A method for suppressing switching frequency jitter in charger PFC control

Abstract

The application provides a switching frequency jitter inhibition method for charger PFC control, relates to the technical field of jitter inhibition, and performs data monitoring on a switching tube of a charger PFC stage to obtain switching tube monitoring data, performs switching frequency analysis according to the switching tube monitoring data to obtain switching frequency analysis data, performs dynamic adjustment analysis according to the switching frequency analysis data to obtain dynamic adjustment data of a switching tube driving signal, performs adjustment interference analysis according to the dynamic adjustment data to obtain adjustment interference analysis data, performs jitter offset compensation analysis according to the adjustment interference analysis data to obtain jitter offset compensation analysis data, obtains a target switching frequency according to the jitter offset compensation analysis data, performs closed-loop control, and obtains closed-loop control information. The application realizes full-process and full-range inhibition of switching frequency jitter, avoids potential safety hazards, such as PFC circuit instability and power factor reduction, caused by frequency jitter from the root, and guarantees normal operation of the charger PFC stage.

Description

Technical Field

[0001] This invention proposes a method for suppressing switching frequency jitter in charger PFC control, which relates to the field of jitter suppression technology, specifically to the field of suppressing switching frequency jitter in charger PFC control. Background Technology

[0002] As the core component of power conversion, the switching frequency stability of the PFC stage in a charger directly determines the charger's operational reliability, power factor, and device losses. In practical applications, the switching frequency is susceptible to fluctuations caused by four factors: input voltage fluctuations, sudden load changes, device temperature drift, and external electromagnetic interference. This fluctuation can lead to PFC circuit instability, decreased power factor, increased switching transistor losses, shortened device and overall charger system lifespan, and reduced charger adaptability under complex operating conditions. Traditional switching frequency jitter suppression methods are relatively simple, often targeting a single cause, and cannot address the combined effects of dynamic changes in operating conditions and various interferences. They suffer from low adjustment precision and poor adaptability, making it difficult to achieve effective suppression of frequency jitter throughout the entire process and failing to meet the charger's requirements for efficient and stable operation. Summary of the Invention

[0003] This invention provides a method for suppressing switching frequency jitter in charger PFC control to solve the above-mentioned problems: This invention proposes a method for suppressing switching frequency jitter in charger PFC control, the method comprising: S1. Monitor the data of the PFC stage switching transistor of the charger, obtain the switching transistor monitoring data, and perform switching frequency analysis based on the switching transistor monitoring data to obtain switching frequency analysis data. S2. Perform dynamic adjustment analysis based on the switching frequency analysis data to obtain dynamic adjustment data of the switching transistor drive signal. Perform adjustment interference analysis based on the dynamic adjustment data to obtain adjustment interference analysis data. S3. Perform jitter compensation analysis based on the adjustment interference analysis data to obtain jitter compensation analysis data. Obtain the target switching frequency based on the jitter compensation analysis data and perform closed-loop control to obtain closed-loop control information.

[0004] Furthermore, the system includes: The monitoring and analysis module is used to monitor the data of the PFC-level switching transistors in the charger, obtain the switching transistor monitoring data, and perform switching frequency analysis based on the switching transistor monitoring data to obtain switching frequency analysis data. The interference analysis module is used to perform dynamic adjustment analysis based on the switching frequency analysis data to obtain dynamic adjustment data of the switching transistor drive signal, and to perform adjustment interference analysis based on the dynamic adjustment data to obtain adjustment interference analysis data. The jitter compensation analysis module is used to perform jitter compensation analysis based on the adjustment interference analysis data, obtain jitter compensation analysis data, obtain the target switching frequency based on the jitter compensation analysis data, perform closed-loop control, and obtain closed-loop control information.

[0005] The beneficial effects of this invention are as follows: This method effectively solves the technical problems of traditional switching frequency jitter suppression methods being singular, lacking specificity, and unable to take into account dynamic changes in operating conditions and various interference effects. It breaks through the limitations of traditional methods, which can only suppress a single cause and have poor adaptability. Through a full-process control mechanism, it achieves full-process and all-round suppression of switching frequency jitter, fundamentally avoiding safety hazards such as PFC circuit instability and power factor decline caused by frequency jitter, and ensuring the normal operation of the charger's PFC stage. At the same time, it effectively improves the charger's adaptability and operational reliability under complex operating conditions, reduces the additional losses of the switching transistor caused by frequency jitter, extends the service life of the switching transistor and the entire charger system, enhances the stability and consistency of system operation, and ensures that the charger can output stably in various working scenarios, meeting the requirements of high efficiency and safety in power conversion. Attached Figure Description

[0006] Figure 1 A schematic diagram of a switching frequency jitter suppression method for PFC control of a charger; Figure 2 This is a schematic diagram for switching frequency analysis; Figure 3 This is a schematic diagram of fluctuation interference analysis; Figure 4 This is a diagram illustrating compensation and adjustment. Detailed Implementation

[0007] The preferred embodiments of the present invention will be described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are for illustration and explanation only and are not intended to limit the present invention.

[0008] In one embodiment of the present invention, a method for suppressing switching frequency jitter in charger PFC control is provided, the method comprising: S1. Monitor the data of the PFC stage switching transistor of the charger, obtain the switching transistor monitoring data, and perform switching frequency analysis based on the switching transistor monitoring data to obtain switching frequency analysis data. S2. Perform dynamic adjustment analysis based on the switching frequency analysis data to obtain dynamic adjustment data of the switching transistor drive signal. Perform adjustment interference analysis based on the dynamic adjustment data to obtain adjustment interference analysis data. S3. Perform jitter compensation analysis based on the interference analysis data to obtain jitter compensation analysis data. Based on this data, determine the target switching frequency and perform closed-loop control to obtain closed-loop control information, such as... Figure 1 As shown.

[0009] This invention addresses the switching frequency jitter problem of PFC-stage switching transistors.

[0010] Switching frequency jitter is mainly caused by four types of factors: input voltage fluctuation, load change, device temperature drift, and external electromagnetic interference.

[0011] This method collects relevant data of the switching transistor, analyzes frequency fluctuations, and establishes basic data support; adjusts the switching transistor drive signal based on the S1 result, identifies interference during the adjustment process; compensates for the interference, determines the stable target switching frequency, and ensures frequency stability through closed-loop control.

[0012] Switch monitoring data: switch electrical parameters, timing parameters, and environmental parameters; Switching frequency analysis data: frequency fluctuation characteristics and their correspondence with electrical anomalies; Dynamic adjustment data: Adjustment parameters of the switching transistor drive signal (on / off timing, drive voltage, etc.); Adjustment interference analysis data: characteristics and degree of impact of interference during the adjustment process; Jitter cancellation compensation analysis data: compensation parameters, timing and method; Target switching frequency: The dynamically stable frequency adapted to the current operating conditions; Closed-loop control information: control parameters, frequency convergence effect, and system stability data.

[0013] The working principle and technical effects of the above-mentioned technical solution are as follows: This method comprehensively monitors the PFC-level switching transistors, collecting their electrical parameters, timing parameters, and environmental parameters. This allows for in-depth analysis of the switching frequency, clarifying frequency fluctuation characteristics and the correspondence between fluctuations and electrical anomalies, accurately capturing the initial state and underlying causes of frequency jitter. Based on the switching frequency analysis data, the switching transistor drive signal is dynamically adjusted to determine the on / off timing, drive voltage, and other adjustment parameters. Simultaneously, potential interference during adjustment is identified, and its characteristics and impact are analyzed. For the identified adjustment interference, targeted jitter compensation analysis is performed to determine compensation parameters, timing, and methods, thereby obtaining a dynamically stable target switching frequency suitable for the current operating conditions. Through closed-loop control and continuous feedback and adjustment, the switching frequency is ensured to remain stable within the target range. The core causes of switching frequency jitter include four categories: input voltage fluctuations, load mutations, device temperature drift, and external electromagnetic interference. The entire control mechanism revolves around these four causes, achieving jitter suppression across all scenarios and processes.

[0014] This method effectively solves the technical challenges of traditional switching frequency jitter suppression methods, which are often singular, lack specificity, and cannot simultaneously address dynamic changes in operating conditions and various interference effects. It overcomes the limitations of traditional methods, which can only suppress a single cause and have poor adaptability. Through a full-process control mechanism, it achieves comprehensive and all-round suppression of switching frequency jitter, fundamentally avoiding safety hazards such as PFC circuit instability and power factor degradation caused by frequency jitter, thus ensuring the normal operation of the charger's PFC stage. Simultaneously, it effectively improves the charger's adaptability and operational reliability under complex operating conditions (such as input voltage fluctuations, load changes, high-temperature environments, and strong electromagnetic interference scenarios), reduces additional losses in the switching transistors caused by frequency jitter, extends the lifespan of the switching transistors and the entire charger system, enhances system stability and consistency, and ensures stable output from the charger under various operating scenarios, meeting the requirements for high efficiency and safety in power conversion.

[0015] In one embodiment of the present invention, S1 includes: like Figure 2 As shown, the switching status of the PFC stage switching transistor in the charger is collected to obtain switching status data. Multiple switch status data are sorted according to the acquisition timing information to obtain switch monitoring data; Based on the preset switching transistor acquisition frequency information, the corresponding switching transistor monitoring data is obtained and the electrical feature information is extracted to obtain the electrical feature monitoring dataset. Based on the electrical feature monitoring dataset, perform electrical feature anomaly analysis to obtain electrical feature anomaly analysis data; Switching frequency analysis data is obtained by performing switching frequency analysis based on electrical characteristic anomaly analysis data.

[0016] Switching status acquisition: High-precision sensors and high-speed ADCs are used to acquire the switching transistor's Vgs, Vds, Is, and timing signals. The sampling frequency is no less than 20 times the rated frequency of the switching transistor to ensure the capture of transient characteristics.

[0017] Data sorting: Collected data is sorted by microsecond-level timestamps to establish a time correlation between frequency fluctuations and electrical parameters, which facilitates traceability.

[0018] Electrical feature extraction: At preset frequencies of 10μs and 50μs / time, feature parameters such as conduction time and dead time are extracted to form an electrical feature monitoring dataset.

[0019] Electrical characteristic anomaly analysis: Compare characteristic parameters with normal baseline values, identify abnormal data, analyze the anomaly type, duration and magnitude, and output anomaly analysis data.

[0020] Switching frequency analysis: Remove invalid periodic data, calculate real-time frequency, analyze fluctuation characteristics and their correlation with electrical anomalies, and output switching frequency analysis data.

[0021] The working principle and technical effect of the above technical solution are as follows: This method uses a high-precision sensor and a high-speed ADC (analog-to-digital converter) to collect the switching state of the PFC stage switching transistor in the charger. It focuses on collecting Vgs (gate-source voltage), Vds (drain-source voltage), Is (drain current), and timing signals of the switching transistor. To ensure the capture of the transient operating characteristics of the switching transistor, the sampling frequency is set to no less than 20 times the rated frequency of the switching transistor, avoiding the loss of transient fluctuation data due to insufficient sampling frequency. The collected switching state data are sorted according to microsecond-level timestamps to establish a correspondence between the switching transistor's operating data and time, forming a complete switching transistor monitoring dataset. This facilitates tracing the time correlation between frequency fluctuations and changes in electrical parameters, and accurately locating the time node where jitter occurs. According to the preset... At sampling frequencies of 10μs and 50μs / time, key electrical characteristic parameters such as conduction time and dead time are extracted from the switching transistor monitoring data to form an electrical characteristic monitoring dataset. This dataset focuses on core parameters related to frequency jitter and reduces interference from invalid data. The extracted electrical characteristic parameters are compared with preset normal reference values ​​to identify abnormal data exceeding the reference values. The type, duration, and fluctuation amplitude of the abnormal data are analyzed, and electrical characteristic anomaly analysis data is output to clarify the specific circumstances of the electrical parameter anomalies. Based on the electrical characteristic anomaly analysis data, invalid periodic data is removed, the real-time operating frequency of the switching transistor is calculated, and the characteristics of frequency fluctuations (such as fluctuation amplitude and fluctuation rate) and the correlation between frequency fluctuations and electrical parameter anomalies are analyzed in depth. Finally, switching frequency analysis data is output.

[0022] This method solves the technical problems of low sampling accuracy, disorganized data, and inability to accurately capture the correlation between frequency fluctuations and electrical anomalies in traditional monitoring methods. It achieves high-precision, full-time-series acquisition and accurate analysis of switching transistor data. Through high-precision sampling and microsecond-level time-series sorting, the completeness and accuracy of monitoring data are ensured, avoiding the omission of transient fluctuation data and providing reliable basic data support for subsequent processes. Electrical feature extraction and anomaly analysis can accurately identify abnormal electrical parameters, clarify the anomaly type and its impact range. Switching frequency analysis eliminates invalid data, establishes the correlation between frequency fluctuations and electrical anomalies, and accurately locates the initial cause of frequency jitter, avoiding blind adjustments in subsequent processes. Overall, this embodiment improves the accuracy and reliability of switching frequency monitoring, reduces problems such as adjustment failures and inadequate compensation caused by inaccurate or incomplete data, and ensures the pertinence and effectiveness of the entire control mechanism.

[0023] In one embodiment of the present invention, the step of performing electrical feature anomaly analysis based on an electrical feature monitoring dataset to obtain electrical feature anomaly analysis data includes: Obtain time-series electrical characteristic data at different time-series nodes based on electrical characteristic monitoring data; Anomaly data extraction is performed on time-series electrical characteristic data to obtain time-series anomaly characteristic data; Obtain the time interval data of adjacent time series anomaly feature data to obtain anomaly feature time interval data; The abnormal feature interval time data is compared with the preset abnormal feature interval time threshold to obtain the abnormal feature interval comparison result; Electrical characteristic status is determined based on the comparison results of abnormal characteristic intervals, and electrical characteristic anomaly analysis data is obtained.

[0024] Acquire time-series electrical characteristic data: Extract electrical characteristic parameters at each acquisition time in chronological order to form a time-series sequence.

[0025] Anomaly data extraction: Compare feature parameters with baseline thresholds to filter out time-series anomalous feature data that exceed the thresholds.

[0026] Anomaly Interval Calculation: Calculate the time interval between adjacent anomaly data to form an interval time series.

[0027] Abnormal interval comparison: The interval time is compared with the preset thresholds of 1ms and 10ms to obtain the comparison result.

[0028] Electrical characteristic status determination: Based on the comparison results, anomalies are classified as stable anomalies (intervals consistently less than the threshold), random interference (intervals random), and occasional anomalies (intervals consistently greater than the threshold), and anomaly analysis data is output.

[0029] The working principle and technical effect of the above technical solution are as follows: This method extracts electrical characteristic parameters from electrical characteristic monitoring data in chronological order at each acquisition moment, forming a complete time-series electrical characteristic sequence. This ensures the temporal continuity of anomaly analysis and avoids misjudgments caused by time discontinuities. Each characteristic parameter in the time-series electrical characteristic sequence is compared with a preset benchmark threshold. Time-series abnormal characteristic data exceeding the benchmark threshold are selected, clarifying the specific values ​​and corresponding time points of the abnormal data, and initially identifying the anomaly. The interval time between two adjacent time-series abnormal characteristic data is calculated to form an abnormal characteristic interval time sequence. The system analyzes the occurrence patterns of anomalies to determine whether they occur continuously, randomly, or sporadically. It compares the anomaly interval data with two preset thresholds of 1ms and 10ms to obtain the anomaly interval comparison results, distinguishing between different interval types of anomalies. Based on the anomaly interval comparison results, it classifies the electrical characteristic states into three categories: stable anomalies (intervals consistently less than the threshold, i.e., continuous occurrences), random disturbances (intervals with no regularity and random fluctuations), and sporadic anomalies (intervals consistently greater than the threshold, i.e., occasional occurrences). The final output includes electrical characteristic anomaly analysis data containing the anomaly type, occurrence pattern, and scope of impact.

[0030] This method addresses the technical problem of traditional electrical anomaly analysis, which can only identify the existence of anomalies but cannot distinguish their types or patterns of occurrence. It achieves accurate classification and pattern identification of electrical characteristic anomalies. Through time-series analysis, the continuity and completeness of anomaly analysis are ensured, avoiding misjudgments caused by isolated anomaly data. By calculating anomaly intervals and comparing thresholds, it can accurately distinguish between stable anomalies, random interference, and sporadic anomalies, clarifying the occurrence patterns of different anomalies and avoiding misjudgments of frequency jitter causes due to confusing different types of anomalies. Furthermore, this embodiment improves the precision of electrical characteristic anomaly analysis, accurately locating the impact range and occurrence patterns of anomalies, reducing adjustment deviations and compensation failures caused by inaccurate anomaly identification, and further enhancing the reliability and specificity of the entire jitter suppression method.

[0031] In one embodiment of the present invention, the step of performing switching frequency analysis based on electrical characteristic anomaly analysis data to obtain switching frequency analysis data includes: Obtain switching frequency information, extract frequency features from the switching frequency information, and obtain frequency feature extraction information; By temporally correlating frequency feature extraction information with electrical feature anomaly analysis data, temporal correlation information is obtained. By correlating frequency feature extraction information with electrical feature anomaly analysis data, feature correlation information is obtained. By associating time-related information with feature-related information, time-feature-related information is obtained; The time feature correlation information is the switching frequency analysis data.

[0032] Frequency feature extraction: Calculate the real-time switching frequency and extract core features such as frequency deviation, fluctuation rate, and fluctuation amplitude.

[0033] Time correlation: Corresponding frequency fluctuation characteristics with electrical anomaly characteristics at the same time to clarify the time correlation.

[0034] Feature correlation: Analyze the frequency fluctuation types corresponding to different electrical anomalies and establish causal relationships.

[0035] Joint correlation of time features: Integrate time and feature correlation information to form switching frequency analysis data, and clarify the causes, timing and characteristics of frequency jitter.

[0036] The working principle and technical effect of the above technical solution are as follows: This method calculates the real-time operating frequency of the switching transistor based on the previously collected monitoring data, and extracts the core features of frequency fluctuation, including frequency deviation (the difference between the real-time frequency and the reference frequency), fluctuation rate (the speed of frequency change), fluctuation amplitude (the maximum range of frequency fluctuation), etc., to form frequency feature extraction information, comprehensively capturing the specific situation of frequency fluctuation; the extracted frequency feature extraction information is correlated with electrical feature anomaly analysis data in time, and the frequency fluctuation features at the same time point are correlated with electrical anomaly features to clarify the time synchronization of frequency fluctuation and electrical anomaly occurrence, determine whether electrical anomaly and frequency jitter occur simultaneously, and establish a time-level correlation. The relationship is as follows: Frequency feature extraction information is correlated with electrical anomaly analysis data to analyze the corresponding frequency fluctuations (such as slight fluctuations, severe fluctuations, and slow drifts) for different types of electrical anomalies (such as stable anomalies, random interference, and occasional anomalies). A causal relationship between electrical anomalies and frequency fluctuations is established to clarify the specific causes of frequency jitter. Time correlation information is fused with feature correlation information to form time feature correlation information. This information includes both the temporal synchronization relationship between frequency fluctuations and electrical anomalies, as well as their causal relationship, fully presenting the causes, occurrence time, and fluctuation characteristics of frequency jitter. This constitutes the switching frequency analysis data, ensuring that the adjustment mechanism can specifically address frequency jitter caused by different factors.

[0037] This method addresses the technical problem of traditional switching frequency analysis, which focuses solely on frequency fluctuations and fails to correlate them with the underlying causes of electrical anomalies. It achieves a deep correlation between frequency fluctuations and electrical anomalies, accurately pinpointing the core causes of frequency jitter. Through frequency feature extraction, it comprehensively captures the detailed characteristics of frequency fluctuations, avoiding misjudgments of fluctuation patterns caused by focusing solely on numerical frequency values. Through temporal and feature correlation, it clarifies the temporal synchronicity and causal relationship between frequency jitter and electrical anomalies, enabling precise differentiation of frequency fluctuation types caused by different electrical anomalies and avoiding blind adjustments. Furthermore, this embodiment enhances the depth and accuracy of switching frequency analysis, clearly presenting the causes, occurrence time, and fluctuation characteristics of frequency jitter. It reduces problems such as adjustment failures and inadequate compensation caused by insufficient frequency analysis, further optimizing the control effect of the overall jitter suppression method.

[0038] In one embodiment of the present invention, S2 includes: like Figure 3 As shown, the switching frequency change trend data is determined based on the switching frequency analysis data, and the switching frequency change data points are determined based on the switching frequency change trend data. Based on the switching frequency change data points, fluctuation analysis is performed to obtain fluctuation analysis data. Dynamic adjustment is performed based on the data of changes and fluctuations to obtain dynamic adjustment data; Fluctuation adjustment is performed based on dynamic adjustment data to obtain fluctuation adjustment data; Regulation disturbance analysis is performed based on fluctuation regulation data to obtain regulation disturbance analysis data.

[0039] Determine the trend and data points: Based on the frequency analysis data of S1, the frequency change trend is determined by the trend algorithm, and nodes with obvious frequency changes are extracted.

[0040] Fluctuation analysis: Analyze the amplitude, rate and duration of fluctuations, and classify the fluctuations (slight / moderate / severe).

[0041] Dynamic adjustment data generation: Based on the fluctuation level, differentiated strategies (PID fine-tuning, composite control, etc.) are formulated, and the specific adjustment parameters of the switching transistor drive signal are calculated to form dynamic adjustment data.

[0042] Fluctuation regulation: Adjust the switching frequency based on dynamic regulation data to obtain fluctuation regulation data.

[0043] Regulation interference analysis: Compare the theoretical effect of regulation with the actual effect, identify the type and characteristics of interference, and output regulation interference analysis data.

[0044] The working principle and technical effects of the above technical solution are as follows: This method, based on switching frequency analysis data, determines the changing trend of switching frequency (such as upward trend, downward trend, or fluctuation trend) through trend algorithms (e.g., linear trend analysis, moving average trend analysis). Simultaneously, it extracts nodes where the switching frequency changes significantly (i.e., time points where the frequency abruptly changes or the fluctuation amplitude increases significantly), clarifying the key positions and trend directions of frequency changes. It performs fluctuation analysis on the switching frequency change data points, focusing on analyzing the amplitude, rate, and duration of frequency fluctuations. The fluctuations are classified according to their severity (slight fluctuations, moderate fluctuations, severe fluctuations) to avoid under-regulation or over-regulation caused by using a uniform adjustment strategy. Based on the fluctuation classification results, a formula is developed... Differentiated dynamic adjustment strategies are employed, such as PID fine-tuning for slight fluctuations, composite control for moderate fluctuations, and rapid adjustment for severe fluctuations. Specific adjustment parameters of the switching transistor drive signal (e.g., on / off timing adjustment, drive voltage adjustment, etc.) are calculated to generate dynamic adjustment data. The switching frequency is adjusted based on this data, and fluctuation adjustment data is obtained, recording the frequency change after adjustment. The theoretical effect of the adjustment (the expected frequency change calculated based on the dynamic adjustment data) is compared with the actual effect (the actual frequency change after adjustment). Interferences present during the adjustment process are identified, and their types (e.g., electromagnetic interference, device temperature drift interference), characteristics, and degree of impact are analyzed, outputting adjustment interference analysis data.

[0045] This method addresses the technical problems of traditional dynamic adjustment methods, such as lack of differentiation, low adjustment accuracy, and inability to identify interference during the adjustment process. It achieves differentiated dynamic adjustment of switching frequency and accurate identification of adjustment interference. By analyzing frequency change trends and extracting change data points, it can accurately grasp the key nodes and trend directions of frequency changes. Through fluctuation grading and differentiated adjustment strategies, it avoids under- or over-adjustment caused by uniform adjustment, improving the accuracy and efficiency of dynamic adjustment and achieving initial suppression of frequency jitter. By comparing the theoretical and actual effects of adjustment, it can accurately identify interference during the adjustment process, clarify the type and degree of interference, and avoid adjustment failure caused by interference.

[0046] In one embodiment of the present invention, the step of performing fluctuation analysis based on switching frequency change data points to obtain fluctuation analysis data includes: Determine the temporal characteristics and data characteristics of frequency change based on the switching frequency change data points; The time characteristics of frequency change are compared with a preset time threshold of frequency change to obtain the time comparison result; The frequency change data characteristics are compared with a preset frequency change data threshold to obtain the data comparison results; Based on the time comparison results and data comparison results, the state of change and fluctuation is determined, and change and fluctuation analysis data is obtained.

[0047] Extract time features and data features; Temporal characteristics: How long does the frequency fluctuation last? Data characteristics: how much the frequency changed and how fast it changed; The fluctuation is compared with a time threshold to determine whether it is instantaneous, short-lived, or continuous.

[0048] The fluctuation was determined to be slight to moderately severe based on the comparison with the data threshold.

[0049] The combined determination of fluctuation status uses a combination of time magnitude and data magnitude to identify instantaneous disturbances, slow drifts, and severe fluctuations, ultimately outputting change fluctuation analysis data.

[0050] The working principle and technical effect of the above technical solution are as follows: This method extracts two types of core features from the switching frequency change data points: frequency change time features and frequency change data features. The time features mainly refer to the duration of frequency fluctuations (i.e., the length of time from the start to the end of the fluctuation), while the data features mainly refer to the amplitude of frequency changes (the difference between the real-time frequency and the reference frequency) and the rate of change (how fast the frequency changes). These two types of features together determine the severity and scope of the fluctuation. The extracted frequency change time features are compared with a preset time threshold. The time threshold is used to determine the time type of the fluctuation, such as instantaneous fluctuation (duration much shorter than the threshold), short-term fluctuation (duration close to the threshold), or continuous fluctuation. The process involves comparing the extracted frequency change data features with a preset data threshold to determine the fluctuation type, such as slight fluctuation (small amplitude and slow rate), moderate fluctuation (moderate amplitude and rate), and severe fluctuation (large amplitude and fast rate). Combining the time comparison results and data comparison results, the frequency change fluctuation state is jointly determined, ultimately classifying fluctuations into three categories: instantaneous interference (short duration and small amplitude), slow drift (long duration, small amplitude and slow rate), and severe fluctuation (long duration, large amplitude and fast rate). The output includes fluctuation analysis data containing fluctuation type, duration, amplitude, and rate.

[0051] This method addresses the technical problem of traditional fluctuation analysis, which can only determine fluctuation amplitude but cannot comprehensively identify fluctuation types and patterns, achieving accurate classification and comprehensive analysis of frequency fluctuations. By extracting time and data features, it comprehensively captures key fluctuation information, avoiding misjudgments caused by single-feature analysis. Through dual-threshold comparison and joint judgment, it can accurately distinguish between three different types of fluctuations: instantaneous interference, slow drift, and severe fluctuations, clarifying the severity and impact range of different fluctuations. This ensures that corresponding adjustment strategies are adopted for different types of fluctuations, avoiding under- or over-adjustment. Simultaneously, this embodiment improves the refinement of fluctuation analysis, accurately grasping the patterns and characteristics of fluctuations, reducing adjustment failures caused by misjudgments of fluctuation types, further improving the accuracy and efficiency of dynamic adjustment, and enhancing the ability of the charger's PFC stage to cope with different types of frequency fluctuations.

[0052] In one embodiment of the present invention, the step of performing dynamic analysis and adjustment based on fluctuation analysis data to obtain dynamic adjustment data includes: Based on the fluctuation analysis data, obtain the corresponding switching frequency analysis data, adjust the electrical characteristic anomaly analysis data of the switching frequency analysis data, and obtain the electrical characteristic adjustment data. The fluctuation analysis data is updated based on the electrical characteristic adjustment data to obtain the updated fluctuation data; Adjustment process data for acquiring change and fluctuation analysis data and change and fluctuation update data; The adjustment process data is compared with the preset adjustment process threshold to obtain adjustment process comparison data; The comparison data during the adjustment process is the dynamic adjustment data.

[0053] Based on the fluctuation analysis data, the electrical characteristic anomaly analysis is adjusted to classify the fluctuation level (slight / moderate / severe), and the detection threshold and adjustment strategy are adjusted accordingly.

[0054] Update the volatility analysis data by re-updating the volatility analysis results with adjusted feature data.

[0055] Acquire process data recordings such as adjustment amount, adjustment speed, and adjustment direction.

[0056] The adjustment is compared with the threshold of the adjustment process to determine whether the adjustment is reasonable or excessive.

[0057] The dynamic adjustment data is generated to obtain the specific adjustment parameters of the drive signal (such as duty cycle adjustment, trigger offset, etc.).

[0058] The working principle and technical effect of the above technical solution are as follows: This method, based on the fluctuation analysis data, reverse-correlates the corresponding switching frequency analysis data, and combines the electrical characteristic anomaly information in the switching frequency analysis data to perform targeted adjustments on the electrical characteristic anomaly analysis data. Specifically, according to the fluctuation level (slight / moderate / severe), the detection threshold and adjustment strategy of the electrical characteristics are adjusted accordingly. For example, during severe fluctuations, the detection threshold is appropriately relaxed and the adjustment sensitivity is enhanced; during slight fluctuations, the detection threshold is tightened and a mild adjustment strategy is adopted to obtain electrical characteristic adjustment data. Using the electrical characteristic adjustment data, the switching frequency change data points are re-analyzed, the fluctuation analysis data is updated, and the errors caused by unreasonable electrical characteristic detection thresholds are corrected. The system analyzes fluctuation deviations to obtain updated fluctuation data; it records key data during the electrical characteristic adjustment process, namely adjustment process data, including adjustment amount (adjustment amplitude of the drive signal), adjustment speed (adjustment rate of the drive signal), and adjustment direction (adjustment direction of the drive signal, such as increasing / decreasing the drive voltage, advancing / delaying the turn-on timing), comprehensively capturing the details of the adjustment process; it compares the adjustment process data with the preset adjustment process threshold to determine whether the adjustment amount is reasonable, whether the adjustment speed is too fast or too slow, and whether the adjustment direction is correct, avoiding over-adjustment or under-adjustment. The final output adjustment process comparison data is the dynamic adjustment data, which includes the specific adjustment parameters of the switching transistor drive signal.

[0059] This method addresses the technical problems of traditional dynamic adjustment strategies being fixed, unable to dynamically optimize based on fluctuations, and lacking rationality judgment for adjustment parameters. It achieves adaptive optimization of the dynamic adjustment strategy and precise control of adjustment parameters. By combining fluctuation level-based electrical characteristic anomaly analysis data, differentiated optimization of the adjustment strategy is achieved, ensuring the strategy matches the fluctuation type and improving the targeting of dynamic adjustment. Updating the fluctuation analysis data corrects fluctuation analysis biases, ensuring accuracy. Recording adjustment process data and comparing it with thresholds allows for timely detection of unreasonable aspects during adjustment (such as over-adjustment or excessively fast adjustment), preventing exacerbated frequency jitter due to improper adjustment and ensuring the rationality and effectiveness of dynamic adjustment. Simultaneously, it enhances the adaptive capability and accuracy of dynamic adjustment, enabling real-time optimization of the adjustment strategy and parameters based on fluctuations, reducing adjustment bias, and further improving the overall jitter suppression effect, ensuring the switching frequency quickly stabilizes.

[0060] In one embodiment of the present invention, the step of performing regulation interference analysis based on fluctuation regulation data to obtain regulation interference analysis data includes: Determine the characteristics of fluctuation regulation change and fluctuation regulation invariance based on fluctuation regulation data; Adjusting the fluctuation regulation characteristics to obtain disturbance regulation data; Obtain interference feedback data based on interference modulation data; The interference feedback data is compared with the preset interference feedback threshold to obtain the interference feedback comparison result; Based on the interference feedback comparison results, the interference characteristics of the fluctuation regulation change characteristics are determined, and regulation interference analysis data are obtained.

[0061] Determine the changing and constant characteristics of fluctuation regulation; Change characteristics: Whether the frequency changes as expected after adjustment; Invariant characteristics: whether the regulation is effective and whether it is subject to interference; Try adjusting the driving parameters to regulate the changing characteristics and observe whether the frequency responds.

[0062] Obtain interference feedback data to compare the theoretical adjustment effect with the actual frequency response.

[0063] The interference is compared with the interference feedback threshold to determine whether interference exists and its intensity.

[0064] The output is adjusted to analyze interference data to determine the type, magnitude, and presence of interference.

[0065] The working principle and technical effect of the above technical solution are as follows: This method avoids regulation failure caused by interference and ensures the effect of dynamic regulation. The specific process is as follows: From the fluctuation regulation data, distinguish between the changing characteristics and the invariant characteristics of the fluctuation regulation. The changing characteristics mainly refer to whether the switching frequency changes as expected after regulation (i.e., whether the regulation produces an effect), while the invariant characteristics mainly refer to whether the regulation is effective and whether it is affected by external or internal factors (i.e., the reason why the regulation effect did not meet expectations). Targeted adjustment attempts are made on the changing characteristics of the fluctuation regulation, i.e., adjusting the switching transistor drive parameters (such as changing the regulation amount or speed), observing the response of the switching frequency, obtaining interference regulation data, and recording the frequency changes during the adjustment attempts. The theoretical effect of the regulation (the expected frequency calculated based on the dynamic regulation data) is compared. The system compares the frequency change (rate change) with the actual frequency response (actual frequency change after adjustment attempts) to obtain interference feedback data, clarify the deviation between the adjustment effect and the expectation, and determine whether interference exists and its initial impact. It then compares the interference feedback data with a preset interference feedback threshold to determine the existence and intensity of interference (e.g., slight, moderate, severe interference). Based on the interference feedback comparison results, it performs interference characteristic determination on the fluctuation adjustment change characteristics, clarifying the type of interference (e.g., external electromagnetic interference, device temperature drift interference, input voltage fluctuation interference, etc.), interference amplitude, existence, and range of influence. Finally, it outputs adjustment interference analysis data.

[0066] This method solves the technical problems of traditional adjustment processes, such as the inability to identify interference and clearly define its characteristics. It achieves accurate identification and feature analysis of adjustment interference, avoiding adjustment failure and increased frequency jitter caused by interference. By distinguishing between the changing and constant characteristics of fluctuation adjustment, it can quickly determine whether the adjustment is effective and whether interference exists. Through adjustment attempts and interference feedback data collection, it can accurately capture the impact of interference on the adjustment effect and clarify the deviation between the adjustment effect and expectations. Through threshold comparison and interference feature determination, it can accurately identify the type, intensity, and scope of interference, avoiding blind interference investigation. Simultaneously, it improves the accuracy and efficiency of interference identification, enabling timely detection of interference during the adjustment process, preventing interference from continuously affecting the stability of the switching frequency, ensuring the effective guarantee of dynamic adjustment, further improving the reliability and anti-interference capability of the entire jitter suppression method, and enhancing the operational stability of the charger's PFC stage in complex interference environments.

[0067] In one embodiment of the present invention, S3 includes: like Figure 4 As shown, interference feature extraction is performed on the modulation interference analysis data to obtain interference feature extraction data; Interference feature compensation information is determined based on the interference feature extraction data; Parameter compensation adjustment is performed based on interference feature compensation information to obtain parameter compensation adjustment data; Interference signal cancellation is performed based on parameter compensation adjustment data to obtain interference signal cancellation data. The interference signal cancellation data is compared with a preset interference signal cancellation threshold to obtain the interference cancellation comparison result. Frequency adjustment is performed based on the interference cancellation comparison results until the interference signal cancellation data is greater than the preset interference signal cancellation threshold. The target switching frequency is then obtained, and closed-loop control is performed to obtain closed-loop control information.

[0068] Interference feature extraction extracts features such as interference type, amplitude, and frequency from the interference analysis data.

[0069] Determine compensation information, specifying the compensation method, amount, and timing.

[0070] The parameter compensation adjustment uses compensation parameters to adjust the drive signal to cancel out interference.

[0071] The frequency fluctuations before and after interference signal cancellation are compared to determine the cancellation effect.

[0072] The interference is compared with the cancellation threshold to determine whether it has been suppressed to an acceptable level.

[0073] Continue frequency adjustment (closed loop). If the threshold is not reached, continue adjustment; if it is reached, determine the target switching frequency.

[0074] The output closed-loop control information records stable control parameters, frequency convergence status, and system stability data.

[0075] The working principle and technical effects of the above technical solution are as follows: This method extracts interference features from the interference analysis data, focusing on extracting core features such as the type of interference (e.g., external electromagnetic interference, device temperature drift interference), amplitude (intensity of interference), and frequency (operating frequency of interference) to clarify the specific attributes of the interference; based on the extracted interference features, corresponding interference feature compensation information is determined, clarifying the compensation method (e.g., signal cancellation compensation, parameter adjustment compensation), compensation amount (compensation magnitude), and compensation timing (e.g., real-time compensation when interference occurs, periodic compensation), ensuring the pertinence and effectiveness of the compensation strategy; according to the interference feature compensation information, the relevant parameters of the switching transistor drive signal are compensated and adjusted to offset the influence of interference, obtaining parameter compensation adjustment data and recording the specific process of compensation adjustment; based on the parameter compensation adjustment data, the interference signal is specifically canceled, and the results before and after compensation are compared. The system monitors frequency fluctuations, acquires interference signal cancellation data, and assesses the effectiveness of interference cancellation. It compares this data with a preset interference signal cancellation threshold to determine if interference has been suppressed to an acceptable level (i.e., cancellation data greater than the threshold indicates effective suppression, while data less than the threshold indicates incomplete suppression). Based on the cancellation comparison results, continuous frequency adjustment is performed. If interference is not completely suppressed (cancellation data less than the threshold), compensation parameters are adjusted, and the compensation process is repeated until the interference signal cancellation data exceeds the preset threshold. At this point, a dynamically stable target switching frequency suitable for the current operating conditions is determined. Based on this, closed-loop control is initiated, monitoring frequency changes in real time. If frequency fluctuations occur, timely feedback and adjustments to compensation parameters and drive signals are made to maintain frequency stability. Finally, closed-loop control information is output, including stable control parameters, frequency convergence effect, and system stability data, completing the entire jitter suppression process.

[0076] This method addresses the technical problems of traditional interference compensation methods, such as weak targeting, poor compensation effect, and lack of closed-loop control leading to unstable frequency. It achieves precise interference cancellation and continuous stable control of the switching frequency. By extracting interference features, it accurately grasps the specific attributes of the interference, avoiding blind compensation. Through targeted compensation adjustment and interference signal cancellation, it effectively counteracts the effects of various interferences, solving the frequency jitter problem caused by interference and improving frequency stability. Through closed-loop control, it can monitor frequency changes in real time and adjust compensation parameters and drive signals in a timely manner, avoiding secondary frequency fluctuations and achieving continuous stability of the switching frequency, ensuring long-term stable operation of the charger's PFC stage. Furthermore, this embodiment further optimizes the control effect of the entire jitter suppression method, overcoming the limitations of traditional methods in balancing operating condition changes and interference effects. It achieves full-process, all-round suppression of frequency jitter, avoiding potential problems such as PFC instability and power factor decline, improving the charger's adaptability and reliability in complex operating conditions and strong interference environments, reducing losses of switching transistors due to frequency jitter, extending device lifespan, enhancing the operational stability and consistency of the entire charger system, and ensuring that the charger can achieve stable and efficient power conversion.

[0077] According to one embodiment of the present invention, the system includes: The monitoring and analysis module is used to monitor the data of the PFC-level switching transistors in the charger, obtain the switching transistor monitoring data, and perform switching frequency analysis based on the switching transistor monitoring data to obtain switching frequency analysis data. The interference analysis module is used to perform dynamic adjustment analysis based on the switching frequency analysis data to obtain dynamic adjustment data of the switching transistor drive signal, and to perform adjustment interference analysis based on the dynamic adjustment data to obtain adjustment interference analysis data. The jitter compensation analysis module is used to perform jitter compensation analysis based on the adjustment interference analysis data, obtain jitter compensation analysis data, obtain the target switching frequency based on the jitter compensation analysis data, perform closed-loop control, and obtain closed-loop control information.

[0078] The working principle and technical effects of the above-mentioned technical solution are as follows: This system comprehensively monitors the PFC-level switching transistors, collecting their electrical parameters, timing parameters, and environmental parameters. This allows for in-depth analysis of the switching frequency, clarifying frequency fluctuation characteristics and the correspondence between fluctuations and electrical anomalies, accurately capturing the initial state and underlying causes of frequency jitter. Based on the switching frequency analysis data, the system dynamically adjusts the switching transistor drive signal, determining the on / off timing and drive voltage adjustment parameters. Simultaneously, it identifies potential interference during adjustment, analyzing its characteristics and impact. For the identified adjustment interference, targeted jitter compensation analysis is performed, determining compensation parameters, timing, and methods. This yields a dynamically stable target switching frequency suitable for the current operating conditions. Through closed-loop control and continuous feedback and adjustment, the system ensures the switching frequency remains stable within the target range. The core causes of switching frequency jitter include four categories: input voltage fluctuations, load mutations, device temperature drift, and external electromagnetic interference. The entire control mechanism revolves around these four causes, achieving jitter suppression across all scenarios and processes.

[0079] This system effectively solves the technical challenges of traditional switching frequency jitter suppression methods, which are often limited in scope and lack specificity, failing to address dynamic changes in operating conditions and various interference effects. It overcomes the limitations of traditional methods, which can only suppress a single cause and have poor adaptability. Through a full-process control mechanism, it achieves comprehensive and all-round suppression of switching frequency jitter, fundamentally preventing safety hazards such as PFC circuit instability and power factor degradation caused by frequency jitter, thus ensuring the normal operation of the charger's PFC stage. Simultaneously, it effectively improves the charger's adaptability and operational reliability under complex operating conditions (such as input voltage fluctuations, load changes, high-temperature environments, and strong electromagnetic interference scenarios), reduces additional losses in the switching transistors caused by frequency jitter, extends the lifespan of the switching transistors and the entire charger system, enhances system stability and consistency, and ensures stable output from the charger in various operating scenarios, meeting the requirements for high efficiency and safety in power conversion.

[0080] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A method for suppressing switching frequency jitter in charger PFC control, characterized in that, The method includes: S1. Monitor the data of the PFC stage switching transistor of the charger, obtain the switching transistor monitoring data, and perform switching frequency analysis based on the switching transistor monitoring data to obtain switching frequency analysis data. S2. Perform dynamic adjustment analysis based on the switching frequency analysis data to obtain dynamic adjustment data of the switching transistor drive signal. Perform adjustment interference analysis based on the dynamic adjustment data to obtain adjustment interference analysis data. S3. Perform jitter compensation analysis based on the adjustment interference analysis data to obtain jitter compensation analysis data. Obtain the target switching frequency based on the jitter compensation analysis data and perform closed-loop control to obtain closed-loop control information.

2. The method for suppressing switching frequency jitter in charger PFC control according to claim 1, characterized in that, S1 includes: The switching status of the PFC stage switching transistor in the charger is collected to obtain switching status data. Multiple switch status data are sorted according to the acquisition timing information to obtain switch monitoring data; Based on the preset switching transistor acquisition frequency information, the corresponding switching transistor monitoring data is obtained and the electrical feature information is extracted to obtain the electrical feature monitoring dataset. Based on the electrical feature monitoring dataset, perform electrical feature anomaly analysis to obtain electrical feature anomaly analysis data; Switching frequency analysis data is obtained by performing switching frequency analysis based on electrical characteristic anomaly analysis data.

3. The method for suppressing switching frequency jitter in charger PFC control according to claim 2, characterized in that, The step of performing electrical feature anomaly analysis based on the electrical feature monitoring dataset to obtain electrical feature anomaly analysis data includes: Obtain time-series electrical characteristic data at different time-series nodes based on electrical characteristic monitoring data; Anomaly data extraction is performed on time-series electrical characteristic data to obtain time-series anomaly characteristic data; Obtain the time interval data of adjacent time series anomaly feature data to obtain anomaly feature time interval data; The abnormal feature interval time data is compared with the preset abnormal feature interval time threshold to obtain the abnormal feature interval comparison result; Electrical characteristic status is determined based on the comparison results of abnormal characteristic intervals, and electrical characteristic anomaly analysis data is obtained.

4. The method for suppressing switching frequency jitter in charger PFC control according to claim 2, characterized in that, The step of performing switching frequency analysis based on electrical characteristic anomaly analysis data to obtain switching frequency analysis data includes: Obtain switching frequency information, extract frequency features from the switching frequency information, and obtain frequency feature extraction information; By temporally correlating frequency feature extraction information with electrical feature anomaly analysis data, temporal correlation information is obtained. By correlating frequency feature extraction information with electrical feature anomaly analysis data, feature correlation information is obtained. By associating time-related information with feature-related information, time-feature-related information is obtained; The time feature correlation information is the switching frequency analysis data.

5. The method for suppressing switching frequency jitter in charger PFC control according to claim 1, characterized in that, S2 includes: Based on the switching frequency analysis data, determine the switching frequency change trend data, and based on the switching frequency change trend data, determine the switching frequency change data points; Based on the switching frequency change data points, fluctuation analysis is performed to obtain fluctuation analysis data. Dynamic adjustment is performed based on the data of changes and fluctuations to obtain dynamic adjustment data; Fluctuation adjustment is performed based on dynamic adjustment data to obtain fluctuation adjustment data; Regulation disturbance analysis is performed based on fluctuation regulation data to obtain regulation disturbance analysis data.

6. The method for suppressing switching frequency jitter in charger PFC control according to claim 5, characterized in that, The step of performing fluctuation analysis based on switching frequency change data points to obtain fluctuation analysis data includes: Determine the temporal characteristics and data characteristics of frequency change based on the switching frequency change data points; The time characteristics of frequency change are compared with a preset time threshold of frequency change to obtain the time comparison result; The frequency change data characteristics are compared with a preset frequency change data threshold to obtain the data comparison results; Based on the time comparison results and data comparison results, the state of change and fluctuation is determined, and change and fluctuation analysis data is obtained.

7. The method for suppressing switching frequency jitter in charger PFC control according to claim 5, characterized in that, The process of dynamically analyzing and adjusting based on fluctuation analysis data to obtain dynamic adjustment data includes: Based on the fluctuation analysis data, obtain the corresponding switching frequency analysis data, adjust the electrical characteristic anomaly analysis data of the switching frequency analysis data, and obtain the electrical characteristic adjustment data. The fluctuation analysis data is updated based on the electrical characteristic adjustment data to obtain the updated fluctuation data; Adjustment process data for acquiring change and fluctuation analysis data and change and fluctuation update data; The adjustment process data is compared with the preset adjustment process threshold to obtain adjustment process comparison data; The comparison data during the adjustment process is the dynamic adjustment data.

8. The method for suppressing switching frequency jitter in charger PFC control according to claim 5, characterized in that, The step of performing regulation disturbance analysis based on fluctuation regulation data to obtain regulation disturbance analysis data includes: Determine the characteristics of fluctuation regulation change and fluctuation regulation invariance based on fluctuation regulation data; Adjusting the fluctuation regulation characteristics to obtain disturbance regulation data; Obtain interference feedback data based on interference modulation data; The interference feedback data is compared with the preset interference feedback threshold to obtain the interference feedback comparison result; Based on the interference feedback comparison results, the interference characteristics of the fluctuation regulation change characteristics are determined, and regulation interference analysis data are obtained.

9. The method for suppressing switching frequency jitter in charger PFC control according to claim 1, characterized in that, S3 includes: Interference features are extracted from the modulation interference analysis data to obtain interference feature extraction data; Interference feature compensation information is determined based on the interference feature extraction data; Parameter compensation adjustment is performed based on interference feature compensation information to obtain parameter compensation adjustment data; Interference signal cancellation is performed based on parameter compensation adjustment data to obtain interference signal cancellation data. The interference signal cancellation data is compared with a preset interference signal cancellation threshold to obtain the interference cancellation comparison result. Frequency adjustment is performed based on the interference cancellation comparison results until the interference signal cancellation data is greater than the preset interference signal cancellation threshold. The target switching frequency is then obtained, and closed-loop control is performed to obtain closed-loop control information.

10. A system for implementing a switching frequency jitter suppression method for PFC control of a charger as described in claim 1, characterized in that, The system includes: The monitoring and analysis module is used to monitor the data of the PFC-level switching transistors in the charger, obtain the switching transistor monitoring data, and perform switching frequency analysis based on the switching transistor monitoring data to obtain switching frequency analysis data. The interference analysis module is used to perform dynamic adjustment analysis based on the switching frequency analysis data to obtain dynamic adjustment data of the switching transistor drive signal, and to perform adjustment interference analysis based on the dynamic adjustment data to obtain adjustment interference analysis data. The jitter compensation analysis module is used to perform jitter compensation analysis based on the adjustment interference analysis data, obtain jitter compensation analysis data, obtain the target switching frequency based on the jitter compensation analysis data, perform closed-loop control, and obtain closed-loop control information.

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