Method, system and medium for optimizing dynamic response of frequency converter

Abstract

The application provides a variable frequency converter dynamic response optimization method, system and medium, and relates to the technical field of variable frequency converters. The method comprises the following steps: receiving a motor driving signal, driving a first signal processing threshold to perform sparse representation, determining a time-varying transfer sequence, and the time-varying transfer sequence exists amplification processing based on local phase expansion; a second frequency modulation node identifies the time-varying transfer sequence to determine a variable frequency signal based on a first state space and a second action space, and a directional frequency modulation Markov decision; a third pulse optimization node is triggered to perform pulse coding on the variable frequency signal, and the optimized variable frequency signal is determined through relative balance optimization based on switching loss and harmonic suppression, and the variable frequency converter is controlled and driven. The application solves the technical problem that the variable frequency converter control method in the prior art usually depends on preset fixed control parameters and simple frequency adjustment, the dynamic characteristic response of the motor is insufficient, and the control performance is unstable.

Description

TECHNICAL FIELD

[0001] The application relates to the technical field of frequency converters, and in particular to a frequency converter dynamic response optimization method, system and medium. BACKGROUND

[0002] Frequency converters are widely used in motor drive systems, mainly by adjusting the output frequency and voltage to control the speed and torque of the motor. The core function of the frequency converter is to adjust the power output of the motor to achieve energy saving, improve efficiency and prolong the service life of the motor. However, under high-speed operation and complex working conditions, the dynamic response and control accuracy of the frequency converter are crucial to the overall performance of the system. Traditional frequency converter control methods usually rely on pre-set fixed control parameters and simple frequency adjustment. This method is insufficient for the dynamic characteristics of the motor, especially when the load changes rapidly. The frequency converter often needs a long time to adjust the output signal. When the motor load changes greatly, the response of the frequency converter is slow, which may cause unstable speed and torque, resulting in motor overload or low efficiency, and even may cause equipment damage or shutdown accidents. SUMMARY

[0003] The application provides a frequency converter dynamic response optimization method, system and medium, aiming to solve the technical problem that the existing frequency converter control method usually relies on pre-set fixed control parameters and simple frequency adjustment, which is insufficient for the dynamic characteristics of the motor, resulting in unstable control performance.

[0004] The first aspect of the application discloses a frequency converter dynamic response optimization method, which comprises the following steps: receiving a motor drive signal, driving a first signal processing threshold, performing sparse representation on the motor drive signal, and determining a time-varying transmission sequence, wherein the time-varying transmission sequence exists based on local phase expansion amplification processing; a second frequency modulation node identifies the time-varying transmission sequence to determine a variable frequency signal based on a first state space and a second action space under a directional frequency modulation Markov decision, wherein the first state space is defined by motor drive state characteristics, and the second action space is defined by PID parameters; a third pulse optimization node is triggered to perform pulse coding on the variable frequency signal, and an optimized variable frequency signal is determined by relatively balanced optimization based on switching loss and harmonic suppression, and the frequency converter is controlled and driven.

[0005] In a second aspect, the application discloses a system for optimizing dynamic response of a frequency converter, which is used for the method for optimizing dynamic response of a frequency converter, and comprises: a time-varying transfer sequence determination module, which is used for collecting a motor drive signal, determining a time-varying transfer sequence by performing sparse representation on the motor drive signal and a local phase expansion amplification process based on a first signal processing threshold; a variable frequency signal determination module, which is used for identifying the time-varying transfer sequence at a second frequency modulation node, and determining a variable frequency signal by performing Markov decision of directional frequency modulation based on a first state space and a second action space, wherein the first state space is defined by motor drive state characteristics, and the second action space is defined by PID parameters; and a control driving module, which is used for triggering a third pulse optimization node, performing pulse coding on the variable frequency signal, and determining an optimized variable frequency signal by performing relative balance optimization based on switching loss and harmonic suppression, and performing control driving on the frequency converter.

[0006] In a third aspect, the application discloses a storage medium, which stores a computer program, and the computer program is executed by a processor to implement the steps of the method for optimizing dynamic response of a frequency converter.

[0007] The one or more technical solutions provided in the application have at least the following beneficial effects:

[0008] By performing sparse representation and local phase expansion amplification process on the motor drive signal, instantaneous changes and dynamic characteristics in the motor response can be accurately captured, and local amplification can improve the sensitivity to signals that change rapidly, so that the frequency converter can respond more quickly and accurately to changes in the motor drive signal, and large hysteresis or oscillation can be avoided, which enables the system to finely capture the interaction process between the motor and the frequency converter, thereby optimizing the response speed of the frequency converter and improving the stability and sensitivity thereof; by performing Markov decision of directional frequency modulation based on the first state space and the second action space, intelligent decision support can be provided for variable frequency signal generation, the Markov decision helps to determine the optimal variable frequency signal based on the current state of the motor and the PID parameters, and this method can intelligently adjust the frequency and amplitude of the signal to ensure that the motor always maintains optimal control under different loads or working states; by performing pulse coding on the variable frequency signal and combining the optimization process of switching loss and harmonic suppression, the switching loss and harmonic can be effectively reduced while maintaining the control accuracy of the motor, and the overall efficiency of the motor drive system can be improved; by optimizing the variable frequency signal to control the frequency converter to drive the motor, more accurate control effect can be achieved, the optimized signal not only improves the smoothness of the motor during startup, but also prevents overshoot, oscillation and other unstable phenomena, and enhances the stability and reliability of the system.

[0009] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0010] Figure 1 This is a schematic diagram of the inverter dynamic response optimization method provided in an embodiment of this application.

[0011] Figure 2 This is a schematic diagram of the inverter dynamic response optimization system structure provided in an embodiment of this application.

[0012] Explanation of reference numerals in the attached diagram: Time-varying transmission sequence determination module 10, frequency conversion signal determination module 20, control drive module 30. Detailed Implementation

[0013] This application provides a method, system, and medium for optimizing the dynamic response of frequency converters, which solves the technical problem that existing frequency converter control methods typically rely on preset fixed control parameters and simple frequency adjustment, resulting in insufficient response to the dynamic characteristics of the motor and unstable control performance.

[0014] After introducing the basic principles of this application, various non-limiting embodiments of this application will be described in detail below with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are merely illustrative of this application and are not intended to limit this application.

[0015] Example 1, as Figure 1 As shown in the embodiment of this application, a method for optimizing the dynamic response of a frequency converter is provided, the method comprising:

[0016] The system receives a motor drive signal, drives a first signal processing threshold, performs sparse representation on the motor drive signal, and determines a time-varying transfer sequence, wherein the time-varying transfer sequence undergoes amplification processing based on local phase expansion.

[0017] The motor drive signal is received, which contains instructions for the operation of the motor. The first signal processing threshold is a threshold setting used to preprocess the received motor drive signal. By setting an appropriate first signal processing threshold, important parts of the signal can be screened out, such as noise filtering, to ensure that the data for subsequent processing is more representative. Sparse representation is a technique in signal processing that selectively retains important information in the motor drive signal based on the first signal processing threshold, i.e. key features, and removes redundant data, which means that only the most useful components are retained in the motor drive signal, thereby reducing unnecessary calculations and data storage. The time-varying transfer sequence is a sequence of transfer functions of the motor drive system that changes over time, reflecting the dynamic relationship between the motor state and the motor drive signal. Local phase expansion refers to the amplification of the phase of the local region of the motor drive signal, thereby enhancing the influence of important parts of the signal. This process helps to strengthen the effective information in the signal and reduce the influence of interference signals.

[0018] The second frequency modulation node identifies the time-varying transfer sequence to determine the variable frequency signal based on the first state space and the second action space under the directional frequency modulation Markov decision, wherein the first state space is defined by the motor drive state characteristics, and the second action space is defined by the PID parameters.

[0019] The task of the second frequency modulation node is to identify the dynamic pattern from the time-varying transfer sequence and find out the unstable or adjustable part to make corresponding variable frequency signal adjustment. The first state space describes the motor drive state characteristics, such as the speed of the motor, the load current, the vibration, etc., which reflect the running state of the motor system; the second action space is related to the PID parameters (proportion, integral, and differential coefficients), and according to the current state of the motor, the variable frequency signal is controlled by adjusting the PID parameters to make the motor run more smoothly. By combining the first state space and the second action space, the Markov decision process is used to adjust the frequency directionally. The Markov decision process is an optimization method that selects the optimal action sequence (in this case, the adjustment of the PID parameters) through the transition probability of the state and the action, so that the variable frequency signal can be dynamically adjusted according to the running state of the motor to achieve the best performance. Based on the Markov decision process, the output variable frequency signal is determined.

[0020] The third pulse optimization node is triggered to perform pulse coding on the variable frequency signal, and the optimized variable frequency signal is determined by optimizing the relative balance based on the switching loss and harmonic suppression, and the frequency converter is controlled and driven.

[0021] The third pulse optimization node is used to optimize the output pulse sequence of the variable frequency signal, and the purpose of pulse optimization is to reduce unnecessary losses in the system and improve system efficiency. Pulse coding is performed on the variable frequency signal, which can convert the analog signal into a series of digitized control signals, so that the frequency converter can accurately adjust the motor according to these signals. When the frequency converter performs frequency conversion, each switching operation will produce a certain loss, and one of the goals of the optimization process is to reduce this switching loss. The switching action of the frequency converter will introduce harmonics, which will pollute the power grid. When optimizing, the balance between switching loss and harmonic suppression needs to be balanced to ensure stable operation of the motor and minimal impact on the power grid. Through the relatively balanced optimization based on switching loss and harmonic suppression, the generated optimized variable frequency signal can minimize energy waste and harmonic interference, improving the overall efficiency of the system. The final optimized variable frequency signal will be input to the frequency converter, which will control the operation of the motor according to the optimized variable frequency signal. Through the optimized variable frequency signal, the motor can operate under optimal conditions, achieving higher efficiency and longer service life.

[0022] Further, in the interaction thread between the motor and the frequency converter, an external device data interface is provided; a variable frequency decision plug-in is deployed in the data interface, wherein the variable frequency decision plug-in includes a first signal processing threshold, a second frequency modulation node, and a third pulse optimization node.

[0023] The interaction thread refers to the process of data communication and control logic execution between the motor and the frequency converter, which describes how the frequency converter interacts with the motor in real time, including how to obtain state information from the motor and how to control the operation of the motor. The external device data interface refers to the connection point between the motor and the frequency converter and external devices.

[0024] The variable frequency decision plug-in is deployed in the data interface of the motor and the frequency converter, responsible for deciding the adjustment strategy of the frequency converter based on the received motor state data. The task of the variable frequency decision plug-in is to analyze the input signal, make corresponding decisions, and control the motor through the frequency converter. The first signal processing threshold is used to preprocess the motor drive signal and set the threshold value, which can be dynamically adjusted according to the load, current or other key parameters of the motor. Through the control of the first signal processing threshold, the variable frequency decision plug-in can filter out valid signals and remove useless information to ensure the quality of the subsequent processed signals. The second frequency modulation node is used to analyze the time-varying transmission sequence and make frequency modulation decisions based on the analysis results. Frequency modulation decisions rely on the Markov decision process, combining the motor state space and action space to dynamically adjust the variable frequency signal. The third pulse optimization node is used to optimize the output pulse sequence of the variable frequency signal, mainly through pulse coding and optimization techniques to reduce switching loss and harmonic interference. By adjusting the distribution of pulse width and frequency, the motor can efficiently operate and avoid energy waste and electromagnetic interference.

[0025] Further, the motor drive signal is sparsely represented, and a time-varying transfer sequence is determined, including:

[0026] A threshold condition is determined, in which a signal step of a preset amplitude is conditionally set with a pulse direction change; the frequency conversion decision plug-in receives the motor drive signal, performs signal point screening based on the threshold condition according to the first signal processing threshold, and determines a sparse signal sequence; the sparse signal sequence is phase-expanded in a fuzzy signal segment to determine the time-varying transfer sequence.

[0027] The threshold condition is used to filter the signal, in which a signal step refers to a sudden jump of the signal in the time domain, for example, when the motor load suddenly changes, the drive signal also jumps, and the step point is used to identify the important change of the signal; the pulse direction change refers to the change of the pulse width or frequency direction in the signal, for example, the periodic change or frequency change of the control signal, which can reflect the adjustment demand of the system. By setting a threshold value of the signal amplitude to screen out the step and pulse change points in the signal, the purpose is to only focus on the change part that can significantly affect the operation of the motor in the subsequent processing, and to remove other irrelevant or small fluctuations.

[0028] The frequency conversion decision plug-in receives the motor drive signal, and the signal point screening is to screen out important signal points in the motor drive signal and remove unnecessary interference, and this process is based on the set threshold condition. If the change (such as amplitude or frequency) of the signal exceeds the set threshold value, these signal points will be considered important and retained; otherwise, if the signal fluctuation is less than the threshold value, it will be ignored or filtered out. Sparse representation is a signal processing method that reduces the amount of calculation and storage by retaining only the important components of the signal. The screened signal points form a sparse signal sequence, that is, only the key parts that affect the motor control are retained, reducing redundant data.

[0029] In the sparse signal sequence, there are some fuzzy signal segments, that is, the signals change ambiguously in amplitude, frequency, etc. The existence of the fuzzy signal segment means that the signal change is relatively complex or not completely determined. Phase expansion is a signal processing technique used to adjust and amplify the phase of the signal to better adapt to the needs of the system. Here, the phase of the fuzzy signal segment is expanded to make the signal more accurate in time or frequency, so as to better reflect the dynamic change of the motor. For the motor drive signal, phase expansion helps to effectively control and adjust the fluctuation part of the signal, thereby improving the control accuracy of the frequency converter. Through phase expansion, the time-varying transfer sequence is determined, which describes the control response between the motor and the frequency converter over time.

[0030] Further, the time-varying transfer sequence has a local phase expansion-based amplification process, including:

[0031] Traverse the sparse signal sequence, identify ambiguous signal segments, wherein the preset density of signal points and fluctuation state are taken as identification basis; for the ambiguous signal segments, determine the phase expansion ratio; according to the phase expansion ratio, perform phase expansion processing on the ambiguous signal segments in the sparse signal sequence.

[0032] The purpose of traversing the sparse signal sequence is to check each data point in the sequence one by one, find out those parts with unclear signal characteristics or uncertainties, which are characterized by frequent fluctuations or complex change patterns, and mark these parts as ambiguous signal segments. For example, the load of the motor changes rapidly, resulting in complex changes in the control signal, which is difficult to accurately capture. In the ambiguous signal segment, the signal change may not be a single linear trend, but there are frequent high-frequency fluctuations, resulting in unclear signal itself. Among them, the fluctuation intensity refers to the part of the signal that changes very frequently, and these changes may be caused by sudden load changes or rapid changes in motor state; the fluctuation state refers to the way the signal changes over time, such as frequency, amplitude, etc. By analyzing the fluctuation state, the complexity of the signal can be identified. By setting the preset density and fluctuation state as the identification basis, the ambiguous signal segment can be quickly located. These ambiguous signal segments are irregular or chaotic parts of the signal that need further processing and optimization.

[0033] After identifying the ambiguous signal segment, determine the phase expansion ratio, that is, how to amplify the range of signal changes in the time or frequency domain. The goal of phase expansion is to make the signal in the ambiguous signal segment more explicit and clear, so that it is easier to be recognized and analyzed by subsequent processing steps. The determination of the phase expansion ratio usually involves mathematical calculations, such as dynamically adjusting the expansion ratio according to the amplitude and change speed of the signal. This ratio needs to ensure that important features of the signal are amplified, while not distorting the overall trend of the signal.

[0034] After the phase expansion ratio is determined, the phase expansion processing is performed. The phase expansion processing is a method of adjusting the ambiguous part in the signal through phase amplification, so that the details of the signal are clearer. This is to increase the phase difference of the signal to enhance the degree of change of the signal, thereby facilitating subsequent signal analysis and optimization. For example, the signal fluctuates intensively and the amplitude changes in various ways. To ensure rapid identification, the details of the signal are amplified within a certain time or frequency range through phase expansion. For example, in the case of a signal fluctuation range of 0-π, the phase of the signal will become 0-π / 2-π through phase expansion. In this way, the change of the signal in this section can be displayed more clearly. In this way, the details of the signal can be captured more finely, especially in those ambiguous signal sections with intensive fluctuations. This process is part of the local amplification processing. It makes the details of the signal more prominent through local amplification of important sections in the signal. This is very important for the dynamic response in the signal, especially in the process of motor control. Any subtle change may affect the stability and efficiency of the motor operation.

[0035] Further, the variable frequency signal is determined based on the Markov decision of the first state space and the second action space under the directional frequency modulation, including:

[0036] By identifying the time-varying transmission sequence, a first state deviation group is determined according to the first state space in the second frequency modulation node. According to the first state deviation group, a first state group and a second state group are determined, and a Markov decision of state trend is performed to determine a third control group based on the second action space, wherein the third control group at least contains PID parameters. According to the third control group, a variable frequency signal is generated.

[0037] The first state space describes the motor driving state characteristics, such as the speed of the motor, the load current, the vibration, etc. These characteristics reflect the running state of the motor system. The deviation of the motor state is analyzed, i.e. the difference between the actual running state and the expected target value (such as the set speed, current, etc.). The first state deviation group is a set of errors composed of multiple characteristics, for example: current error, indicating the difference between the current current and the target current; speed deviation, indicating the difference between the current speed and the set speed.

[0038] The first state group and the second state group respectively represent state sets of the system under different conditions, the first state group contains current state information of the motor, such as speed, current, etc., and the second state group represents a desired or target state set, such as a set target speed or current, etc., and the two state groups are determined according to the first state deviation group (i.e. the actual error of the motor). The Markov decision process is used to select the optimal action strategy under the given current state, which assumes that the selection of the current decision is only related to the current state, and is irrelevant to the past state and decision, and the state trend refers to making decisions according to the trend of the current state, which is achieved by modeling the state and using the Markov decision process to calculate the evolution of the possible future state, so as to determine the best control strategy, and here, the Markov decision selects the most appropriate control measure according to the current state of the motor (such as speed, current, etc.) and the target state (desired speed, target current, etc.).

[0039] The second action space is related to the PID parameters (proportion, integral, and differential coefficients), and according to the current state of the motor, the PID parameters are adjusted to control the variable frequency signal, so that the motor runs more smoothly. The third control group is a set of control strategies obtained based on the above Markov decision, which contains a series of control parameters, and the PID parameters are the most important part, which are used to adjust the input of the system to make the output of the system as close to the desired target as possible. Here, the optimization of the PID parameters is used to adjust the output signal of the frequency converter, including the proportional gain, integral time, and differential time.

[0040] The final variable frequency signal is generated based on the third control group, which is directly used to control the operation of the frequency converter to achieve precise speed regulation and stable operation of the motor.

[0041] Further, the optimized variable frequency signal is determined, including:

[0042] According to the variable frequency signal, a PWM pulse sequence is determined, and the PWM pulse sequence is optimized in pulse distribution to determine the optimized variable frequency signal, with switching loss and harmonic suppression as the guide.

[0043] PWM (Pulse Width Modulation) is a common method for controlling motor speed and output power. The basic principle of PWM is to adjust the width of the pulse (i.e. the duty cycle) to achieve voltage regulation, thereby controlling the power of the motor. In this step, the variable frequency signal is converted into a PWM signal, which represents the frequency and amplitude information required for motor driving, and the PWM signal is the actual control signal to achieve these requirements. This process involves converting the time domain signal of the variable frequency signal to ensure that the motor operates at a stable frequency, and the generated PWM pulse sequence controls the power output of the motor by changing the pulse width.

[0044] In order to reduce switching loss and reduce the generation of harmonics, pulse distribution optimization is performed on the PWM pulse sequence. In this process, coding technology is used to process the PWM signal, so that the optimization problem can be expressed and solved by algebraic method. Specifically, the different pulse points, pulse width and other related characteristics of the PWM signal are converted into symbol sequences by using coding. For the coded symbol sequence, further fine-tuning of the pulse distribution is performed, so that the final PWM signal can achieve the optimal effect as much as possible under the condition of meeting the switching loss and harmonic suppression. This fine-tuning ensures that the frequency converter can operate with minimal loss and interference.

[0045] Further, the pulse distribution optimization of the PWM pulse sequence is guided by switching loss and harmonic suppression, which includes:

[0046] The PWM pulse sequence is pulse state coded to determine a pulse symbol sequence, wherein each pulse node is represented as a first symbol based on switching loss and a second symbol based on harmonic suppression. A preset iteration mode is introduced, wherein the positioning of the target pulse point is iteratively processed based on the relative balance of the first symbol and the second symbol, and the target pulse point is a pre-optimized pulse point. According to the preset iteration mode, the pulse symbol sequence is iteratively optimized to determine an optimized pulse distribution. The optimized pulse distribution is replaced in the PWM pulse sequence to determine the optimized variable frequency signal.

[0047] Pulse state coding of the PWM pulse sequence means that the PWM signal is converted into a sequence composed of symbols by coding different characteristics of each pulse, such as pulse width, frequency, timing, etc. to determine a pulse symbol sequence, wherein the first symbol is a symbol related to switching loss, which usually occurs in each switching action. By coding the timing and amplitude of the switch, it helps to evaluate the contribution of each pulse to power loss; the second symbol is a symbol related to harmonic suppression. Harmonics are caused by irregular PWM waveforms, so the effect of each pulse on reducing harmonics needs to be considered during the coding process. In this way, the spectral characteristics of the signal are optimized.

[0048] The preset iteration mode is introduced. Specifically, the iteration mode refers to continuously optimizing the distribution of PWM pulses through multiple steps, so that the final PWM signal can meet the needs of reducing switching loss and harmonic suppression at the same time. The target pulse point refers to the key pulse that needs to be adjusted in the optimization process. By selecting the target pulse point, the timing and width of these pulses can be focused on adjusting, thereby significantly affecting the overall effect of the PWM signal. In the iteration process, the pulse distribution is adjusted according to the relative balance between the first symbol and the second symbol. The weights of switching loss and harmonic suppression need to be balanced through the iteration process, that is, the influence of switching loss is reduced in certain pulse positions, while the optimization of harmonic suppression is increased. This is achieved by gradually adjusting pulse width and frequency characteristics.

[0049] According to the preset iteration mode, the pulse symbol sequence is gradually optimized. In this process, the optimization effect of the pulse is calculated at each step, including switching loss and harmonic suppression, and adjustment is made according to the optimization target. This is a multi-round adjustment process. After each adjustment, the pulse distribution is evaluated. If the effect is better, the adjustment result is kept; if the effect is not ideal, the adjustment continues until the predetermined optimization target is met. Finally, through these iteration steps, the optimized pulse distribution is obtained.

[0050] The original PWM pulse sequence is replaced by the optimized pulse distribution. Specifically, the original pulse timing and width are replaced with the adjusted results, so that the new PWM signal has lower switching loss and better harmonic suppression performance in operation, and finally the optimized variable frequency signal is obtained.

[0051] Further, the variable frequency decision plug-in outputs the optimized variable frequency signal, transmits according to the interaction thread, and executes variable frequency control driving in response to the frequency converter; wherein, after executing the variable frequency control driving, it includes: tracking the variable frequency driving response, wherein the variable frequency driving response contains the running data of the frequency converter and the motor; according to the variable frequency driving response, performing variable frequency optimization evaluation to determine the variable frequency control coefficient; adding the variable frequency control coefficient into the temporary database, performing variable frequency error positioning and tracing of the preset period, and performing feedback response optimization management.

[0052] The optimized variable frequency signal is transmitted to the frequency converter through the interaction thread. In this process, the frequency converter responds and starts to control according to the optimized variable frequency signal. This transmission mechanism ensures the accurate transmission of the optimized variable frequency signal from the variable frequency decision plug-in to the frequency converter.

[0053] After performing the variable frequency control driving, the next task is to track the variable frequency driving response, which means the running state of the frequency converter and the motor will be monitored in real time. The tracking content includes the running data of the frequency converter and the motor, such as current, voltage, speed, temperature, etc. These data are used to judge the control effect of the frequency converter, including whether the frequency converter works according to the predetermined target and whether the motor runs in the expected working state.

[0054] According to the variable frequency driving response, the effect after the variable frequency control driving is evaluated, including whether it can effectively avoid stepwise large control. For example, when the driving system starts, especially when the motor load is large or the starting moment is sensitive, a continuous step-up slow start strategy is usually adopted. This starting method is more smooth compared with stepwise starting (large change of voltage and frequency), which can reduce the impact and vibration of the motor and improve the stability of the system. By monitoring the driving response data, it is judged whether the driving effect is consistent with the expectation. If the motor can start smoothly and reach the predetermined speed, and there is no excessive jitter or overload during operation, it means that the optimized variable frequency signal is effective. On the contrary, if there is obvious control abnormality such as overshoot, oscillation or unstable state, the variable frequency control parameters need to be re-evaluated and adjusted. Based on the result of optimization evaluation, the variable frequency control coefficient is determined, which is an index for adjusting the PID parameters, used for fine adjustment of the output of the frequency converter to further optimize the control effect.

[0055] The variable frequency control coefficient is stored in a temporary database. This storage method can ensure that all optimization parameters and control data are recorded for review and adjustment at any time. Variable frequency error positioning and tracing are performed regularly. If an abnormal or unexpected response occurs, tracing can quickly find the root cause of the problem. By analyzing historical data, variable frequency control coefficients, variable frequency signals and other information, the cause of failure or performance decline can be effectively located. Based on the results of error positioning and tracing analysis, feedback response optimization is performed, which means that according to the feedback obtained in actual operation, the variable frequency control strategy and optimization parameters are adjusted again to ensure that the performance of the frequency converter and the motor remains in the best state in long-term operation.

[0056] In summary, the variable frequency converter dynamic response optimization method provided by the embodiments of the present application has the following technical effects:

[0057] By sparse representation of motor drive signal and local phase expansion processing, the instantaneous changes and dynamic characteristics in motor response can be accurately captured, and local amplification can improve the sensitivity to signals that change quickly, ensuring that the frequency converter responds more quickly and accurately to changes in motor drive signals, avoiding excessive lag or oscillation, which enables the system to finely capture the interaction process between the motor and the frequency converter, thereby optimizing the response speed of the frequency converter and improving its stability and sensitivity; By Markov decision making in the first state space and the second action space, intelligent decision support can be provided for frequency signal generation, and Markov decision making can help determine the optimal frequency signal based on the current state of the motor and the PID parameters. This method can intelligently adjust the frequency and amplitude of the signal to ensure that the motor always maintains optimal control under different loads or working conditions; By pulse coding of the frequency signal and combining the optimization of switching loss and harmonic suppression, the control accuracy of the motor can be maintained while effectively reducing switching loss and harmonics, improving the overall efficiency of the motor drive system; By optimizing the frequency signal to control the frequency converter to drive the motor, a more accurate control effect is achieved, and the optimized signal not only improves the smoothness of the motor during startup, but also prevents overshoot, oscillation and other unstable phenomena, enhancing the stability and reliability of the system.

[0058] In the second embodiment, based on the same inventive concept as the frequency converter dynamic response optimization method in the preceding embodiments, as shown in the following table, the present application provides a frequency converter dynamic response optimization system, which comprises: Figure 2

[0059] The time-varying transmission sequence determination module 10 is configured to receive a motor drive signal, drive a first signal processing threshold, perform sparse representation on the motor drive signal, and determine a time-varying transmission sequence, wherein the time-varying transmission sequence is subjected to amplification processing based on local phase expansion; the frequency signal determination module 20 is configured to identify the time-varying transmission sequence at a second frequency modulation node, and determine a frequency signal based on Markov decision making of directional frequency modulation in a first state space and a second action space, wherein the first state space is defined based on motor drive state characteristics, and the second action space is defined based on PID parameters; the control driving module 30 is configured to trigger a third pulse optimization node, perform pulse coding on the frequency signal, and determine an optimized frequency signal based on relative balance optimization of switching loss and harmonic suppression, and control and drive the frequency converter.

[0060] Further, a data interface is deployed in the interaction thread between the motor and the frequency converter; a frequency decision plug-in is deployed in the data interface, wherein the frequency decision plug-in includes a first signal processing threshold, a second frequency modulation node, and a third pulse optimization node.

[0061] Further, the time-varying transmission sequence determination module 10 is configured to perform the following operation steps:​

[0062] determining a threshold condition, wherein a signal step with a preset amplitude and a pulse direction change are conditionally set; the variable frequency decision plug-in receives the motor driving signal, and performs signal point screening based on the threshold condition according to the first signal processing threshold, to determine a sparse signal sequence; and the sparse signal sequence is subjected to phase expansion of a fuzzy signal section, to determine the time-varying transmission sequence.

[0063] Further, the time-varying transmission sequence determination module 10 is configured to perform the following operation steps:

[0064] traversing the sparse signal sequence to identify a fuzzy signal section, wherein a preset density of signal points and a wave state are taken as identification bases; for the fuzzy signal section, a phase expansion ratio is determined; and the fuzzy signal section in the sparse signal sequence is subjected to phase expansion processing according to the phase expansion ratio.

[0065] Further, the variable frequency signal determination module 20 is configured to perform the following operation steps:

[0066] by identifying the time-varying transmission sequence, a first state deviation group is determined according to a first state space in the second frequency modulation node; a first state group and a second state group are determined according to the first state deviation group, a Markov decision of state trend change is performed, a third control group based on a second action space is determined, wherein the third control group at least contains PID parameters; and a variable frequency signal is generated according to the third control group.

[0067] Further, the control driving module 30 is configured to perform the following operation steps:

[0068] a PWM pulse sequence is determined according to the variable frequency signal; and the PWM pulse sequence is subjected to pulse distribution optimization oriented to switching loss and harmonic suppression, to determine an optimized variable frequency signal.

[0069] Further, the control driving module 30 is configured to perform the following operation steps:

[0070] the PWM pulse sequence is subjected to pulse state coding, to determine a pulse symbol sequence, wherein each pulse node is represented as a first symbol based on switching loss and a second symbol based on harmonic suppression; a preset iteration mode is introduced, wherein a target pulse point is located, and iteration processing based on relative balance of the first symbol and the second symbol is performed, the target pulse point is a pre-optimized pulse point; the pulse symbol sequence is subjected to iteration optimization according to the preset iteration mode, to determine an optimized pulse distribution; and the optimized pulse distribution is replaced in the PWM pulse sequence, to determine the optimized variable frequency signal.

[0071] Further, the frequency conversion decision plug-in outputs the optimized frequency conversion signal, transmits according to the interaction thread, and executes frequency conversion control driving in response to the frequency converter; wherein after executing the frequency conversion control driving, the method comprises: tracking the frequency conversion driving response, wherein the frequency conversion driving response contains operation data of the frequency converter and the motor; performing frequency conversion optimization evaluation according to the frequency conversion driving response, determining the frequency conversion control coefficient; adding the frequency conversion control coefficient into the temporary database, performing frequency conversion error positioning and tracing for a preset period, and performing feedback response optimization management.

[0072] The foregoing detailed description of the method for optimizing the dynamic response of the frequency converter enables those skilled in the art to clearly understand the frequency converter dynamic response optimization system in the embodiments. Since the system corresponds to the method disclosed in the embodiments, it is described simply, and the relevant parts can be referred to the method part description.

[0073] Embodiment three provides a storage medium having a computer program stored thereon, wherein the computer program is executed by a processor to implement any step of the method of embodiment one.

[0074] The technical features of the above embodiments can be combined in any manner. To make the description concise, not all possible combinations of the technical features in the above embodiments are described, however, as long as the combinations of the technical features do not exist contradictions, they should be considered as the scope of the present disclosure.

[0075] The above description of the disclosed embodiments enables those skilled in the art to implement or use the present application. Various modifications to the embodiments will be apparent to those skilled in the art, and the general principles defined herein can be implemented in other embodiments without departing from the spirit or scope of the present application. Therefore, the present application will not be limited to the embodiments shown herein, but will conform to the widest scope consistent with the principles and novel features disclosed herein.

Claims

1. A method for optimizing the dynamic response of a frequency converter, characterized by The method comprises: receiving a motor drive signal, driving a first signal processing threshold, performing sparse representation on the motor drive signal, determining a time-varying transfer sequence, wherein the time-varying transfer sequence exists amplification processing based on local phase expansion, wherein the local phase expansion refers to amplifying the phase of the local area of the motor drive signal; a second frequency modulation node identifies the time-varying transfer sequence to determine a variable frequency signal based on Markov decision of directional frequency modulation under a first state space and a second action space, wherein the first state space is defined by motor drive state characteristics, and the second action space is defined by PID parameters; a third pulse optimization node is triggered to perform pulse coding on the variable frequency signal, and an optimized variable frequency signal is determined by relatively balanced optimization based on switching loss and harmonic suppression to control and drive the frequency converter.

2. The method of claim 1, wherein the frequency converter dynamic response optimization is performed by: an external data interface is arranged in the interaction thread of the motor and the frequency converter; a variable frequency decision plug-in is arranged in the data interface, wherein the variable frequency decision plug-in comprises the first signal processing threshold, the second frequency modulation node and the third pulse optimization node.

3. The method of claim 2, wherein the step of determining the frequency of the variable frequency drive is performed by the variable frequency drive. The method comprises: determining a threshold condition, wherein the condition is set by signal step and pulse direction change with a preset amplitude; the variable frequency decision plug-in receives the motor drive signal, performs signal point screening based on the threshold condition according to the first signal processing threshold, and determines a sparse signal sequence; phase expansion of the fuzzy signal section is performed on the sparse signal sequence to determine the time-varying transfer sequence.

4. The method of claim 3, wherein the frequency converter dynamic response optimization is performed by: The time-varying transfer sequence exists amplification processing based on local phase expansion, comprising: traverse the sparse signal sequence to identify fuzzy signal sections, wherein the preset density of signal points and fluctuation state are used as identification basis; determine the phase expansion ratio for the fuzzy signal section; perform phase expansion processing on the fuzzy signal section in the sparse signal sequence according to the phase expansion ratio.

5. The method of claim 1, wherein the frequency converter dynamic response optimization is performed by a computer. The method comprises: determine a first state deviation group according to the first state space in the second frequency modulation node by identifying the time-varying transfer sequence; determine a first state group and a second state group according to the first state deviation group, perform Markov decision of state trend change, and determine a third regulation group based on the second action space, wherein the third regulation group at least comprises PID parameters; generate a variable frequency signal according to the third regulation group.

6. The method of claim 1, wherein the frequency converter dynamic response optimization is performed by a computer. The method comprises: determine a PWM pulse sequence according to the variable frequency signal; perform pulse distribution optimization on the PWM pulse sequence to determine an optimized variable frequency signal, which is guided by switching loss and harmonic suppression.

7. The method of claim 6, wherein the step of determining the frequency of the variable frequency drive is performed by: determining a frequency of the variable frequency drive based on the frequency of the motor and the speed of the motor. The method comprises: perform pulse state coding on the PWM pulse sequence to determine a pulse code sequence, wherein each pulse node is represented by a first code element based on switching loss and a second code element based on harmonic suppression; introducing a preset iteration mode, wherein, in the positioning of a target pulse point, an iteration process is performed based on the relative equalization of the first symbol and the second symbol, and the target pulse point is a pre-optimized pulse point; According to the preset iteration mode, the pulse symbol sequence is iteratively optimized to determine an optimized pulse distribution; In the PWM pulse sequence, the optimized pulse distribution is replaced to determine the optimized variable frequency signal.

8. The method of claim 2, wherein the frequency converter dynamic response optimization is performed by a computer. The variable frequency decision plug-in outputs the optimized variable frequency signal, transmits according to the interaction thread, and responds to the frequency converter to perform variable frequency control driving; After performing the variable frequency control driving, it includes: Tracking variable frequency driving response, wherein the variable frequency driving response contains the operation data of the frequency converter and the motor; According to the variable frequency driving response, the variable frequency optimization evaluation is performed to determine the variable frequency control coefficient; Add the variable frequency control coefficient to the temporary database to perform preset period variable frequency error positioning and tracing, and perform feedback response optimization management.

9. A variable frequency drive dynamic response optimization system, characterized by, The system for implementing the variable frequency dynamic response optimization method of any one of claims 1-8, the system comprising: a time-varying transfer sequence determination module (10) for receiving a motor driving signal, driving a first signal processing threshold, performing sparse representation on the motor driving signal, and determining a time-varying transfer sequence, wherein the time-varying transfer sequence exists based on local phase expansion amplification processing; a variable frequency signal determination module (20) for identifying the time-varying transfer sequence at a second frequency modulation node to determine a variable frequency signal based on a Markov decision of directional frequency modulation under a first state space and a second action space, wherein the first state space is defined by motor driving state characteristics and the second action space is defined by PID parameters; a control driving module (30) for triggering a third pulse optimization node to perform pulse coding on the variable frequency signal, determining an optimized variable frequency signal through relative equalization optimization based on switching loss and harmonic suppression, and performing control driving on the frequency converter.

10. A storage medium having stored thereon a computer program, characterized in that The computer program is executed by the processor to realize the steps of the variable frequency dynamic response optimization method of any one of claims 1 to 8. The computer program is executed by the processor to realize the steps of the variable frequency dynamic response optimization method of any one of claims 1 to 8.

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