AC / DC power supply based on magnetic integration

Abstract

The invention relates to the technical field of power electronics, in particular to an alternating current and direct current power supply based on magnetic integration, which comprises a compensation parameter calculation module, a power output management module, a starting parameter configuration module, a temperature management control module, an abnormity monitoring and overload protection module and a performance evaluation and maintenance management module. According to the invention, through real-time monitoring and adjustment of power supply output, optimization of accuracy and adaptability of power supply, improvement of power supply response speed and efficiency, and through real-time monitoring of the temperature of the power supply assembly and adjustment of the cooling equipment, risks caused by overheating of the equipment are effectively reduced, and stability and reliability of the power supply are improved. Abnormality monitoring and overload protection are carried out through real-time data analysis, power abnormality is identified, overload and short circuit problems are responded, the equipment failure rate and maintenance cost are reduced, data support is provided for a maintenance plan in combination with prediction of a performance degradation trend, and the efficiency and stability of long-term operation are guaranteed.

Description

Technical Field

[0001] The present invention relates to the field of power electronics technology, and in particular to an AC-DC power supply based on magnetic integration. Background Art

[0002] Power electronics technology focuses on the efficient conversion and control of electrical energy, and is applied to various devices such as frequency converters, inverters, rectifiers, and power controllers. By adjusting the frequency, amplitude, and phase of the current, it adapts to various application requirements, aiming to improve energy efficiency, reduce energy losses, and enhance the overall performance and reliability of the system. By utilizing various algorithms and control strategies, it optimizes the efficiency and responsiveness of power conversion, and is applied to multiple aspects of smart grids, battery management systems for electric vehicles, and renewable energy integration, supporting complex power management and optimization tasks.

[0003] Among them, the AC-DC power supply aims to provide a power supply system that can output both AC and DC. By integrating various magnetic components such as transformers and inductors through magnetic integration technology, it improves energy efficiency and power density and reduces the volume of the device. It is applied to various occasions that require the simultaneous use of AC and DC power sources, including smart home systems, medical devices, and industrial automation systems in various environments. Combined with supporting highly automated and system-level power management strategies, it ensures the high efficiency and reliability of the power supply, and supports the efficient and stable operation of various electronic devices.

[0004] Traditional AC-DC power supply technology lacks the ability to monitor the global performance of the power supply system in real time and adaptively adjust it. It does not respond quickly enough when the power load suddenly changes, resulting in system instability and failures. It lacks active intervention in power temperature management, causing the device to operate at non-ideal working temperatures, affecting efficiency and lifespan. It is usually not accurate enough in predicting power performance degradation and maintenance requirements, leading to premature or late maintenance, increasing operating costs, and falling short in the face of growing demands, making it difficult to meet the requirements of modern power applications for high efficiency and high reliability. Summary of the Invention

[0005] The purpose of the present invention is to solve the deficiencies existing in the prior art, and to propose an AC-DC power supply based on magnetic integration.

[0006] To achieve the above purpose, the present invention adopts the following technical solutions. An AC-DC power supply based on magnetic integration includes:

[0007] The compensation parameter calculation module, based on the output power demand data, executes the power output parameters input by the user, compares them with the actual output of the power supply, identifies the differences and calculates the required compensation parameters, and generates an output parameter adjustment record;

[0008] The power output management module analyzes the output parameter adjustment records, predicts the power demand changes according to the actual application scenarios, adjusts and optimizes the power output, and generates power management effect information;

[0009] The startup parameter configuration module adjusts the output parameters at power startup based on the power management effect information, optimizes the stability of power startup by smoothly increasing the voltage slope, and generates a soft startup control record;

[0010] The temperature management control module based on the soft startup control record, monitors the temperature data of multiple power components in real time, adjusts the output parameters of the cooling equipment, and generates power thermal management parameters;

[0011] The anomaly monitoring and overload protection module based on the power thermal management parameters, combines the real-time voltage and current output data of the power supply, identifies overload and short circuits, adjusts the switch state of the power supply, and generates an anomaly event handling log;

[0012] The performance evaluation and maintenance management module based on the anomaly event handling log, evaluates the reliability of the power supply by performing time series analysis on the operation data of the power supply, predicts the performance degradation trend, adjusts the maintenance time list, and generates a power supply maintenance record.

[0013] As a further solution of the present invention, the output parameter adjustment record includes user input parameters, actual output monitoring data, and difference compensation parameters. The power management effect information includes the prediction result of power demand changes, the optimization record of output voltage and current, and the performance evaluation score. The soft startup control record includes the adjustment data of the startup voltage slope, the time series of smooth startup, and the stability index during startup. The power thermal management parameters include real-time temperature data, the adjusted output settings of the cooling equipment for the overheat risk assessment result. The anomaly event handling log includes marked power anomaly fluctuations, identified overload and short circuit events, and the power switch adjustment status. The power supply maintenance record includes the analysis result of the operation data of the power supply, the predicted performance degradation trend information, and the maintenance time list.

[0014] As a further solution of the present invention, the compensation parameter calculation module includes:

[0015] The input processing sub-module adjusts the power output based on the output power demand data and according to various power output parameters input by the user, including voltage, current, and frequency, and generates an input data record;

[0016] The difference analysis sub-module based on the input data record, monitors the actual output of the power supply in real time, compares it with the preset parameters, identifies the output differences in voltage, current, and frequency, and generates a difference identification result;

[0017] Based on the difference recognition result, the parameter calculation sub-module calculates the compensation parameters required by the power supply, adjusts the output voltage, current, and frequency, and generates an output parameter adjustment record.

[0018] As a further solution of the present invention, the power supply output management module includes:

[0019] The scenario analysis sub-module analyzes the output parameter adjustment record, combines the actual application scenario, and predicts the demand change of the power supply output through time series analysis of the power supply output parameters, and generates a demand prediction result;

[0020] The output adjustment sub-module adjusts the power supply output settings based on the demand prediction result, optimizes the voltage, current, and frequency to match the predicted demand, optimizes the stability of the power supply output, and generates a power supply output optimization record;

[0021] The effect evaluation sub-module analyzes the operation efficiency and stability of the power supply according to the power supply output optimization record, evaluates the effectiveness of the adjusted output settings, and generates power supply management effect information.

[0022] As a further solution of the present invention, the startup parameter configuration module includes:

[0023] The startup voltage adjustment sub-module sets the output voltage when the power supply starts according to the output demand based on the power supply management effect information, and generates power supply startup parameters;

[0024] The startup slope adjustment sub-module optimizes the stability of the power supply startup process by smoothly increasing the slope of the startup voltage based on the power supply startup parameters, and generates a slope adjustment result;

[0025] The startup process recording sub-module records the power supply startup process based on the slope adjustment result, including the real-time voltage, current, and frequency data at multiple time points during the startup process, evaluates the stability of the power supply startup, and generates a soft startup control record.

[0026] As a further solution of the present invention, the temperature management control module includes:

[0027] The real-time temperature monitoring sub-module uses a temperature sensor to collect the temperature data of multiple components inside the power supply in real time based on the soft startup control record, and generates real-time temperature monitoring data;

[0028] The power supply overheat identification sub-module calculates the change trend of the temperature data based on the real-time temperature monitoring data, identifies the power supply overheat risk, and generates an overheat risk analysis result;

[0029] The cooling demand analysis sub-module evaluates the cooling demand according to the temperature data based on the overheat risk analysis result, and adjusts the output parameters of the cooling equipment, including the rotation speed of the cooling fan, and generates power supply thermal management parameters.

[0030] As a further solution of the present invention, the specific formula for calculating the change trend of the temperature data is:

[0031]

[0032] wherein, T t represents the predicted temperature value at time t, c is a constant term, φ i is the autoregressive coefficient, i represents the time unit counted forward from the current time point t, and the influence of the temperature values T t-i of these historical time points on the current prediction, θ j is the moving average coefficient, j represents the error time unit counted forward from the current time point t, and describes the influence of the historical prediction error ∈ t-j on the current prediction, ∈ t is the current prediction error, p represents the order of autoregression, that is, including T t-1 to T t-p of the historical temperature values, q represents the order of moving average, that is, including ∈ t-1 to ∈ t-q of the historical prediction errors.

[0033] As a further solution of the present invention, the anomaly monitoring and overload protection module includes:

[0034] The safety threshold comparison sub-module compares the real-time voltage and current output data with the set safety threshold based on the power thermal management parameters, identifies the power data exceeding the safety threshold, and generates a power parameter comparison result;

[0035] The power anomaly analysis sub-module identifies and records abnormal power fluctuations based on the power parameter comparison result, evaluates the causes of anomalies, including overload and short circuit, and generates an abnormal cause identification result;

[0036] The short circuit and overload response sub-module adjusts the switch state of the power supply according to the abnormal cause identification result and generates an abnormal event handling log according to the identified abnormal cause.

[0037] As a further solution of the present invention, the performance evaluation and maintenance management module includes:

[0038] The time series analysis sub-module performs time series analysis on the power supply operation data based on the abnormal event handling log, including the temperature data and the deviation values of the output voltage and current, and generates an operation data analysis result;

[0039] The performance degradation analysis sub-module evaluates the reliability of the power supply based on the operation data analysis result, calculates the degradation trend of the power supply performance, and generates performance prediction information;

[0040] The power supply maintenance management sub-module adjusts the maintenance time list of the power supply according to the performance prediction information, optimizes the stability of the power supply operation, and generates a power supply maintenance record.

[0041] As a further solution of the present invention, the specific formula for calculating the degradation trend of the power supply performance is:

[0042]

[0043] Where P t represents the predicted output at time point t, x t-i+1 represents the power output data at the i-th time point forward from the current time t, w i is the weight coefficient at the i-th time point, n is the total number of time periods considered, i is the time point index within the current period, t is the time point of the current analysis, representing the predicted moment.

[0044] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0045] In the present invention, by real-time monitoring and adjusting the power output, the accuracy and adaptability of power supply are optimized, the power supply response speed and efficiency are improved. By real-time monitoring the temperature of power supply components and adjusting the cooling equipment, the risk caused by equipment overheating is effectively reduced, and the stability and reliability of the power supply are improved. By real-time data analysis for abnormal monitoring and overload protection, power anomalies are identified and overload and short-circuit problems are responded to, reducing equipment failure rate and maintenance costs. Combining with the prediction of performance degradation trend, data support is provided for the maintenance plan, ensuring the efficiency and stability of long-term operation. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Figure 1 is the power supply flow chart of the present invention;

[0047] Figure 2 is the schematic diagram of the power supply framework of the present invention;

[0048] Figure 3 is the flow chart of the compensation parameter calculation module of the present invention;

[0049] Figure 4 is the flow chart of the power output management module of the present invention;

[0050] Figure 5 is the flow chart of the start parameter configuration module of the present invention;

[0051] Figure 6 is the flow chart of the temperature management control module of the present invention;

[0052] Figure 7 is the flow chart of the abnormal monitoring and overload protection module of the present invention;

[0053] Figure 8 This is the flowchart of the performance evaluation and maintenance management module of the present invention. Specific implementation manners

[0054] In order to make the objectives, technical solutions and advantages of the present invention clearer and more understandable, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0055] In the description of the present invention, it should be understood that the orientation or positional relationships indicated by the terms "length", "width", "upper", "lower", "front", "rear", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", etc. are based on the orientation or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and thus should not be construed as limiting the present invention. In addition, in the description of the present invention, "a plurality of" means two or more unless otherwise specifically defined.

[0056] Please refer to Figures 1 to 2 , an AC-DC power supply based on magnetic integration includes:

[0057] The compensation parameter calculation module executes the power output parameters input by the user based on the output power demand data, compares them with the actual output of the power supply, identifies the differences and calculates the required compensation parameters, and generates an output parameter adjustment record;

[0058] The power output management module analyzes the output parameter adjustment record, predicts the change in power demand according to the actual application scenario, adjusts and optimizes the power output, and generates power management effect information;

[0059] The startup parameter configuration module adjusts the output parameters when the power supply starts based on the power management effect information, optimizes the startup stability of the power supply by smoothly increasing the voltage slope, and generates a soft startup control record;

[0060] The temperature management control module based on the soft startup control record, monitors the temperature data of multiple power supply components in real time, adjusts the output parameters of the cooling device, and generates power supply thermal management parameters;

[0061] The abnormal monitoring and overload protection module based on the power supply thermal management parameters, combined with the real-time voltage and current output data of the power supply, identifies overload and short circuit, adjusts the switch state of the power supply, and generates an abnormal event handling log;

[0062] The performance evaluation and maintenance management module evaluates the reliability of the power supply, predicts the performance degradation trend, adjusts the maintenance time list, and generates the power supply maintenance record by performing time series analysis on the operation data of the power supply based on the exception event handling log.

[0063] The output parameter adjustment record includes user input parameters, actual output monitoring data, and differential compensation parameters. The power management effect information includes the predicted result of power demand change, the optimization record of output voltage and current, and the performance evaluation score. The soft start control record includes the adjustment data of the start voltage slope, the time series of smooth start, and the stability index during the start process. The power thermal management parameters include real-time temperature data, the adjusted output setting of the cooling device after overheat risk assessment. The exception event handling log includes marked power abnormal fluctuations, identified overload and short circuit events, and the power switch adjustment status. The power supply maintenance record includes the analysis result of the power supply operation data, the predicted performance degradation trend information, and the maintenance time list.

[0064] Please refer to Figure 2 and Figure 3 , the compensation parameter calculation module includes:

[0065] The input processing sub-module adjusts the power output based on the output power demand data according to various power output parameters input by the user, including voltage, current, and frequency, and generates an input data record.

[0066] In the input processing sub-module, based on the output power demand data, the power output is optimized through various power output parameters provided by the user. The target parameters include voltage, current, and frequency. The process includes reading and real-time adjustment of each power parameter to ensure that the power output reaches the expected accuracy and efficiency. By real-time monitoring of the voltage, current, and frequency parameters, the output is automatically adjusted according to the change of the actual load to meet the needs of different devices and scenarios. The generated input data record reflects the parameter values, adjustment time, and adjustment results of each adjustment. The technologies used in the process include analog signal processing and digital signal processing technologies. The target technology ensures the accurate transmission and real-time update of data. The output input data record provides accurate real-time data support for the subsequent modules.

[0067] The differential analysis sub-module monitors the actual output of the power supply in real time based on the input data record, compares it with the preset parameters, identifies the output differences of voltage, current, and frequency, and generates a differential identification result.

[0068] In the difference analysis sub-module, the actual output data of the power supply, including voltage, current, and frequency, is extracted from the input data records. Real-time data processing algorithms are used to compare the actual output with the preset output parameters to identify any deviations or abnormalities. The comparison algorithms employed include the least squares method and deviation variance analysis. The specific values and types of parameter deviations are located. The results of difference identification will record the differences between the preset values and the actual values of each parameter, including the magnitude of the difference, the scope of influence, and cause analysis. The target results are crucial for the optimization of the power management system to ensure the stable operation and efficient output of the power supply.

[0069] Based on the results of difference identification, the parameter calculation sub-module calculates the compensation parameters required by the power supply, adjusts the output voltage, current, and frequency, and generates an output parameter adjustment record.

[0070] In the above content, based on the results of difference identification, the compensation parameters required by the power supply are calculated, and the output voltage, current, and frequency are adjusted. The calculation is performed according to the formula to generate an output parameter adjustment record.

[0071] where V t is the target voltage value, the preset ideal output voltage of the power supply, V a is the actual voltage value, the voltage actually output by the power supply during actual operation, I t is the target current value, the preset ideal output current of the power supply, I a is the actual current value, the current actually output by the power supply during actual operation, F t is the target frequency value, the preset ideal output frequency of the power supply, F a is the actual frequency value, the frequency actually output by the power supply during actual operation, P v is the calculated voltage compensation parameter, representing the adjustment amount required to reach the target voltage, P i is the calculated current compensation parameter, representing the adjustment amount required to reach the target current, P f is the calculated frequency compensation parameter, representing the adjustment amount required to reach the target frequency;

[0072] Detailed explanation of the formula and the derivation process of formula calculation:

[0073] Assume the target voltage V t is 230V, the actual voltage V a is 220V, the target current I t is 5A, the actual current I a is 4.5A, the target frequency F t is 60Hz, and the actual frequency F a is 58Hz;

[0074] Calculate voltage compensation P v :

[0075]

[0076] Calculate current compensation P i :

[0077]

[0078] Calculate frequency compensation P f :

[0079]

[0080] Result P v = 10.35V, P i = 0.555A, P f = 2.07Hz shows the voltage, current, and frequency compensation amounts required to achieve the target output, ensuring that the power supply output matches the preset parameters.

[0081] Please refer to Figure 2 and Figure 4 The power supply output management module includes:

[0082] The scenario analysis sub-module analyzes the output parameter adjustment records, combines the actual application scenario, predicts the demand changes of the power supply output through time series analysis of the power supply output parameters, and generates a demand prediction result;

[0083] In the scenario analysis sub-module, autoregressive integrated moving average model and exponential smoothing method, which are time series analysis techniques, are used to analyze the power supply output parameter adjustment records, extract trend and periodic factors from them, predict future power supply demand changes. Time series analysis is based on past data to estimate the demand fluctuations of the power supply output in the future. During the analysis and processing, the system cleans the data, excludes outliers, performs model fitting and prediction. The generated demand prediction result provides a scientific basis for subsequent power supply output adjustment, ensuring that the power management system can adjust its output predictively to match the demand changes.

[0084] The output adjustment sub-module adjusts the power supply output settings based on the demand prediction result, optimizes the voltage, current, and frequency to match the predicted demand, optimizes the stability of the power supply output, and generates a power supply output optimization record;

[0085] In the output adjustment sub-module, based on the demand prediction results, a PID controller in control theory is applied to adjust the voltage, current, and frequency of the power supply output. The PID controller dynamically adjusts the output parameters according to the changes in the predicted demand, optimizing the response speed and accuracy of the power supply output. By continuously monitoring the power supply output and comparing it with the predicted demand, the controller automatically adjusts the output settings to match the predicted load demand, including setting control parameters such as gain, integral time, and derivative time, and adjusting the target parameters to ensure the optimization and stability of the power supply output. The generated power supply output optimization record describes the parameters adjusted each time, the output values before and after the adjustment, and the time points of the adjustment, providing a detailed operation record for power management.

[0086] The effect evaluation sub-module analyzes the operation efficiency and stability of the power supply based on the power supply output optimization record, evaluates the effectiveness of the adjusted output settings, and generates power management effect information.

[0087] In the effect evaluation sub-module, by analyzing the power supply output optimization record and using data analysis and statistical methods, including regression analysis and variance analysis, the effect after the adjustment of the power supply output settings is evaluated, and the operation efficiency and stability of the power supply are identified. During the process, by calculating the efficiency change before and after the adjustment, the improvement in stability is evaluated, including analyzing the data in the optimization record and comparing the voltage, current, and frequency stability before and after the adjustment. The significance of the effect is confirmed through statistical tests. The generated power management effect information includes the percentage of efficiency improvement, the specific values of stability improvement, and the impact on the overall system performance. The target information is crucial for further optimizing the power supply output configuration.

[0088] Please refer to Figure 2 and Figure 5 , the startup parameter configuration module includes:

[0089] The startup voltage adjustment sub-module sets the output voltage at startup of the power supply based on the power management effect information and according to the output demand, generating power supply startup parameters.

[0090] In the startup voltage adjustment sub-module, the startup voltage is set according to the power management effect information to ensure that the voltage at startup of the power supply matches the output demand. The PID control algorithm of voltage control technology is used to adjust the startup voltage to an appropriate initial value, optimizing the performance and response speed at startup of the power supply. The voltage setting is determined based on historical data and preset performance indicators to ensure the optimal startup performance of the power supply under different operating conditions. The generated power supply startup parameters include the initial voltage value, the power demand of the target device, and the expected environmental conditions. The target parameters are recorded and used for subsequent startup slope adjustment, providing basic data for the stable operation of the power supply system.

[0091] The startup slope adjustment sub-module optimizes the stability of the power supply startup process by smoothly increasing the slope of the startup voltage based on the power supply startup parameters, and generates a slope adjustment result;

[0092] In the startup slope adjustment sub-module, the startup process of the power supply is optimized by controlling the gradual increase of the voltage slope to ensure the smoothness of the entire startup stage. Through slope control and linear incremental adjustment, it helps to smooth out the voltage mutation during the power supply startup process and reduce the power impact during startup, including setting the starting voltage, calculating the ideal voltage increase rate, and gradually applying the slope until the operating voltage is reached. The slope adjustment result records each step change from the initial voltage to the operating voltage, including the voltage value and time mark of each stage, providing data support for the power supply startup process.

[0093] The startup process recording sub-module records the power supply startup process based on the slope adjustment result, including the real-time voltage, current, and frequency data at multiple time points during the startup process, evaluates the stability of the power supply startup, and generates a soft startup control record;

[0094] In the startup process recording sub-module, key data during the power supply startup process is recorded, including the real-time voltage, current, and frequency at different time points. Through measurement techniques and data recording techniques, such as real-time monitoring systems and data logs, all key parameters during the power supply startup process are monitored and recorded. The target data is used to evaluate the stability of the power supply startup, ensure a smooth transition of the power supply from startup to normal operation. The generated soft startup control record shows the voltage and current changes as well as the frequency adjustment situation in each stage during the startup process, providing a comprehensive evaluation of the startup process stability. The target record provides an important basis for optimizing the power supply startup strategy and improving the device design.

[0095] Please refer to Figure 2 and Figure 6 , the temperature management control module includes:

[0096] The real-time temperature monitoring sub-module, based on the soft startup control record, uses temperature sensors to collect the temperature data of multiple components inside the power supply in real time, and generates real-time temperature monitoring data;

[0097] In the real-time temperature monitoring sub-module, the temperature data of key components is collected in real time through multiple temperature sensors installed inside the power supply. Thermocouples and thermistors are used as temperature sensing devices to provide temperature measurement data. Through the data acquisition system, the real-time temperature monitoring data is continuously recorded and sent to the central monitoring system through wireless transmission technology. The monitoring data includes the position information, time stamp, and measured temperature value of each sensor. The target data is used to track the thermal state inside the power supply, detect abnormal temperature rises in a timely manner, and provide a real-time and reliable data basis for overheat risk analysis.

[0098] Based on the real-time temperature monitoring data, the power supply overheat identification sub-module calculates the change trend of the temperature data, identifies the power supply overheat risk, and generates the overheat risk analysis result;

[0099] The specific formula for calculating the change trend of the temperature data is:

[0100]

[0101] Where, T t represents the predicted temperature value at time t, c is the constant term, φ i is the autoregressive coefficient, i represents the time unit counted forward from the current time point t, and the influence of the temperature values T t-i at these historical time points on the current prediction, θ j is the moving average coefficient, j represents the error time unit counted forward from the current time point t, and describes the influence of the historical prediction error ∈ t-j on the current prediction, ∈ t is the current prediction error, p represents the order of autoregression, that is, including T t-1 to T t-p of the historical temperature values, q represents the order of moving average, that is, including ∈ t-1 to ∈ t-q of the historical prediction errors.

[0102] Formula:

[0103]

[0104] Detailed explanation of the formula and the derivation process of the formula calculation:

[0105] The formula is used to calculate the temperature prediction value of time, and the result is used to judge whether the device has an overheat risk and whether cooling measures need to be taken.

[0106] Parameter meanings and setting values:

[0107] c is the constant term of the model, which is used to provide the baseline temperature level and is assumed to be 20°C;

[0108] φ i is the autoregressive coefficient, which reflects the influence of the historical temperature data T t-i on the current temperature prediction, and is assumed to be φ 1 = 0.5, T t-1 = 22°C;

[0109] θ j is the moving average coefficient, which represents the influence of the historical prediction error ∈ t-j on the current prediction, and is assumed to be θ 1 = 0.3, ∈ t-1 = 0.2°C

[0110] ∈ t is the random error term, and according to system monitoring, the error range is usually set to ±0.5°C;

[0111] Substitute the parameters into the formula for calculation:

[0112] T t = 20 + 0.5×22 + 0.3×0.2 + 0.5 = 31.06

[0113] The result T t = 31.06 indicates that based on historical data and error estimation, the temperature at the target time point is expected to be 31.06°C. The prediction result is used for analysis and decision-making on whether to take cooling measures to avoid damage to the equipment caused by overheating.

[0114] The cooling demand analysis sub-module, based on the overheating risk analysis result, evaluates the cooling demand according to the temperature data, adjusts the output parameters of the cooling equipment, including the rotation speed of the cooling fan, and generates power thermal management parameters;

[0115] In the cooling demand analysis sub-module, according to the overheating risk analysis result, the necessary cooling demand is evaluated, the parameters of the cooling equipment are adjusted to meet the current thermal management requirements, the PID control algorithm is adopted to adjust the rotation speed of the cooling fan to achieve an ideal cooling effect. The cooling demand analysis involves the evaluation of temperature data, the setting of the performance parameters of the cooling fan, and the real-time adjustment of the fan rotation speed. The generated power thermal management parameter record lists the required heat dissipation measures, the adjusted specific parameters, the expected and actual cooling effects, ensuring that the power system is maintained within the safe temperature range under any operating conditions.

[0116] Please refer to Figure 2 and Figure 7 , the abnormal monitoring and overload protection module includes:

[0117] The safety threshold comparison sub-module, based on the power thermal management parameters, compares the real-time voltage and current output data with the set safety threshold, identifies the power data exceeding the safety threshold, and generates the power parameter comparison result;

[0118] In the safety threshold comparison sub-module, using the embedded system and power monitoring technology, the real-time voltage and current output data are compared with the set safety threshold. The applied technologies include real-time monitoring and data comparison analysis, and the threshold alarm system. Through the regularly updated safety threshold, the module monitors the power output data in real time to ensure that the output data does not exceed the predetermined safety limit. If the power data exceeds the safety threshold, the system automatically records the event and triggers the corresponding safety warning. The generated power parameter comparison result includes the voltage and current values for each monitoring, the specific time and duration of the over-threshold event. The target monitoring data is crucial for maintaining the safe operation of the power system.

[0119] Based on the comparison results of power parameters, the power anomaly analysis sub-module identifies and records abnormal power fluctuations, evaluates the causes of anomalies, including overload and short circuit, and generates the identification results of the causes of anomalies.

[0120] In the power anomaly analysis sub-module, based on the comparison results of power parameters, fault diagnosis techniques such as fault tree analysis and sequence event analysis are used to identify and record abnormal power fluctuations, analyze the fluctuation patterns of abnormal power data, evaluate the causes of anomalies, including power overload, short circuit, and system faults. The identification results of the causes of anomalies include descriptions of each power anomaly event, such as the type of anomaly, the power components affected, the time of occurrence of the anomaly, and the possible causes, which are used to ensure the stability and security of the system.

[0121] The short circuit and overload response sub-module adjusts the switch state of the power supply according to the identification results of the causes of anomalies and generates a log of abnormal event handling.

[0122] In the short circuit and overload response sub-module, according to the identification results of the causes of anomalies, an automated control system and a power management strategy are adopted to adjust the switch state of the power supply to prevent the deterioration of abnormal situations. Technologies such as intelligent circuit breakers and automatic load transfer systems are used. The target system can respond quickly, automatically cut off and transfer the load to prevent serious damage to the power system. The log of abnormal event handling records the operation details of each response, including the response time, response measures, and the evaluation of the effect of the measures. The target log provides important historical data for the power system to optimize future response strategies and improve the overall response ability of the system.

[0123] Please refer to Figure 2 and Figure 8 , the performance evaluation and maintenance management module includes:

[0124] The time series analysis sub-module performs time series analysis on the power supply operation data based on the log of abnormal event handling, including temperature data and the deviation values of output voltage and current, and generates the operation data analysis results.

[0125] In the time series analysis sub-module, based on the log of abnormal event handling, time series analysis techniques are used to analyze the power supply operation data. The data involved includes temperature, output voltage, and the deviation value of current. The autoregressive integrated moving average model and the fast Fourier transform are adopted to identify the long-term trends and periodic fluctuations in the data, including preprocessing the original data to eliminate outliers and noise, predicting the data trend through the ARIMA model, and using the FFT method to analyze the periodic components of the data. The generated operation data analysis results record the change trends of temperature and power parameters at different time nodes. The target data provides a scientific basis for further power supply performance evaluation and maintenance planning.

[0126] Based on the analysis results of the operation data, the performance degradation analysis sub-module evaluates the reliability of the power supply, calculates the degradation trend of the power supply performance, and generates performance prediction information;

[0127] The specific formula for calculating the degradation trend of the power supply performance is:

[0128]

[0129] Where, P t represents the predicted output at time point t, x t-i+1 represents the power supply output data at the i-th time point forward from the current time t, w i is the weight coefficient at the i-th time point, n is the total number of time periods considered, i is the time point index within the current period, t is the time point of the current analysis, representing the prediction moment.

[0130] Formula:

[0131]

[0132] Detailed explanation of the formula and the derivation process of the formula calculation:

[0133] The formula is used to calculate the predicted output of the power supply performance at time point t. By using the weighted average of historical data, the weighting coefficient reflects the importance of the most recent data, improving the accuracy and response speed of the prediction. The result is used to evaluate the future performance degradation trend of the power supply and assist in adjusting the maintenance strategy;

[0134] Parameter meanings and setting values:

[0135] P t is the predicted output at time point t, indicating the expected performance of the power supply during the prediction period;

[0136] n is the total number of time periods considered, w i is the weight coefficient at the i-th time point, x t-i+1 is the power supply output data at the i-th time point forward from the current time t. Assume n = 3, weight w 1 = 0.6, w 2 = 0.3, w 3 = 0.1, x t-1 = 100, x t-2 = 95, x t-3 = 90;

[0137] i is the time point index within the current period;

[0138] Substitute the parameters into the formula for calculation:

[0139]

[0140] Pt = 97.5

[0141] Result P t = 97.5 indicates that within the currently set weights and the considered time period, the power output capacity score at the predicted time point t is 97.5, indicating that the power performance is relatively stable and slightly better than the average performance in the past few days. The result is used to analyze whether the power supply requires immediate maintenance or can continue to operate without a significant risk of performance degradation.

[0142] The power supply maintenance management sub-module adjusts the power supply maintenance time list according to the performance prediction information, optimizes the stability of the power supply operation, and generates a power supply maintenance record;

[0143] In the power supply maintenance management sub-module, based on the performance prediction information, by adjusting the power supply maintenance time list, the stability of the power supply operation is optimized. The technologies used include a CBM-based maintenance plan generator. According to the degradation time given in the performance prediction information, the priority and time window of the power supply maintenance are adjusted, the plan of the maintenance operation is set, the maintenance frequency and maintenance type are adjusted, and a power supply maintenance record is generated. The record includes the time of each maintenance operation, the components involved, and the relevant maintenance measures to ensure the efficient and safe operation of the power supply and prevent performance degradation and resulting failures.

[0144] The above is only a preferred embodiment of the present invention and does not limit the present invention in other forms. Any person skilled in the art may use the disclosed technical content to make changes or modifications into equivalent embodiments with equivalent changes and apply them to other fields. However, any simple modification, equivalent change, and modification made to the above embodiments based on the technical essence of the present invention without departing from the technical solution content of the present invention still fall within the protection scope of the technical solution of the present invention.

Claims

1. An AC / DC power supply based on magnetic integration, characterized in that: The power supply comprises: The compensation parameter calculation module executes the power supply output parameters input by the user based on the output power demand data, and compares them with the actual output of the power supply, identifies the difference and calculates the required compensation parameters, and generates an output parameter adjustment record; The power output management module analyzes the output parameter adjustment record, predicts the change of power demand according to the actual application scenario, adjusts and optimizes the power output, and generates power management effect information; The startup parameter configuration module adjusts the output parameters of the power supply when starting up based on the power supply management effect information, optimizes the stability of the power supply startup by smoothly increasing the voltage slope, and generates a soft start control record; The temperature management control module monitors the temperature data of multiple power components in real time based on the soft start control record, adjusts the output parameters of the cooling device, and generates power thermal management parameters; The abnormality monitoring and overload protection module identifies overload and short circuit based on the power supply thermal management parameters and the real-time voltage and current output data of the power supply, adjusts the switch state of the power supply, and generates an abnormal event processing log; The performance evaluation and maintenance management module is based on the abnormal event processing log, and through time series analysis of the power supply operation data, evaluates the reliability of the power supply, predicts the performance degradation trend, adjusts the maintenance time list, and generates the power supply maintenance record.

2. The AC / DC power supply based on magnetic integration according to claim 1, characterized in that: The output parameter adjustment record includes user input parameters, actual output monitoring data, and difference compensation parameters; the power management effect information includes power demand change prediction results, output voltage and current optimization records, and performance evaluation scores; the soft start control record includes adjustment data of the startup voltage slope, the time series of smooth startup, and stability indicators during the startup process; the power thermal management parameters include real-time temperature data and cooling device output settings adjusted according to the overheating risk assessment results; the abnormal event processing log includes marked abnormal power fluctuations, identified overload and short circuit events, and power switch adjustment status; the power supply maintenance record includes power supply operation data analysis results, predicted performance degradation trend information, and a maintenance time list.

3. The AC / DC power supply based on magnetic integration according to claim 1, characterized in that: The compensation parameter calculation module includes: The input processing submodule adjusts the power output based on the output power demand data and various power output parameters input by the user, including voltage, current and frequency, and generates input data records; The difference analysis submodule monitors the actual output of the power supply in real time based on the input data record, compares it with the preset parameters, identifies the output differences of voltage, current and frequency, and generates a difference identification result; The parameter calculation submodule calculates the compensation parameters required by the power supply based on the difference identification result, adjusts the output voltage, current and frequency, and generates an output parameter adjustment record.

4. The AC / DC power supply based on magnetic integration according to claim 1, characterized in that: The power output management module comprises: The scenario analysis submodule analyzes the output parameter adjustment record, and in combination with the actual application scenario, predicts the demand change of the power output by performing time series analysis on the power output parameters, and generates a demand prediction result; The output adjustment submodule adjusts the power output settings based on the demand prediction results, optimizes the voltage, current and frequency to match the predicted demand, optimizes the stability of the power output, and generates a power output optimization record; The effect evaluation submodule analyzes the operating efficiency and stability of the power supply according to the power supply output optimization record, evaluates the effectiveness of the adjusted output setting, and generates power supply management effect information.

5. The AC / DC power supply based on magnetic integration according to claim 1, characterized in that: The startup parameter configuration module includes: The startup voltage adjustment submodule sets the output voltage when the power supply is started based on the power supply management effect information and output requirements, and generates power supply startup parameters; The startup slope adjustment submodule generates a slope adjustment result by smoothly increasing the slope of the startup voltage based on the power startup parameters to optimize the stability of the power startup process; The startup process recording submodule records the power startup process based on the slope adjustment result, including real-time voltage, current, and frequency data at multiple time points during the startup process, evaluates the stability of the power startup, and generates a soft start control record.

6. The AC / DC power supply based on magnetic integration according to claim 1, characterized in that: The temperature management control module includes: The real-time temperature monitoring submodule collects temperature data of multiple components inside the power supply in real time based on the soft start control record and uses a temperature sensor to generate real-time temperature monitoring data; The power supply overheat identification submodule calculates the change trend of the temperature data based on the real-time temperature monitoring data, identifies the power supply overheat risk, and generates an overheat risk analysis result; The cooling demand analysis submodule evaluates the cooling demand according to the temperature data based on the overheating risk analysis result, adjusts the output parameters of the cooling device, including the speed of the cooling fan, and generates power supply thermal management parameters.

7. The AC / DC power supply based on magnetic integration according to claim 6, characterized in that: The specific formula for calculating the change trend of temperature data is: Among them, T t represents the predicted temperature value at time t, c is a constant term, φ i is the autoregressive coefficient, i represents the time unit from the current time point t forward, affecting the temperature value T at these historical time points t-i Contribution to the current prediction, θ j is the moving average coefficient, j represents the error time unit from the current time point t forward, describing the historical forecast error ∈ t-j Impact on the current prediction, ∈ t is the current forecast error, p represents the order of autoregression, that is, including T t-1 to T t-p The historical temperature value, q represents the order of the moving average, that is, including ∈ t-1 to∈ t-q historical forecast errors.

8. The AC / DC power supply based on magnetic integration according to claim 1, characterized in that: The abnormality monitoring and overload protection module includes: The safety threshold comparison submodule compares the real-time voltage and current output data with the set safety threshold based on the power supply thermal management parameters, identifies the power data exceeding the safety threshold, and generates a power parameter comparison result; The power anomaly analysis submodule identifies and records abnormal power fluctuations based on the power parameter comparison results, evaluates the causes of the anomalies, including overload and short circuit, and generates an abnormal cause identification result; The short circuit and overload response submodule adjusts the switch state of the power supply according to the abnormal cause identification result and the identified abnormal cause, and generates an abnormal event processing log.

9. The AC / DC power supply based on magnetic integration according to claim 1, characterized in that: The performance evaluation and maintenance management module includes: The time series analysis submodule performs time series analysis on the power supply operation data based on the abnormal event processing log, including temperature data and deviation values ​​of output voltage and current, and generates operation data analysis results; The performance degradation analysis submodule evaluates the reliability of the power supply, calculates the degradation trend of the power supply performance, and generates performance prediction information based on the operation data analysis results; The power supply maintenance management submodule adjusts the maintenance time list of the power supply according to the performance prediction information, optimizes the stability of the power supply operation, and generates a power supply maintenance record.

10. The AC / DC power supply based on magnetic integration according to claim 9, characterized in that: The specific formula for calculating the degradation trend of power supply performance is: Among them, P t represents the predicted output at time point t, x t-i+1 represents the power output data from the current time t to the i-th time point forward, w i is the weight coefficient of the ith time point, n is the total number of time periods considered, i is the index of the time point within the current period, and t is the current analyzed time point, which represents the moment of prediction.

Images