. A readable medium may be a readable signal medium or a readable storage medium. A readable storage medium may, for example, include, but is not limited to, electrical, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatuses, or devices, or any combination thereof. More specific examples of readable storage media (a non-exhaustive list) include: electrical connections having one or more wires, portable disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0161] The basic principles of this application have been described above with reference to specific embodiments. However, it should be noted that the advantages, benefits, and effects mentioned in this application are merely examples and not limitations, and should not be considered as essential features of each embodiment of this application. Furthermore, the specific details disclosed above are for illustrative and facilitative purposes only, and are not limitations. These details do not restrict the application from being implemented using the specific details described above.

[0162] The block diagrams of devices, apparatuses, devices, and systems involved in this application are merely illustrative examples and are not intended to require or imply that they must be connected, arranged, or configured in the manner shown in the block diagrams. As those skilled in the art will recognize, these devices, apparatuses, devices, and systems can be connected, arranged, and configured in any manner. Words such as “comprising,” “including,” “having,” etc., are open-ended terms meaning “including but not limited to,” and are used interchangeably with them. The terms “or” and “and” as used herein refer to the terms “and / or,” and are used interchangeably with them unless the context clearly indicates otherwise. The term “such as” as used herein refers to the phrase “such as but not limited to,” and is used interchangeably with it.

[0163] It should also be noted that in the apparatus, equipment, and methods of this application, the components or steps can be disassembled and / or recombined. These disassemblies and / or recombinations should be considered as equivalent solutions of this application.

[0164] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use this application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein can be applied to other aspects without departing from the scope of this application. Therefore, this application is not intended to be limited to the aspects shown herein, but rather to be accorded the widest scope consistent with the principles and novel features disclosed herein.

[0165] The above description has been given for purposes of illustration and description. Furthermore, this description is not intended to limit the embodiments of this application to the forms disclosed herein. Although numerous exemplary aspects and embodiments have been discussed above, those skilled in the art will recognize certain variations, modifications, alterations, additions, and sub-combinations thereof.

Claims

1. A dynamic speed control system based on speed feedback of a permanent magnet synchronous motor, characterized in that, include: Data acquisition module: used to acquire the three-phase stator current data, raw physical speed feedback data and stator voltage command data of the motor, and input the stator voltage command data into the preset motor mathematical model to obtain the model estimated speed data; Real-time deviation calculation module: used to calculate the real-time deviation divergence between the original physical speed feedback data and the model estimated speed data, obtain the residual fluctuation based on the three-phase stator current data, and correlate and map the real-time deviation divergence and the residual fluctuation to obtain the dynamic feedback reliability factor; Weighted fusion module: used to perform weighted fusion of the original physical speed feedback data and the model estimated speed data according to the weight allocation ratio generated by the dynamic feedback credibility factor, and generate a composite feedback speed signal; Speed ​​regulation module: used to input the composite feedback speed signal as a speed loop feedback quantity into the speed regulator, generate torque command current, and combine it with the three-phase stator current data to generate pulse width modulation command; Change rate judgment module: used to perform time series sampling on the composite feedback speed signal, calculate the change rate of the composite feedback speed signal based on the sampled values ​​at the current time and the historical time, and determine whether the change rate exceeds a preset threshold; If the judgment result is yes, then the rate of change exceeding the preset threshold is fed back as an abnormal disturbance to the generation logic of the dynamic feedback credibility factor for parameter correction. If the judgment result is negative, then the generation parameters of the dynamic feedback credibility factor remain unchanged.

2. The dynamic speed control system based on permanent magnet synchronous motor speed feedback according to claim 1, characterized in that: The system also includes the following correction steps: Determine whether the dynamic feedback reliability factor is in a preset high range; If the judgment result is yes, then the stator resistance parameters and flux linkage parameters inside the motor mathematical model are corrected online based on the real-time deviation divergence, dynamic feedback reliability factor and composite feedback speed signal. If the judgment result is negative, then skip the online correction step of the internal parameters of the motor mathematical model.

3. The dynamic speed control system based on permanent magnet synchronous motor speed feedback according to claim 2, characterized in that, The system also includes: Obtain the comprehensive environmental stress characterization parameters that work in conjunction with the dynamic feedback credibility factor; While generating the composite feedback speed signal, the fluctuation of the composite feedback speed signal is correlated and mapped with the comprehensive environmental stress characterization parameters to obtain the stress influence feature vector. Based on the degree of deviation between the stress influence feature vector and the preset steady-state standard, the current operating steady-state level of the system is determined; Based on the steady-state operating level, dynamically adjust the preset high-level range corresponding to the dynamic feedback reliability factor and the preset threshold corresponding to the rate of change; The dynamic feedback reliability factor is coupled with the steady-state operating level to generate a comprehensive evaluation index for system health.

4. The dynamic speed control system based on permanent magnet synchronous motor speed feedback according to claim 1, characterized in that, The system also includes: Determine whether a target oscillation characteristic component exists under the current operating condition. The target oscillation characteristic component is obtained by extracting the energy distribution characteristics of the composite feedback speed signal in different frequency bands and defining the components in the energy distribution characteristics that exceed a preset energy threshold. If the judgment result is yes, then the difference between the torque command current at the current time and the previous sampling time is obtained, the output change rate of the torque command current is obtained, the energy ratio of the target oscillation characteristic component in the composite feedback speed signal is calculated, and a self-damping constraint coefficient is generated according to the energy ratio. The self-damping constraint coefficient is used to limit and correct the output change rate of the torque command current. If the judgment result is negative, then the current output logic of the torque command current remains unchanged.

5. The dynamic speed control system based on permanent magnet synchronous motor speed feedback according to claim 4, characterized in that, The amplitude limiting correction also includes: The phase deviation characteristics between the composite feedback speed signal and the torque command current are acquired in real time, and the phase deviation characteristics are correlated and mapped with the target oscillation characteristic components in a time series to determine the elastic load coefficient characterizing the mechanical flexibility of the system. Determine whether the elastic load coefficient exceeds the preset stability boundary value; If the judgment result is yes, then based on the center frequency of the target oscillation characteristic component, a compensation gain for the torque command current is dynamically generated, and the compensation gain is superimposed on the torque command current to suppress the amplitude of the target oscillation characteristic component. If the judgment result is negative, the current compensation state of the torque command current remains unchanged.

6. The dynamic speed control system based on permanent magnet synchronous motor speed feedback according to claim 2, characterized in that, The online correction of the stator resistance parameters and flux linkage parameters includes: Based on the mapping correlation results between the real-time deviation divergence and the dynamic feedback reliability factor, the comprehensive correction gain for the stator resistance parameter and the flux linkage parameter is determined. The real-time operating frequency of the motor is calculated based on the composite feedback speed signal, and the update weights of the stator resistance parameter and the flux linkage parameter in the comprehensive correction gain are dynamically decoupled based on the real-time operating frequency. When the motor is operating at high frequency, the update weight of the flux linkage parameter is increased and the correction step size of the stator resistance parameter is constrained. Based on the amplitude characteristics of the three-phase stator current data, the update slope of the stator resistance parameter is dynamically adjusted.

7. The dynamic speed control system based on permanent magnet synchronous motor speed feedback according to claim 6, characterized in that, The dynamic decoupling of the updated weights includes: Extract the real-time amplitude change rate of the three-phase stator current data, and determine the current disturbance intensity index based on the real-time amplitude change rate; Based on the real-time operating frequency, a first weighted mapping function for the stator resistance parameter with respect to the comprehensive correction gain and a second weighted mapping function for the flux linkage parameter with respect to the comprehensive correction gain are determined. The output values ​​of the first weighted mapping function and the second weighted mapping function are cross-corrected using the current disturbance intensity index.

8. The dynamic speed control system based on permanent magnet synchronous motor speed feedback according to claim 1, characterized in that, The parameter correction includes: Based on the absolute value of the amplitude of the abnormal disturbance, a dynamic attenuation operator is calculated to adjust the sensitivity of the generation logic; The real-time deviation divergence is reconstructed using the dynamic attenuation operator to obtain the corrected divergence discrimination criterion. Based on the divergence discrimination criterion, the step size of the dynamic feedback reliability factor is limited, and the abnormal disturbance is simultaneously mapped to a deviation cancellation gain with the opposite polarity to the three-phase stator current data. The generation parameters of the dynamic feedback reliability factor are corrected by superimposing the deviation cancellation gain.

9. An electronic device comprising a memory and a processor, characterized in that: The memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions, which, when executed by the processor, implement the steps of the system as described in any one of claims 1 to 8.

10. A computer storage medium storing computer-executable instructions thereon, characterized in that: When the computer-executable instructions are executed by the processor, they implement the steps of the system as described in any one of claims 1 to 8.

Images