A low-voltage power supply pile intelligent optimization control method and system

Abstract

The application discloses a kind of low voltage power supply pile intelligent optimization control method and system, it is related to power supply pile intelligent optimization technical field, the system is by installing multiple types of sensors real-time monitoring the running data in the operation of power supply pile, and synchronous hits high-precision timestamp, pre-processes and constructs polarization response data group and perturbation data group.Polarization response control index fpj is calculated, and polarization response evaluation is carried out with the set insulation polarization risk threshold A, and when polarization response evaluation is there is polarization backlog, asymmetric perturbation energy index asy is calculated;Comprehensive dynamic control index vcm is obtained by summary calculation, and electric field perturbation risk evaluation is carried out with the set perturbation asymmetric tolerance threshold B, and then according to the evaluation result, execute control instruction.The system realizes the synchronous perception and joint control of polarization anomaly and perturbation trend in the starting process of power supply pile by real-time data acquisition and evaluation, improves electric field control precision and insulation stability.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of intelligent optimization of power supply piles, in particular to a low-voltage power supply pile intelligent optimization control method and system. BACKGROUND

[0002] With the large-scale popularization of new energy vehicles, low-voltage power supply piles gradually become one of the important infrastructures in urban electric transportation systems. Compared with high-voltage fast charging piles, low-voltage power supply piles have the advantages of flexible layout, low cost, high safety, etc., and are widely used in residential areas, office areas and shared travel scenes. However, under the conditions of high humidity environment or frequent load fluctuation, the starting stability and system adaptive adjustment capability of the traditional low-voltage power supply pile still have obvious shortcomings. In order to realize higher dimension of charging safety and efficiency improvement, the concept of "intelligent optimization control" emerges as the times require, aiming to use multi-source sensors to collect power supply state data in real time and build dynamic control logic. The core of the system focuses on the key sensitive area in the power supply link, that is, the insulation layer of the power supply cable, whose dielectric properties, polarization behavior and leakage risk directly affect whether the starting process of the whole system is smooth and safe.

[0003] The existing low-voltage power supply system mainly uses static design parameters for control, while ignoring the fact that in the actual running environment, the insulation layer of the power supply cable will be affected by environmental humidity, temperature change and electromagnetic disturbance, resulting in dynamic changes in its dielectric properties. Especially in long-term high humidity and plum rain season, the surface of the insulation layer is prone to "polarization accumulation" phenomenon, which shows abnormal states such as slow rise of leakage current and unbalanced electric field distribution; at the same time, due to the failure to effectively monitor the magnetic disturbance and current density change, the system is not easy to identify the potential "disturbance concentration area", which makes it not easy to intervene and adjust the control strategy in time. This control mechanism driven by "experience threshold" and "fixed logic" lacks the linkage perception ability to the changes of multiple physical fields, thereby reducing the response efficiency to the electric field disturbance risk and the evolution trend of insulation fatigue. SUMMARY

[0004] In view of the deficiencies of the prior art, the present application provides a low-voltage power supply pile intelligent optimization control method and system, which solves the problems in the background art.

[0005] To achieve the above purpose, the present application is realized by the following technical scheme: a low-voltage power supply pile intelligent optimization control system, comprising a synchronous sensing module, a polarization evaluation module, a disturbance energy analysis module and a comprehensive regulation and control module;

[0006] The synchronous sensing module is used for monitoring the running data of the power supply pile in real time according to the installed sensor group, and pre-processing the running data to obtain a polarization response data group and a disturbance data group;

[0007] The polarization evaluation module is configured to calculate the polarization response control index fpj according to the polarization response data set, and set the insulation polarization risk threshold A to evaluate the polarization response according to the polarization response control index fpj;

[0008] The disturbance energy analysis module is configured to calculate the asymmetric disturbance energy index asy according to the disturbance data set when the polarization response evaluation indicates that there is polarization backlog;

[0009] The comprehensive regulation module is configured to calculate the comprehensive dynamic regulation index vcm according to the polarization response control index fpj and the asymmetric disturbance energy index asy, set the disturbance asymmetric tolerance threshold B to evaluate the electric field disturbance risk according to the comprehensive dynamic regulation index vcm, and execute the regulation instruction according to the evaluation result.

[0010] Preferably, the synchronous perception module comprises a data perception unit and a data processing unit.

[0011] The data perception unit is configured to monitor the operation data of the low-voltage power supply pile in real time according to the sensor set installed inside the low-voltage power supply pile and on the surface of the power cable insulation layer.

[0012] The sampling period of the sensor set is controlled by the synchronous clock generated by the same RTC, and the monitored operation data is punched into a μs-level time stamp.

[0013] The sensor set comprises an IR thermopile sensor, a flexible patch current sensor, a humidity sensor, a multi-point array Hall sensor, and a micro current density sensor array.

[0014] The IR thermopile sensor is attached to the outer wall of the cable insulation layer in a spiral manner to monitor the cable surface temperature ts in real time, indicating the thermal response state of the insulation material and correlating with the polarization response rate.

[0015] The flexible patch current sensor is embedded in the insulation layer outside the wrapping belt to form a contact coupling loop, which monitors the insulation layer surface leakage current il in real time, indicating the electric field leakage condition of the insulation layer under humid conditions.

[0016] The humidity sensor installed near the power supply pile monitors the relative humidity rh of the environment in real time, which directly affects the polarization degree and the moisture absorption rate of the medium.

[0017] According to the spatial distribution characteristics of the power supply channel inside the power supply pile, the multi-point array Hall sensor is installed in sequence to monitor the magnetic induction intensity cg and the vertical magnetic field intensity bz in real time, which respectively represent the local magnetic disturbance during transient inrush and the inrush local density peak value in the initial stage of power supply anomaly.

[0018] The micro current density sensor array is sequentially installed on the periphery of the cable copper core to monitor the conductor local current density dm in real time, which represents the actual current density flowing in the conductor within a unit cross-sectional area.

[0019] Preferably, the data processing unit is used for pre-processing the real-time acquired operation data, acquiring a polarization response data set and a disturbance data set.

[0020] The pre-processing includes dimensionless processing, denoising, missing value processing and outlier processing.

[0021] The dimensionless processing is to standardize the multi-physical field data by using Z-Score standardization, the denoising is to suppress noise in the operation data by using multi-dimensional filtering technology to decompose and eliminate the noise influence in the data, the missing value processing is to fill the missing values in the data set by using the mean filling method, and the outlier processing is to detect and process the outliers in the collected operation data by using the interquartile range method.

[0022] The polarization response data set includes cable surface temperature ts, insulation layer surface leakage current il and environmental relative humidity rh.

[0023] The disturbance data set includes magnetic induction intensity cg, vertical magnetic field intensity bz and conductor local current density dm.

[0024] Preferably, the polarization evaluation module includes a polarization response analysis unit and a polarization risk evaluation unit.

[0025] The polarization response analysis unit is used for calculation according to the acquired polarization response data set to acquire a polarization response control index fpj for judging whether the insulation layer has polarization abnormality due to humidity and aging, and the specific formula is as follows.

[0026] ;

[0027] In the formula, ln represents a logarithmic function, dt represents a time integral quantity, ts(t), il(t) and rh(t) respectively represent the cable surface temperature, the insulation layer surface leakage current and the environmental relative humidity at time t.

[0028] Preferably, the polarization risk evaluation unit is used for pre-setting an insulation polarization risk threshold A according to the limit requirement of the insulation performance under the standard state of the power supply pile by a user, and performing polarization response evaluation with the real-time acquired polarization response control index fpj, and the specific evaluation scheme is as follows.

[0029] When the polarization response control index fpj is less than or equal to the insulation polarization risk threshold A, it indicates that the insulation layer does not form hysteresis polarization influence, and the conventional starting mode is maintained.

[0030] When the polarization response control index fpj > insulation polarization risk threshold A, it indicates that there is polarization accumulation in the insulation layer, and at this time, the disturbance distribution analysis is performed.

[0031] Preferably, the disturbance energy analysis module is used to perform disturbance distribution analysis when the polarization response evaluation indicates polarization accumulation.

[0032] The disturbance distribution analysis is used to calculate the asymmetric disturbance energy index asy according to the disturbance data set, to analyze whether a disturbance concentration area has been formed in the power supply system under the double disturbance of the magnetic field and the current signal, and the specific formula is as follows.

[0033] ;

[0034] In the formula, B represents the magnetic induction intensity gradient along the cable direction.

[0035] Preferably, the comprehensive control module includes a dynamic control analysis unit and an evaluation control unit.

[0036] The dynamic control analysis unit is used to calculate the comprehensive dynamic control index vcm according to the polarization response control index fpj and the asymmetric disturbance energy index asy, to synchronize the coupling of the polarization anomaly and the disturbance trend, to generate an accurate dynamic voltage regulation control function, and to realize intelligent soft compensation adjustment of the starting process, and the specific formula is as follows.

[0037] ;

[0038] In the formula, fpj(t) and asy(t) represent the polarization response control index and the asymmetric disturbance energy index at time t respectively, T0 represents the adjustment period set by the user, sin represents the sine function, represents the circular constant, and the value is two decimal places, and dt represents the time integral.

[0039] Preferably, the evaluation control unit includes a disturbance evaluation unit and a control instruction unit.

[0040] The disturbance evaluation unit is used to collect all historical comprehensive dynamic control indexes vcm to calculate the mean value, set a disturbance asymmetric tolerance threshold B based on the mean value, and perform electric field disturbance risk evaluation on the real-time obtained comprehensive dynamic control index vcm, and the specific evaluation scheme is as follows.

[0041] When the comprehensive dynamic control index vcm ≤ the disturbance asymmetric tolerance threshold B, it indicates that the electric field disturbance is in a safe range, and at this time, the slow rise control instruction is executed for control.

[0042] When the comprehensive dynamic regulation index vcm is greater than the disturbance asymmetric tolerance threshold B, it indicates that the electric field disturbance is unbalanced, at which time the strong soft start and pulse regulation compensation double mode control instruction is executed for regulation.

[0043] Preferably, the regulation instruction unit is used to execute the regulation instruction after the electric field disturbance risk assessment, specifically as follows:

[0044] When the slow rise control instruction is executed, the control behavior of the instruction includes:

[0045] The duty cycle regulation module of the PWM controller: adjust the duty cycle rise gradient control value from the original setting to 130% of the original value, and extend the voltage rise time from 200ms to 260ms;

[0046] The power MOS current limiting module: by controlling the MOS gate voltage rise rate, the starting current peak value is limited to 80% of the original setting value;

[0047] The RC filter control module: adjust the filter bandwidth to make the output voltage rise slope drop by 25%;

[0048] When the strong soft start and pulse regulation compensation double mode control instruction is executed, the control behavior of the instruction includes:

[0049] The PWM timer slope limiting module: extend the duty cycle growth period to 180% of the original setting, and increase the total voltage rise time to 360ms;

[0050] The output voltage redundancy control module: by dynamically adjusting the reference source, control the target voltage ±7% redundancy fluctuation band;

[0051] The periodic disturbance modulation module: through the Dither control strategy, make the PWM period produce ±0.2ms micro disturbance;

[0052] The high duty cycle limiting module: forcibly set the duty cycle not to exceed 85% of the rated value.

[0053] A low voltage power supply pile intelligent optimization control method, comprising the following steps:

[0054] S1, according to the installed sensor group, real-time monitoring the operation data of the power supply pile, and pre-processing the operation data, obtaining the polarization response data group and the disturbance data group;

[0055] S2, according to the polarization response data group, calculate the polarization response control index fpj, and set the insulation polarization risk threshold A and the polarization response control index fpj for polarization response evaluation;

[0056] S3, when the polarization response evaluation is that there is polarization accumulation, according to the disturbance data group, calculate the asymmetric disturbance energy index asy;

[0057] S4, according to the polarization response control index fpj and the asymmetric disturbance energy index asy, the comprehensive dynamic control index vcm is obtained by summary calculation, and the disturbance asymmetric tolerance threshold B is set to evaluate the electric field disturbance risk with the comprehensive dynamic control index vcm, and then the control instruction is executed according to the evaluation result.

[0058] The application provides a low-voltage power supply pile intelligent optimization control method and system.

[0059] (1) The system synchronous sensing module realizes real-time, synchronous and high-resolution sensing and time stamp labeling of multiple physical quantities in the operation environment of the power supply pile through a high-precision sensor group. This module can effectively capture early signs of polarization behavior and changes in disturbance field strength, establish a complete data acquisition closed loop, and obtain polarization response data sets and disturbance data sets through data preprocessing procedures, ensuring the quality of input data and providing stable and reliable polarization response data sets and disturbance data sets for subsequent modules, thereby completing the standardization and computability of sensing data.

[0060] (2) The polarization evaluation module and the disturbance energy analysis module of the system focus on the independent identification and index evaluation of insulation polarization abnormalities and electric field disturbance abnormalities. The polarization evaluation module calculates the polarization response control index fpj through a nonlinear integral function constructed by coupling the temperature, current and humidity three parameters of the polarization response data set, accurately identifies the polarization accumulation trend induced by aging or moisture, and performs polarization response evaluation with the set insulation polarization risk threshold A to realize the pre-identification of polarization risk. The disturbance energy analysis module calculates the asymmetric disturbance energy index asy based on the joint analysis of the magnetic field gradient and the current density, effectively identifies the potential spatial disturbance aggregation area in the power supply process, completes the spatial directional quantization evaluation of electromagnetic disturbance risk, and improves the identification ability of the system to dynamic abnormal areas.

[0061] (3) The comprehensive control module of the system constructs a control mechanism based on time window integration and nonlinear response function coupling. The polarization response control index fpj and the asymmetric disturbance energy index asy are summarized and calculated to obtain the comprehensive dynamic control index vcm, and the disturbance asymmetric tolerance threshold B is set to evaluate the electric field disturbance risk with the comprehensive dynamic control index vcm. After integrating the polarization and disturbance information, real-time judgment is performed to realize soft compensation control of the slow rise, enhancement and slow closing of the starting process. This mechanism not only effectively reduces the probability of insulation breakdown caused by peak voltage, but also enhances the adaptability and robustness of the power supply pile in complex load and high humidity environment, and overall realizes the bidirectional guarantee target of voltage rising process stability and insulation response safety, providing a new path for improving the intelligence and reliability of urban low-voltage power distribution system. BRIEF DESCRIPTION OF DRAWINGS

[0062] Figure 1 A low-voltage power supply pile intelligent optimization control system flowchart of the present application;

[0063] Figure 2 A low-voltage power supply pile intelligent optimization control method step schematic diagram of the present application;

[0064] Figure 3 A low-voltage power supply pile intelligent optimization control system operation principle diagram of the present application;

[0065] Figure 4 A risk assessment broken line diagram of the electric field disturbance of the present application. DETAILED DESCRIPTION

[0066] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0067] Embodiment 1

[0068] Please refer to Figure 1 The present application provides a low-voltage power supply pile intelligent optimization control system. To achieve the above purpose, the present application is implemented by the following technical solutions: including a synchronous sensing module, a polarization evaluation module, a disturbance energy analysis module and a comprehensive control module.

[0069] The synchronous sensing module is used for real-time monitoring of the operation data of the power supply pile according to the installed sensor group, and pre-processing the operation data to obtain a polarization response data group and a disturbance data group.

[0070] The polarization evaluation module is used for calculating according to the polarization response data group to obtain a polarization response control index fpj, and setting an insulation polarization risk threshold A to perform polarization response evaluation with the polarization response control index fpj.

[0071] The disturbance energy analysis module is used for calculating according to the disturbance data group to obtain an asymmetric disturbance energy index asy when the polarization response evaluation is that there is polarization backlog.

[0072] The comprehensive control module is used for performing summary calculation according to the polarization response control index fpj and the asymmetric disturbance energy index asy to obtain a comprehensive dynamic control index vcm, and setting a disturbance asymmetric tolerance threshold B to perform electric field disturbance risk evaluation with the comprehensive dynamic control index vcm, and then executing a control instruction according to the evaluation result.

[0073] In this embodiment, the synchronous perception module realizes full-quantity dynamic monitoring and data structure preprocessing of the operation state of the power supply pile, effectively divides the original sensing data into polarization response data group and disturbance data group, thereby building a data basis for subsequent evaluation and calculation. Through the installed sensors, the operation data of the power supply pile is collaboratively collected, greatly improving the system's state awareness in the context of multi-physical coupling. Compared with the traditional system which only relies on voltage and current thresholds for single-point alarm, the system has a wider perception range and higher timing accuracy, laying a solid foundation for dynamic regulation. The polarization evaluation module calculates the polarization response control index fpj based on the polarization response data group, and compares it with the preset insulation polarization risk threshold A. When the polarization response control index fpj exceeds the insulation polarization risk threshold A, it is considered that there is an insulation polarization backlog risk, triggering the operation of the disturbance energy analysis module. The latter further calculates the asymmetric disturbance energy index asy based on the disturbance data group, which is used to judge whether there is an electric field disturbance aggregation area. By exceeding the insulation polarization risk threshold A, the linkage judgment mechanism of the asymmetric disturbance energy index asy is activated, which not only evaluates the trend of insulation polarization, but also quantifies the imbalance of disturbance distribution, solving the defects of traditional systems that "misjudge disturbance" as regular fluctuations and "ignore polarization", and realizing panoramic risk identification of polarization behavior and disturbance behavior driven by two factors. In the comprehensive regulation module, the system fuses the polarization response control index fpj and the asymmetric disturbance energy index asy calculated in real time to construct a comprehensive dynamic regulation index vcm, and compares it with the disturbance asymmetric tolerance threshold B. When the comprehensive dynamic regulation index vcm is less than or equal to the disturbance asymmetric tolerance threshold B, execute the slow rise control instruction; when the comprehensive dynamic regulation index vcm is greater than the disturbance asymmetric tolerance threshold B, start the strong-soft start and pulse regulation compensation double-mode control mechanism, which realizes precise measures from time function adjustment, slope limitation, voltage redundancy regulation and other levels. Compared with the rigid strategy of fixed cycle and fixed threshold in the past, this mechanism has achieved a qualitative leap in time response, adaptive compensation and energy injection control, greatly improving the self-regulation ability and voltage stability of the power supply pile under humid aging and electromagnetic disturbance, and providing a more forward-looking risk identification and flexible regulation scheme for intelligent power systems.

[0074] Embodiment 2

[0075] Please refer to Figure 1 , specifically: the synchronous perception module includes a data perception unit and a data processing unit;

[0076] The data perception unit is used to monitor the operation data of the low-voltage power supply pile in real time according to the sensor group installed inside the low-voltage power supply pile and on the surface of the power cable insulation layer;

[0077] The sampling period of the sensor group is controlled by a synchronous clock generated by the same RTC, and the monitored operating data is timestamped to the μs level;

[0078] The sensor group includes an IR thermopile sensor, a flexible patch current sensor, a humidity sensor, a multi-point array Hall sensor, and a micro current density sensor array;

[0079] The IR thermopile sensor is attached to the outer wall of the cable insulation layer in a spiral manner to monitor the cable surface temperature ts in real time, monitor the polarization instability caused by the influence of temperature rise on the dielectric constant of the material, represent the thermal response state of the insulation material, and correlate the polarization response rate;

[0080] The flexible patch current sensor is embedded in the insulation layer wrapping belt to form a contact coupling loop, which monitors the insulation layer surface leakage current il in real time, represents the electric field leakage condition of the insulation layer under wet conditions, and monitors the weak current leakage caused by incomplete insulation polarization effect;

[0081] The relative humidity rh of the environment is monitored in real time according to the humidity sensor installed near the power supply post, which directly affects the polarization degree and the moisture absorption rate of the medium;

[0082] According to the spatial distribution characteristics of the power supply channel inside the power supply post, multi-point array Hall sensors are installed in sequence to monitor the magnetic induction intensity cg and the vertical magnetic field intensity bz in real time, which respectively represent the local magnetic disturbance during transient inrush current and the local density peak value of inrush current in the initial stage of power supply anomaly;

[0083] The micro current density sensor array is installed in sequence around the cable copper core to monitor the conductor local current density dm in real time, which represents the current density flowing in the actual conductor per unit cross-sectional area.

[0084] The data processing unit is used to preprocess the real-time acquired operating data to obtain a polarization response data set and a disturbance data set;

[0085] The preprocessing includes dimensionless processing, denoising, missing value processing, and outlier processing;

[0086] The dimensionless processing standardizes the multi-physical field data by using Z-Score standardization, the denoising uses multi-dimensional filtering technology to suppress noise in the operating data, and the missing value processing uses the mean filling method to fill the missing values in the data set, and the outlier processing uses the interquartile range method to detect and process the outliers in the collected operating data;

[0087] The polarization response data set includes the cable surface temperature ts, the insulation layer surface leakage current il, and the environmental relative humidity rh;

[0088] The perturbation data set includes a magnetic induction intensity cg, a vertical magnetic field intensity bz, and a conductor local current density dm.

[0089] In this embodiment, by integrating an IR thermopile sensor, a flexible patch current sensor, a humidity sensor, a multi-point array Hall sensor, and a micro current density sensor array in the low-voltage power supply pile and its cable structure, and by controlling the sampling rhythm of the sensors by a unified RTC clock, high- timing-precision data acquisition with a μs-level timestamp mark is realized; the data sensing unit comprehensively monitors the operation data of the low-voltage power supply pile in the power supply system; and the data processing unit structures the original data into a polarization response data set and a perturbation data set through a multi-step processing mechanism such as Z-Score standardization, multi-dimensional filtering, mean filling, and quartile range method. This implementation not only realizes accurate data separation and extraction of the insulation polarization dynamics and the magnetic-electric perturbation behavior, but also significantly enhances the identification ability of early risks under complex operating conditions; compared with the traditional single-variable sensing system, the data precision, identification breadth, and system response foresight are greatly improved, providing accurate, stable, and traceable data support for subsequent index calculation and control strategies, and significantly improving the intelligent degree and stability of the power supply pile operation

[0090] Embodiment 3

[0091] For details, please refer to Figure 1 The polarization evaluation module includes a polarization response analysis unit and a polarization risk evaluation unit.

[0092] The polarization response analysis unit is configured to calculate the polarization response control index fpj according to the obtained polarization response data set, so as to determine whether the insulation layer has polarization abnormalities due to humidity and aging. The specific formula is as follows:

[0093]

[0094] In the formula, ln represents a logarithmic function, dt represents a time differential, ts(t), il(t), and rh(t) represent the cable surface temperature, the insulation layer surface leakage current, and the environmental relative humidity at time t, respectively, represents a temperature rise modulation factor, which suppresses the exponential amplification of the change rate due to the temperature change, and the higher the temperature, the more serious the polarization hysteresis effect, and the smaller the amplification effect on the leakage current change rate, represents the growth rate of the leakage current per unit time, which is the reaction rate of the polarization dynamics of the insulation material under the excitation of the electric field, reflects the nonlinear increasing nature of the humidity influence, and the overall time integral accumulates the polarization response behavior in a short time to establish a time dimension polarization response behavior trend function.

[0095] ​The polarization risk assessment unit is used to preset an insulation polarization risk threshold A by a user according to a limit requirement for insulation performance in a standard state of a power supply pile, and to perform polarization response evaluation with a real-time acquired polarization response control index fpj. A specific evaluation scheme is as follows:

[0096] When the polarization response control index fpj≤ the insulation polarization risk threshold A, it indicates that the insulation layer is not affected by hysteresis polarization, and a normal starting mode is maintained.

[0097] When the polarization response control index fpj> the insulation polarization risk threshold A, it indicates that there is polarization accumulation in the insulation layer, and at this time, disturbance distribution analysis is performed.

[0098] In this embodiment, the polarization evaluation module is composed of a polarization response analysis unit and a polarization risk assessment unit. First, the polarization response analysis unit calculates the polarization response data group composed of cable surface temperature, insulation layer leakage current, and environmental humidity, and constructs a polarization response control index fpj. The index introduces a temperature rise modulation factor, a leakage current growth rate, and its time integral form in mathematics, and fully describes the polarization behavior trend of insulation materials under the coupling action of heat, humidity, and electricity.

[0099] The dielectric polarization behavior of the insulation layer is one of the fundamental reasons for voltage collapse under low voltage environment. Under humid environment, water molecules penetrate into the insulation micro-pore structure, making it exhibit a "class energy storage capacitor" effect, leading to a hysteresis in the process of establishing an external electric field. The insulation layer surface leakage current il is a direct manifestation of this effect; its growth trend indicates that the polarization rate is enhanced. High temperature accelerates the migration of medium charges, amplifies the polarization hysteresis effect, and therefore introduces adjustment; the higher the humidity, the easier the polarization potential is accumulated, and reflects the nonlinear amplification. All these parameters can be obtained in real time through existing sensors and are directly related to the physical process of polarization behavior.

[0100] The formula accumulates and calculates the polarization intensity behavior in the time domain in an integral form, aiming to reflect that polarization hysteresis is a process behavior rather than an instantaneous mutation. The three terms constitute a physical coupling chain: the leakage current change rate is the core driver, the cable surface temperature ts constrains the charge migration rate, and the environmental relative humidity rh reflects the nonlinear enhancement of microscopic polarization. The logarithmic function is used to avoid linear saturation distortion of the environmental relative humidity rh under high humidity conditions; and prevents the polarization change rate in the high temperature interval from being excessively responded by the system. The formula structure not only guarantees physical rationality, but also has numerical stability, which is convenient for deployment as a real-time running core state quantity in the control system.

[0101] The polarization risk assessment unit compares the polarization response control index fpj with the insulation polarization risk threshold A set by the user in real time, and when the polarization response control index fpj exceeds the insulation polarization risk threshold A, the system determines that there is polarization backlog and triggers the disturbance energy analysis process. This embodiment realizes quantitative modeling and early identification of the polarization hysteresis behavior of the insulation layer, effectively avoids the misjudgment or delayed response problem caused by the traditional scheme not considering the multi-physical field coupling behavior, thereby significantly improving the insulation safety, autonomous judgment ability and intelligent control precision of the low-voltage power supply pile in a complex environment, and has strong engineering application value and expansion potential.

[0102] Embodiment 4

[0103] Please refer to Figure 1 , specifically: the disturbance energy analysis module is used to perform disturbance distribution analysis when the polarization response evaluation is that there is polarization backlog;

[0104] The disturbance distribution analysis is used to calculate the asymmetric disturbance energy index asy according to the disturbance data set, which is used to analyze whether a disturbance concentration area has been formed in the power supply system under the dual disturbance of the magnetic field and the current signal. The specific formula is as follows:

[0105]

[0106] In the formula, represents the magnetic induction intensity gradient along the cable direction, which is used to analyze the non-uniformity of the magnetic field in space and whether there is an energy disturbance concentration area in the power supply path, represents a composite disturbance intensity function, which is used to construct a power supply waveform space and time disturbance synthesis index, control the comprehensive spatial field instability and time domain mutation, and output an index of disturbance severity, represents a background field adjustment mask function, which is used to dynamically suppress the composite disturbance intensity value.

[0107] In this embodiment, the disturbance energy analysis module is automatically activated when the polarization response control index fpj exceeds the insulation polarization risk threshold A in the polarization response evaluation, and the magnetic induction intensity cg, the vertical magnetic field intensity bz and the conductor local current density dm in the disturbance data set are called to construct the disturbance distribution analysis mechanism. Based on the calculation of the magnetic induction intensity gradient evaluate the spatial magnetic field non-uniformity, and dynamically obtain the asymmetric disturbance energy index asy by combining the composite disturbance intensity function and the background field adjustment mask function.

[0108] The low-voltage power supply pile output current waveform is prone to electromagnetic coupling disturbance under high humidity and high load conditions. The spatial characteristics of the disturbance are the magnetic induction intensity gradient ​The unevenness reflects local impedance mutation and insulation structure asymmetry in the power supply path, and the time characteristic is embodied in the increase of the conductor local current density dm, which represents signal distortion caused by load switching; and the vertical magnetic field strength bz represents whether it is under high background interference. The combination of the three is the complete expression of the time and space distribution of interference energy, and is the fundamental cause of the asymmetric power supply mode of power supply.

[0109] The formula integrates the spatial distribution and time mutation of the disturbance in the form of Euclidean norm, constructs the disturbance energy amplitude index, and then adjusts the background suppression through a nonlinear function to avoid misjudgment. When the overall magnetic field is low, the function tends to 1 and does not suppress the disturbance; when the overall magnetic field is high, the local disturbance will be judged as a background disturbance, and the system will not enter the misadjustment mode. This processing method can ensure that the control response is triggered only when the disturbance is highly concentrated and the background is stable, and has strong adaptive suppression ability.

[0110] This method can effectively identify the concentrated area of the electric field disturbance caused by the concentrated inrush current and electromagnetic unevenness, and realize quantitative modeling and suppression control of abnormal disturbance sources. Through this module, the system can identify and intervene in the disturbance trend before the voltage has abnormally fluctuated, breaking through the traditional electrical system's limitation of "only responding after the disturbance", and significantly improving the system's stability perception dimension, disturbance trend warning capability and local response accuracy of interference sources in the non-uniform power supply environment.

[0111] Embodiment 5

[0112] Please refer to Figure 1 , specifically: the comprehensive regulation module includes a dynamic regulation analysis unit and an evaluation and regulation unit;

[0113] The dynamic regulation analysis unit is used to perform summary calculation according to the polarization response control index fpj and the asymmetric disturbance energy index asy, and obtain a comprehensive dynamic regulation index vcm, which is used to synchronously couple the polarization anomaly and the disturbance trend, generate an accurate dynamic voltage regulation control function, and realize intelligent soft compensation adjustment of the starting process. The specific formula is as follows:

[0114] ;

[0115] In the formula, fpj(t) and asy(t) represent the polarization response control index and the asymmetric disturbance energy index at time t respectively, T0 represents the user's set adjustment period, sin represents the sine function, represents the circumference, and the value is two digits after the decimal point, and dt represents the time integral quantity, Sin(x) represents a sine window function, used to construct a time window adjustment function to prevent sudden changes in control output, making the regulation "slow start, increase, slow close", matching the actual control response law, and integrating all time point output trends through the integral term to form a decision quantity of the adjustment voltage, analyze the evolution of historical state, and perform trend type control response.

[0116] The evaluation regulation unit includes a disturbance evaluation unit and a regulation instruction unit.

[0117] The disturbance evaluation unit is used to collect all historical comprehensive dynamic regulation indexes vcm to calculate the mean value, and set a disturbance asymmetric tolerance threshold B based on the mean value, and then perform electric field disturbance risk evaluation with the real-time acquired comprehensive dynamic regulation index vcm. The specific evaluation scheme is as follows:

[0118] When the comprehensive dynamic regulation index vcm is less than or equal to the disturbance asymmetric tolerance threshold B, it indicates that the electric field disturbance is in a safe range, and at this time, the slow rise control instruction is executed for regulation.

[0119] When the comprehensive dynamic regulation index vcm is greater than the disturbance asymmetric tolerance threshold B, it indicates that the electric field disturbance is unbalanced, and at this time, the strong soft start and pulse regulation compensation double-mode control instruction is executed for regulation.

[0120] The regulation instruction unit is used to execute the regulation instruction after the electric field disturbance risk evaluation, and the specific regulation instruction is as follows:

[0121] When the slow rise control instruction is executed, the control behavior of the instruction includes:

[0122] The duty cycle adjustment module of the PWM controller: the duty cycle rise gradient control value is adjusted from the original setting to 130% of the original value, and the voltage rise time is extended from 200 ms to 260 ms;

[0123] The power MOS current limiting module: by controlling the MOS gate voltage rise rate, the starting current peak value is limited to 80% of the original set value;

[0124] The RC filter control module: adjust the filter bandwidth to make the output voltage rise slope drop by 25%, to prevent sharp peak excitation insulation collapse;

[0125] When the strong soft start and pulse regulation compensation double-mode control instruction is executed, the control behavior of the instruction includes:

[0126] The PWM timer slope limiting module: the duty cycle growth period is extended to 180% of the original setting, and the total voltage rise time is increased to 360 ms;

[0127] The output voltage redundancy control module: by dynamically adjusting the reference source, the target voltage ±7% redundancy fluctuation band is controlled.

[0128] Periodic disturbance modulation module: through the Dither control strategy, the PWM period produces ±0.2ms micro-disturbance, avoids coinciding with the electromagnetic resonance frequency band;

[0129] High duty cycle limiting module: forcibly set the duty cycle not to exceed 85% of the rated value, prevent transient excess energy injection into weak insulation area.

[0130] In this embodiment, the dynamic control analysis unit and the disturbance evaluation unit under the comprehensive control module construct a comprehensive dynamic control index vcm calculation mechanism based on the polarization response control index fpj and the asymmetric disturbance energy index asy synchronous summary. This formula is the core output module of the entire control system, used to control the voltage compensation behavior of the low-voltage pile when starting in an extreme state. It takes the polarization response control index fpj(t) and the asymmetric disturbance energy index asy(t) at the polarization lag state t as the core factor. Only when both of them reach a high value, the system will generate a larger dynamic compensation output. The sine window function is introduced to simulate the "soft slope" logic in the physical control curve, to ensure that the voltage compensation behavior has a natural rising and gradual falling control rhythm, and to avoid overshoot caused by sudden large voltage regulation.

[0131] The formula structure embodies the typical "product behavior linkage function". The polarization response control index fpj(t) and the asymmetric disturbance energy index asy(t) at time t are two physically different dimension trigger factors. Under the window function modulation, they are integrated and accumulated to form the final compensation signal, ensuring that the system makes judgments based on historical data behavior trends, improves the anti-jitter ability, has good dynamic response and direction perception ability, and the output presents a "bell-shaped response". The peak value is controlled in the middle stage, and the first and last stages tend to 0, which meets the principle of electronic soft start. The denominator T0 limits the control period window, which is used to normalize the overall adjustment speed and response amplitude. The overall structure is a composite model of behavior coordination linkage enhancement, time window control and filter noise reduction stability mechanism, which can ensure that the compensation behavior has the three attributes of intelligence, adaptability and physical interpretability. The comprehensive dynamic control index vcm output by the function can be directly sent to the PWM module to adjust the voltage rising slope and current loading rate in the early stage of power supply, which is one of the most critical control signals in the actual control system.

[0132] The dynamic disturbance asymmetric tolerance threshold B is set again to realize intelligent identification and adaptive response adjustment of the electric field disturbance risk; in the specific embodiment, according to the real-time relationship between the comprehensive dynamic control index vcm and the disturbance asymmetric tolerance threshold B, the “slow rise control” or “strong soft start and pulse regulation compensation” double-mode control strategy is accurately matched, the multi-dimensional collaborative control is performed on the parameters such as the PWM duty cycle rising gradient, the MOS current limiting rate, the filter bandwidth, the periodic disturbance fine adjustment and the high duty limit, the flexible correction of the voltage rise curve in the starting process and the energy modulation of the electromagnetic disturbance peak value are realized. Compared with the traditional single-threshold trigger or fixed cycle rising mode, the present scheme has higher adaptive ability and risk suppression ability, significantly improves the insulation safety margin, voltage regulation accuracy and system overall stability of the power supply pile in the high-humidity, polarization accumulation and current disturbance environment, and achieves the goal of intelligent, controllable and fine voltage starting compensation control

[0133] Embodiment 6

[0134] Please refer to Figure 2 A low-voltage power supply pile intelligent optimization control method, comprising the following steps:

[0135] S1, real-time monitoring of the running data of the power supply pile according to the installed sensor group, and pre-processing the running data to obtain a polarization response data group and a disturbance data group;

[0136] S2, calculating according to the polarization response data group to obtain a polarization response control index fpj, and setting an insulation polarization risk threshold A and the polarization response control index fpj for polarization response evaluation;

[0137] S3, when the polarization response evaluation is that there is polarization accumulation, calculating according to the disturbance data group to obtain an asymmetric disturbance energy index asy;

[0138] S4, calculating according to the polarization response control index fpj and the asymmetric disturbance energy index asy to obtain a comprehensive dynamic control index vcm, setting a disturbance asymmetric tolerance threshold B and the comprehensive dynamic control index vcm for electric field disturbance risk evaluation, and then executing a control instruction according to the evaluation result.

[0139] Although the embodiments of the present application have been shown and described, it can be understood by those of ordinary skill in the art that various changes, modifications, replacements and variations can be made to these embodiments without departing from the principles and spirits of the present application, and the scope of the present application is defined by the appended claims and their equivalents.

Claims

1. A smart optimization control system for low-voltage power supply piles, characterized in that: It includes a synchronous sensing module, a polarization assessment module, a disturbance energy analysis module, and a comprehensive control module; The synchronous sensing module is used to monitor the operation data of the power supply pile in real time based on the installed sensor group, and to preprocess the operation data to obtain polarization response data group and disturbance data group; The synchronous sensing module includes a data sensing unit and a data processing unit; The data sensing unit is used to monitor the operating data of the low-voltage power supply pile in real time based on the sensor group installed inside the low-voltage power supply pile and on the surface of the power supply cable insulation layer. The sampling period of the sensor group is controlled by a synchronous clock generated by the same RTC, and the monitored operating data is stamped with a μs-level timestamp. The sensor group includes an IR thermopile sensor, a flexible patch current sensor, a humidity sensor, a multi-point array Hall sensor, and a miniature current density sensor array. An IR thermopile sensor is spirally attached to the outer wall of the cable insulation layer to monitor the cable surface temperature ts in real time, which represents the thermal response state of the insulation material and correlates the polarization response rate. A flexible patch current sensor is embedded in the outer wrapping tape of the insulating layer to form a contact coupling circuit, which monitors the leakage current il on the surface of the insulating layer in real time, indicating the electric field leakage status of the insulating layer under humid conditions. The relative humidity (rh) of the environment is monitored in real time by a humidity sensor installed near the power supply pile, which directly affects the polarization degree and the moisture absorption rate of the medium. Based on the spatial distribution characteristics of the power supply channels inside the power supply pile, multi-point array Hall sensors are installed in sequence to monitor the magnetic induction intensity cg and the vertical magnetic field intensity bz in real time, which respectively represent the local magnetic disturbance during transient inrush and the peak value of the local density of the inrush during the initial stage of power supply anomaly. A miniature current density sensor array is sequentially installed around the copper core of the cable to monitor the local current density dm of the conductor in real time, which represents the actual current density flowing in the conductor per unit cross-sectional area. The polarization assessment module is used to calculate based on the polarization response data set, obtain the polarization response control index fpj, and set the insulation polarization risk threshold A and the polarization response control index fpj to perform polarization response assessment. The perturbation energy analysis module is used to calculate and obtain the asymmetric perturbation energy index asy based on the perturbation data set when the polarization response assessment indicates the presence of polarization accumulation. The integrated control module is used to calculate the integrated dynamic control index vcm by summarizing the polarization response control index fpj and the asymmetric disturbance energy index asy. It also sets the disturbance asymmetric tolerance threshold B and the integrated dynamic control index vcm to conduct electric field disturbance risk assessment, and then executes control commands based on the assessment results.

2. The intelligent optimization control system for low-voltage power supply piles according to claim 1, characterized in that: The data processing unit is used to preprocess the real-time acquired operating data to obtain polarization response data sets and disturbance data sets; The preprocessing includes dimensionless processing, noise reduction, missing value processing, and outlier processing. The dimensionless processing uses Z-Score standardization to perform standard transformation on the multiphysics data. The denoising uses multidimensional filtering technology to suppress noise in the running data, decompose and eliminate the noise influence in the data. Missing value processing uses the mean imputation method to fill in the missing values ​​in the dataset. Outlier processing uses the interquartile range method to detect and process outliers in the collected running data. The polarization response data set includes cable surface temperature ts, insulation surface leakage current il, and ambient relative humidity rh; The disturbance data set includes magnetic induction intensity cg, vertical magnetic field intensity bz, and conductor local current density dm.

3. The intelligent optimization control system for low-voltage power supply piles according to claim 2, characterized in that: The polarization assessment module includes a polarization response analysis unit and a polarization risk assessment unit; The polarization response analysis unit is used to calculate based on the acquired polarization response data set to obtain the polarization response control index fpj, which is used to determine whether the insulation layer has polarization abnormalities due to humidity and aging. The specific formula is as follows: ； In the formula, ln represents the logarithmic function, dt represents the time integral quantity, and ts(t), il(t), and rh(t) represent the cable surface temperature, insulation surface leakage current, and ambient relative humidity at time t, respectively.

4. The intelligent optimization control system for low-voltage power supply piles according to claim 3, characterized in that: The polarization risk assessment unit is used to preset the insulation polarization risk threshold A by the user based on the limit requirements of insulation performance under the standard state of the power supply pile, and to assess the polarization response with the real-time acquired polarization response control index fpj. The specific assessment scheme is as follows: When the polarization response control index fpj ≤ insulation polarization risk threshold A, it indicates that the insulation layer has not formed a hysteretic polarization effect and maintains the normal start-up mode; When the polarization response control index fpj > insulation polarization risk threshold A, it indicates that there is polarization accumulation in the insulation layer, and at this time, disturbance distribution analysis is performed.

5. The intelligent optimization control system for low-voltage power supply piles according to claim 4, characterized in that: The disturbance energy analysis module is used to perform disturbance distribution analysis when the polarization response is assessed as having polarization accumulation; Disturbance distribution analysis is used to calculate based on disturbance data sets to obtain the asymmetric disturbance energy index asy, which is used to analyze whether the power supply system has formed a disturbance concentration area under the dual disturbance of magnetic field and current signal. The specific formula is as follows; ； In the formula, This represents the gradient of magnetic induction intensity along the direction of the cable.

6. The intelligent optimization control system for low-voltage power supply piles according to claim 5, characterized in that: The integrated control module includes a dynamic control analysis unit and an evaluation control unit; The dynamic control analysis unit is used to summarize and calculate the comprehensive dynamic control index vcm based on the polarization response control index fpj and the asymmetric disturbance energy index asy. This index is used to couple the polarization anomaly with the disturbance trend synchronously to generate a precise dynamic voltage regulation control function, thereby realizing intelligent soft compensation adjustment of the startup process. The specific formula is as follows. ； In the formula, fpj(t) and asy(t) represent the polarization response control exponent and the asymmetric disturbance energy exponent at time t, respectively; T0 represents the user-defined adjustment period; and sin represents the sine function. dt represents pi, with a value to two decimal places, and dt represents the time calculus.

7. The intelligent optimization control system for low-voltage power supply piles according to claim 6, characterized in that: The assessment and control unit includes a disturbance assessment unit and a control instruction unit; The disturbance assessment unit is used to collect all historical comprehensive dynamic control indices vcm, calculate the average value, set a disturbance asymmetry tolerance threshold B based on the average value, and then perform an electric field disturbance risk assessment with the real-time acquired comprehensive dynamic control index vcm. The specific assessment scheme is as follows: When the comprehensive dynamic control index vcm ≤ the disturbance asymmetry tolerance threshold B, it means that the electric field disturbance is within a safe range. At this time, the gradual increase control command is executed for regulation. When the comprehensive dynamic control index vcm > the disturbance asymmetry tolerance threshold B, it indicates that the electric field disturbance is unbalanced. At this time, the dual-mode control command of strong soft start and pulse regulation compensation is executed for regulation.

8. The intelligent optimization control system for low-voltage power supply piles according to claim 7, characterized in that: The control command unit is used to execute control commands after the electric field disturbance risk assessment, as follows; When the gradual ascent control command is executed, the control behavior of the command includes: The duty cycle adjustment module of the PWM controller adjusts the duty cycle rise gradient control value from the original setting to 130% of the original value, thereby extending the voltage rise time from 200ms to 260ms. Power MOS current limiting module: By controlling the rise rate of the MOS gate voltage, the peak startup current is limited to 80% of the original set value; RC filter control module: Adjusts the filter bandwidth to reduce the output voltage rise slope by 25%; When executing the dual-mode control command of strong soft start and pulse regulation compensation, the control behavior of the command includes: PWM timer slope limiting module: extends the duty cycle growth period to the original setting of 180%, increasing the total voltage rise time to 360ms; Output voltage redundancy control module: controls the redundancy fluctuation band of the target voltage by dynamically adjusting the reference source to ±7%; Periodic perturbation modulation module: Through the Dither control strategy, a micro-perturbation of ±0.2ms is generated in the PWM period; High duty cycle limiting module: forces the duty cycle to not exceed 85% of the rated value.

9. A method for intelligent optimization control of low-voltage power supply piles, applied to the intelligent optimization control system for low-voltage power supply piles as described in any one of claims 1-8, characterized in that: Includes the following steps: S1. Based on the installed sensor group, monitor the operation data of the power supply pile in real time, and preprocess the operation data to obtain polarization response data group and disturbance data group; S2. Calculate the polarization response control index fpj based on the polarization response data set, and set the insulation polarization risk threshold A and the polarization response control index fpj to evaluate the polarization response. S3. When the polarization response assessment indicates the presence of polarization accumulation, the asymmetric perturbation energy index asy is obtained by calculation based on the perturbation data set. S4. Based on the polarization response control index fpj and the asymmetric disturbance energy index asy, the comprehensive dynamic control index vcm is obtained. The disturbance asymmetric tolerance threshold B and the comprehensive dynamic control index vcm are used to conduct an electric field disturbance risk assessment. Then, the control command is executed based on the assessment results.

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