Intelligent charging pile health diagnosis and fault prediction system

Abstract

The invention discloses an intelligent charging pile health diagnosis and fault prediction system, and relates to the technical field of electric vehicle charging pile detection. The invention discloses an intelligent charging pile health diagnosis and fault prediction system. Comprising an electric vehicle intelligent charging pile standard identification prompting module, an intelligent charging pile central server, an intelligent charging pile detection first detection analysis module, an intelligent charging pile detection first comparison analysis module, an intelligent charging pile detection second detection analysis module and an intelligent charging pile detection second comparison analysis module. And an intelligent charging pile detection third detection analysis module and an intelligent charging pile detection third comparison analysis module. Layered optimization control is performed by identifying the type of the electric vehicle and analyzing the output power parameters, the electromagnetic environment parameters and the sudden risk parameters of the intelligent charging pile, so that the accuracy of health diagnosis and fault prediction of the intelligent charging pile is improved, and the problem that in the prior art, the intelligent charging pile is damaged is solved. The problem that the accuracy of health diagnosis and fault prediction of the intelligent charging pile is insufficient exists.

Description

Technical Field

[0001] The present invention relates to the technical field of electric vehicle charging pile detection, and in particular to an intelligent charging pile health diagnosis and fault prediction system. Background Art

[0002] Smart charging piles are a kind of high-tech charging equipment that has emerged with the development of the new energy vehicle industry. With the popularity of electric vehicles, the demand for charging piles is increasing, which not only requires charging piles to have efficient and safe charging capabilities, but also requires them to be able to remotely monitor the charging status in real time, realize fault diagnosis and remote maintenance. Smart charging piles can collect charging data, including charging time, power, user usage habits, etc. through Internet technology, and provide data support for operators to optimize services. At the same time, smart charging piles can also intelligently dispatch charging power and time according to grid load and user needs, realize orderly charging, and ensure information security to prevent user data leakage or unauthorized access.

[0003] The existing smart charging pile health diagnosis and fault prediction system is implemented through the following technologies, including: using artificial intelligence technology to monitor the safety and diagnose faults of charging piles. Combined with the Internet of Things technology, the fault prediction and maintenance strategies of smart charging piles have been improved. Real-time fault prediction is performed using cost-sensitive logistic regression and cost-sensitive support vector machine classification. Health status assessment and prediction in the Internet of Vehicles environment: In the Internet of Vehicles environment, a comprehensive health status assessment and short-term prediction method for charging piles is also proposed.

[0004] For example, a charging control method for charging piles based on information monitoring is disclosed in a patent application with announcement number: CN118061839B, which includes: S1. Presetting control schemes for charging piles with multiple known fault types; S2. Obtaining a set of magnetic field strength matrices of fault-free charging piles; S3. Obtaining a set of magnetic field strength matrices of charging piles with known fault types; S4. Constructing a training sample set; S5. Constructing a classifier model based on the classification algorithm in the machine learning method, and training the classifier model with the training sample set to obtain a mature classifier model; S6. Obtaining the magnetic field strength matrix of the charging pile to be detected; S7. Sending the magnetic field strength matrix of the charging pile to be detected into the mature classifier model, and controlling the charging pile according to the output detection results.

[0005] For example, the remote management method and system for charging pile operation and maintenance disclosed in the patent application with announcement number: CN113580983B receives the CAN bus message reported by the charging pile to be diagnosed; reads the charging pile identifier in the CAN bus message, and forms a CAN bus message record according to the charging pile identifier; if there is fault information in the CAN bus message record, matches the faulty accessories corresponding to the fault information with the spare parts database to determine the list of spare parts required for the charging pile to be diagnosed.

[0006] However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the present application found that the above technology has at least the following technical problems:

[0007] In the prior art, electric vehicle charging piles used for airport services are more prone to failure than general electric vehicle charging piles due to the larger passenger flow and more concentrated demand of airport services. However, most existing electric vehicle charging piles only use conventional power parameter detection, and there is a problem of insufficient accuracy in health diagnosis and fault prediction of smart charging piles. Summary of the invention

[0008] The embodiments of the present application solve the problem of insufficient accuracy of health diagnosis and fault prediction of smart charging piles in the prior art by providing a smart charging pile health diagnosis and fault prediction system, thereby achieving the effect of improving the accuracy of health diagnosis and fault prediction of smart charging piles.

[0009] The embodiment of the present application provides a smart charging pile health diagnosis and fault prediction system, including: an electric vehicle smart charging pile standard identification prompt module, a smart charging pile central server, a smart charging pile detection first detection and analysis module, a smart charging pile detection first comparative analysis module, a smart charging pile detection second detection and analysis module, a smart charging pile detection second comparative analysis module, a smart charging pile detection third detection and analysis module and a smart charging pile detection third comparative analysis module; the electric vehicle smart charging pile standard identification prompt module is used to obtain an electric vehicle type identification result for an airport electric vehicle user according to a predefined electric vehicle smart charging pile type in a matching electric vehicle smart charging pile database; the smart charging pile central server is used to send a notification to the electric vehicle user; the smart charging pile detection first detection and analysis module is used to identify the type of electric vehicle according to the smart charging pile type. The output power parameter data is analyzed to obtain the basic value of the smart charging pile detection; the first comparison and analysis module of the smart charging pile detection is used to perform the first optimization adjustment of the smart charging pile according to the comparison and analysis results of the basic value of the smart charging pile detection; the second detection and analysis module of the smart charging pile detection is used to obtain the electromagnetic interference detection value of the smart charging pile according to the electromagnetic environment parameter data of the smart charging pile; the second comparison and analysis module of the smart charging pile detection is used to perform the second optimization adjustment of the smart charging pile according to the comparison and analysis results of the electromagnetic interference detection value of the smart charging pile; the third detection and analysis module of the smart charging pile detection is used to perform a comprehensive analysis to obtain the comprehensive assessment analysis value of the sudden risk of the smart charging pile; the third comparison and analysis module of the smart charging pile detection is used to perform the third optimization adjustment of the smart charging pile according to the comparison and analysis results of the comprehensive assessment analysis value of the sudden risk of the smart charging pile.

[0010] Furthermore, the electric vehicle type identification result obtained for the electric vehicle user at the airport specifically includes: when the electric vehicle user at the airport submits an application for using an electric vehicle charging pile, an image of the electric vehicle user's electric vehicle is captured by a smart camera, and the electric vehicle image is matched with the electric vehicle image in the electric vehicle smart charging pile database. If the match is successful, the standard type of the electric vehicle charging pile is obtained; if the match fails, a notification is sent to relevant personnel; the standard type of the electric vehicle charging pile is sent to the smart charging pile central server; the smart charging pile central server receives the standard type of the electric vehicle charging pile, matches the corresponding predefined target charging area according to the standard type of the electric vehicle charging pile, and sends a charging area notification to the electric vehicle user, wherein the charging area notification is used to describe the predefined target charging area.

[0011] Furthermore, the data analysis based on the output power parameters of the smart charging pile specifically includes: when the smart charging pile starts charging, after a predefined smart charging pile charging time, the output power parameters of the smart charging pile are collected, and the output power parameters of the smart charging pile include the output power of the smart charging pile, the insulation resistance value of the charging pile charging gun detection circuit, the average charging efficiency of the charging pile, the internal temperature of the charging pile and the total usage time of the charging pile; if the output power of the smart charging pile is less than or equal to the output power threshold of the smart charging pile, an alarm is issued and relevant personnel are notified to carry out maintenance; if the output power of the smart charging pile is greater than the output power threshold of the smart charging pile, the insulation resistance value of the charging pile charging gun detection circuit is compared and analyzed, if the insulation resistance value of the charging pile charging gun detection circuit is less than or equal to the predefined charging pile charging gun detection circuit insulation resistance threshold, an alarm is issued and relevant personnel are notified to carry out maintenance, if the insulation resistance value of the charging pile charging gun detection circuit is greater than the predefined charging pile charging gun detection circuit insulation resistance threshold, then the output power parameter analysis and evaluation of the smart charging pile is used to obtain the basic value of the smart charging pile detection.

[0012] Furthermore, the specific process of performing the first optimization adjustment of the smart charging pile based on the comparison and analysis results of the smart charging pile detection basic value is as follows: if the smart charging pile detection basic value is greater than or equal to the smart charging pile detection basic threshold, the system sensitivity of the temperature management system of the smart charging pile is increased, and a first notification is issued to relevant personnel, the first notification is used to inform to increase the inspection and maintenance frequency of the corresponding smart charging pile and to inform to perform manual inspection and analysis on the aging degree of the charging pile, and the corresponding smart charging pile is recorded as the first smart charging pile to be evaluated; if the smart charging pile detection basic value is less than the smart charging pile detection basic threshold, no adjustment is made.

[0013] Furthermore, the specific process of obtaining the electromagnetic interference detection value of the smart charging pile is: collecting the environmental magnetic field parameters of the first smart charging pile to be evaluated through a spectrum analyzer, the environmental magnetic field parameters include the magnetic field strength value, the electromagnetic interference center frequency, and the electromagnetic interference bandwidth; if the magnetic field strength value is greater than or equal to the magnetic field strength threshold of the smart charging pile, an alarm is issued and relevant personnel are notified to add anti-electromagnetic interference equipment to the corresponding smart charging pile; if the magnetic field strength value is less than the magnetic field strength threshold of the smart charging pile, the spectrum analyzer is used to analyze the overlap between the electromagnetic interference center frequency and the communication control frequency of the smart charging pile, and the electromagnetic interference detection value of the first smart charging pile to be evaluated is obtained through comprehensive analysis.

[0014] Furthermore, the second optimization adjustment of the smart charging pile is performed according to the comparative analysis result of the electromagnetic interference detection value of the smart charging pile, specifically including: if the electromagnetic interference detection value of the smart charging pile of the first smart charging pile to be evaluated is less than the electromagnetic interference detection threshold of the smart charging pile, then no adjustment is made, and the first smart charging pile to be evaluated is recorded as the second smart charging pile to be evaluated; if the electromagnetic interference detection value of the smart charging pile of the first smart charging pile to be evaluated is greater than or equal to the electromagnetic interference detection threshold of the smart charging pile, then calling a moving average filter to perform signal averaging processing on the communication control signal of the smart charging pile of the corresponding first smart charging pile to be evaluated and controlling the predefined anti-interference filter of the corresponding first smart charging pile to be evaluated to increase its cutoff frequency and bandwidth until the predefined maximum cutoff frequency and the predefined maximum bandwidth.

[0015] Furthermore, the second optimization adjustment of the smart charging pile based on the comparative analysis results of the electromagnetic interference detection values ​​of the smart charging pile also includes: after a predefined electromagnetic interference time, performing a second smart charging pile detection analysis on the first smart charging pile to be evaluated again, and obtaining a first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated; if the first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated is greater than or equal to a smart charging pile electromagnetic interference detection threshold, an electromagnetic interference alarm is issued and relevant personnel are notified to carry out maintenance; if the first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated is less than the smart charging pile electromagnetic interference detection threshold, no adjustment is made, and the first smart charging pile to be evaluated is recorded as the second smart charging pile to be evaluated.

[0016] Furthermore, the comprehensive analysis obtains a comprehensive assessment analysis value of the sudden risk of the smart charging pile, specifically including: averaging the basic detection values ​​of the smart charging piles in different smart charging pile charging battery monitoring time periods in different smart charging pile charging battery monitoring areas to obtain the basic average value of the smart charging pile detection; arranging all the electromagnetic interference detection values ​​of the smart charging piles in different smart charging pile charging battery monitoring time periods in the same smart charging pile charging battery monitoring area in reverse order to obtain the maximum electromagnetic interference detection value of the smart charging pile and record it as the maximum electromagnetic interference detection value of the smart charging pile; collecting the number of switch activation times of the smart charging pile switch circuit through the built-in switch circuit action sampler of the smart charging pile; comparing and analyzing the built-in charging current samplers of the smart charging pile in turn to obtain the maximum charging current of the smart charging pile; and comprehensively analyzing to obtain the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated.

[0017] Furthermore, the third optimization adjustment of the smart charging pile is performed according to the comparative analysis results of the comprehensive assessment analysis value of the sudden risk of the smart charging pile, specifically including: if the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated is less than the comprehensive assessment analysis threshold of the sudden risk of the smart charging pile, then no adjustment is made; if the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated is greater than or equal to the comprehensive assessment analysis threshold of the sudden risk of the smart charging pile, then the predefined charging current peak value of the corresponding smart charging pile is reduced, and the corresponding inspection frequency increase plan is matched according to the difference between the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated and the comprehensive assessment analysis threshold of the sudden risk of the smart charging pile.

[0018] Furthermore, the third optimization adjustment of the smart charging pile based on the comparative analysis results of the comprehensive assessment analysis value of the sudden risk of the smart charging pile also includes: if the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be assessed is greater than or equal to the comprehensive assessment analysis threshold of the sudden risk of the smart charging pile, recording the ratio of the corresponding second smart charging pile to be assessed and all smart charging piles, recorded as the ratio of the smart charging piles with risks to be assessed; if the ratio of the smart charging piles with risks to be assessed is greater than or equal to the threshold of the ratio of the smart charging piles with risks to be assessed, matching the corresponding charging energy storage addition plan according to the difference between the ratio of the smart charging piles with risks to be assessed and the threshold of the ratio of the smart charging piles with risks to be assessed; if the ratio of the smart charging piles with risks to be assessed is less than the threshold of the ratio of the smart charging piles with risks to be assessed, no adjustment is made.

[0019] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:

[0020] 1. By identifying the type of electric vehicles, analyzing the output power parameters, electromagnetic environment parameters and sudden risk parameters of the smart charging pile, hierarchical optimization control is performed respectively, thereby improving the accuracy of health diagnosis and fault prediction of the smart charging pile, and solving the problem of insufficient accuracy of health diagnosis and fault prediction of the smart charging pile in the existing technology.

[0021] 2. The second optimization adjustment of the smart charging pile is carried out by comparing and analyzing the electromagnetic interference detection values ​​of the smart charging pile, so as to detect electromagnetic interference on the smart charging pile. If the detection value exceeds the threshold, the signal is averaged using a moving average filter, and the cutoff frequency and bandwidth of the predefined anti-interference filter are adjusted to improve its anti-interference ability, thereby improving the reliability of health diagnosis and fault prediction of the smart charging pile.

[0022] 3. Perform the third optimization adjustment of smart charging piles by comparing the comprehensive assessment analysis values ​​of sudden risks of smart charging piles. Adjust the inspection frequency according to the difference and match the charging energy storage addition plan. Through real-time assessment and adjustment, the risks of smart charging piles can be dynamically managed. According to the specific risk assessment results of each charging pile, provide personalized adjustment plans to improve the effectiveness of adjusting smart charging piles. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 A schematic diagram of the structure of the smart charging pile health diagnosis and fault prediction system provided in an embodiment of the present application. DETAILED DESCRIPTION

[0024] The embodiment of the present application solves the problem of insufficient accuracy of health diagnosis and fault prediction of smart charging piles in the prior art by providing a smart charging pile health diagnosis and fault prediction system. By identifying the type of electric vehicle, analyzing the output power parameters, electromagnetic environment parameters and sudden risk parameters of the smart charging pile, hierarchical optimization control is performed respectively, thereby improving the accuracy of health diagnosis and fault prediction of the smart charging pile.

[0025] In order to better understand the above technical solution, the above technical solution will be described in detail below in conjunction with the accompanying drawings and specific implementation methods. Figure 1As shown, it is a structural schematic diagram of the smart charging pile health diagnosis and fault prediction system provided in the embodiment of the present application. The smart charging pile health diagnosis and fault prediction system provided in the embodiment of the present application includes: an electric vehicle smart charging pile standard identification prompt module, a smart charging pile central server, a smart charging pile detection first detection and analysis module, a smart charging pile detection first comparison and analysis module, a smart charging pile detection second detection and analysis module, a smart charging pile detection second comparison and analysis module, a smart charging pile detection third detection and analysis module and a smart charging pile detection third comparison and analysis module; the electric vehicle smart charging pile standard identification prompt module is used to obtain the electric vehicle type identification result of the airport electric vehicle user according to the predefined electric vehicle smart charging pile type matched in the electric vehicle smart charging pile database; the smart charging pile central server is used to send notifications to electric vehicle users; the smart charging pile standard identification prompt module is used to obtain the electric vehicle type identification result of the airport electric vehicle user according to the predefined electric vehicle smart charging pile type matched in the electric vehicle smart charging pile database; the smart charging pile central server is used to send notifications to electric vehicle users; the smart charging pile standard identification prompt module is used to obtain the electric vehicle type identification result of the airport electric vehicle user according to the predefined electric vehicle smart charging pile type matched in the electric vehicle smart charging pile database; the smart charging pile central server is used to send notifications to electric vehicle users; the smart charging pile standard identification prompt module is used to obtain the electric vehicle type identification result of the airport electric vehicle user; the smart charging pile central server is used to send notifications to electric vehicle users ... The first detection and analysis module of the charging pile detection is used to analyze the output power parameter data of the smart charging pile to obtain the basic detection value of the smart charging pile; the first comparative analysis module of the smart charging pile detection is used to perform the first optimization adjustment of the smart charging pile according to the comparative analysis results of the basic detection value of the smart charging pile; the second detection and analysis module of the smart charging pile detection is used to analyze the electromagnetic environment parameter data of the smart charging pile to obtain the electromagnetic interference detection value of the smart charging pile; the second comparative analysis module of the smart charging pile detection is used to perform the second optimization adjustment of the smart charging pile according to the comparative analysis results of the electromagnetic interference detection value of the smart charging pile; the third detection and analysis module of the smart charging pile detection is used to comprehensively analyze and obtain the comprehensive assessment analysis value of the sudden risk of the smart charging pile; the third comparative analysis module of the smart charging pile detection is used to perform the third optimization adjustment of the smart charging pile according to the comparative analysis results of the comprehensive assessment analysis value of the sudden risk of the smart charging pile.

[0026] Furthermore, the electric vehicle type identification result of the electric vehicle user at the airport is obtained, specifically including: when the electric vehicle user at the airport submits an application for using an electric vehicle charging pile, the electric vehicle image of the electric vehicle user is captured by a smart camera, and the electric vehicle image is matched with the electric vehicle image in the electric vehicle smart charging pile database. If the match is successful, the standard type of the electric vehicle charging pile is obtained, and if the match fails, a notification is sent to relevant personnel; the standard type of the electric vehicle charging pile is sent to the smart charging pile central server; the smart charging pile central server receives the standard type of the electric vehicle charging pile, matches the corresponding predefined target charging area according to the standard type of the electric vehicle charging pile, and sends a charging area notification to the electric vehicle user, wherein the charging area notification is used to describe the predefined target charging area.

[0027] In this embodiment, the airport serves passengers from all over the world. Electric vehicles of electric vehicle users at different airports may use different charging standards and connectors, so they need to be matched in advance and given guidance on the charging location of the electric vehicles.

[0028] Image recognition algorithms use edge detection algorithms, which are a fundamental technique in image processing and computer vision, to locate the edges of objects in an image.

[0029] The steps of calling the edge detection algorithm are as follows: use a Gaussian filter to remove noise from the image, convert the color image into a grayscale image, use the Sobel operator to calculate the gradient of the image in each direction (the Sobel operator is a set of convolution kernels used to calculate the derivatives of the image in the horizontal and vertical directions, calculate the gradient direction, and determine the direction of the edge. Calculate the gradient amplitude, which is a combination of the gradient in two directions; along the gradient direction, only retain the local maximum value, suppress the non-maximum value, and use it to refine the edge and remove non-edge pixels on the edge), apply two thresholds to determine which edges are strong edges and which are weak edges, and connect strong edges and weak edges to form a complete edge. If the weak edge is connected to the strong edge, the weak edge is retained; otherwise, the weak edge is suppressed, and the edge is post-processed, such as removing isolated small edges, filling small holes on the edge, etc., and the output edge detection result can be a binary image of the edge or a list of edge coordinates.

[0030] By calling the edge detection algorithm, the electric vehicle logo and model are obtained, and then the corresponding charging pile type of the electric vehicle is obtained.

[0031] If the matching fails, a notification is sent to relevant personnel, and the specific notification is used to express that the standard type of electric vehicle charging pile is obtained by manual matching.

[0032] According to the different types of electric vehicle charging pile standards, the corresponding actual charging location is matched, and the actual charging location is the predefined target charging area. Electric vehicle charging piles with different charging standards are in different areas, so they need to be matched and messages sent for guidance.

[0033] The standard types of electric vehicle charging piles corresponding to different actual charging locations can directly obtain the corresponding matching relationship from the electric vehicle charging pile area planning of the smart charging pile central server.

[0034] Charging area notifications can be sent in a variety of ways, such as display information and mobile phone APP push.

[0035] Furthermore, according to the data analysis of the output power parameters of the smart charging pile, it specifically includes: when the smart charging pile starts charging, after the predefined smart charging pile charging time, the output power parameters of the smart charging pile are collected, and the output power parameters of the smart charging pile include the output power of the smart charging pile, the insulation resistance value of the charging pile charging gun detection circuit, the average charging efficiency of the charging pile, the internal temperature of the charging pile and the total usage time of the charging pile; if the output power of the smart charging pile is less than or equal to the output power threshold of the smart charging pile, an alarm is issued and relevant personnel are notified to carry out maintenance; if the output power of the smart charging pile is greater than the output power threshold of the smart charging pile, the insulation resistance value of the charging pile charging gun detection circuit is compared and analyzed, if the insulation resistance value of the charging pile charging gun detection circuit is less than or equal to the predefined charging pile charging gun detection circuit insulation resistance threshold, an alarm is issued and relevant personnel are notified to carry out maintenance, if the insulation resistance value of the charging pile charging gun detection circuit is greater than the predefined charging pile charging gun detection circuit insulation resistance threshold, then the smart charging pile output power parameter analysis and evaluation is performed to obtain the basic value of the smart charging pile detection.

[0036] In this embodiment, the output power threshold of the smart charging pile is extracted from the smart charging pile central server.

[0037] If the output power of the smart charging pile is less than or equal to the output power threshold of the smart charging pile, it means that the output power of the smart charging pile is not within the normal range and requires manual inspection. Otherwise, manual inspection is not required, but further comparative analysis is required.

[0038] If the insulation resistance value of the charging pile charging gun detection circuit is less than or equal to the predefined charging pile charging gun detection circuit insulation resistance threshold, it means that the charging gun is charging abnormally. For example, the output power of the charging pile is within the normal range, but water has entered the charging gun, causing the insulation resistance value of the charging pile charging gun detection circuit to decrease, affecting the normal power output of the charging gun, and manual inspection is required. Otherwise, manual inspection is not required, but further analysis and evaluation are required.

[0039] It should be noted that if the insulation resistance value of the charging pile charging gun detection circuit is infinite, it may be that the internal circuit of the charging pile charging gun is broken. However, in this case, the output power of the smart charging pile will definitely be abnormal, so it has been detected in the previous step.

[0040] The basic value of smart charging pile detection is used to describe the basic level of relative failure risk of smart charging piles.

[0041] It represents the basic value of smart charging pile detection in the CS0th smart charging pile charging battery monitoring time period in the CQ0th smart charging pile charging battery monitoring area.

[0042] Divide the smart charging pile into different smart charging pile charging battery monitoring areas, and number the smart charging pile charging battery monitoring areas, CQ0 represents the number of the smart charging pile charging battery monitoring area, and CQ represents the total number of the smart charging pile charging battery monitoring areas;

[0043] The smart charging pile detection time is divided into different smart charging pile charging battery monitoring time periods, and the smart charging pile charging battery monitoring time periods are numbered, where CS0 represents the number of the smart charging pile charging battery monitoring time period, and CS represents the total number of the smart charging pile charging battery monitoring time period;

[0044]

[0045] It represents the insulation resistance value of the charging pile charging gun detection circuit in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0046] YZ represents a predefined charging pile charging gun detection circuit insulation resistance threshold, and the predefined charging pile charging gun detection circuit insulation resistance threshold is extracted from the smart charging pile central server.

[0047] The charging pile charging gun detection circuit is the ADC acquisition detection of the charging pile charging gun when it is connected for charging. ADC refers to an analog / digital converter or an analog / digital converter.

[0048] It represents the basic indication value of smart charging pile detection in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0049] It represents the average charging efficiency of the charging pile in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0050] It represents the maximum charging efficiency of the charging pile in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0051] It represents the minimum charging efficiency of the charging pile in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0052] It represents the average temperature inside the charging pile in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0053] It represents the maximum temperature inside the charging pile in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0054] Indicates the minimum temperature inside the charging pile in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0055] CDSY indicates the total usage time of the charging pile.

[0056] CDBSY indicates the predefined charging pile scrapping time.

[0057] It represents the influence factor of the charging times of the CQ0th smart charging pile charging battery monitoring area on the predefined charging pile scrapping time.

[0058] The predefined charging pile scrapping time is mostly estimated under ideal experimental conditions. In fact, more charging times will shorten the actual scrapping time of the charging pile. For the charging piles around the airport, the actual charging times are much higher than those under ideal experimental conditions.

[0059] The impact factor of the number of charging times on the predefined charging pile scrapping time represents the degree of influence of the number of charging times on the basic value of the intelligent charging pile detection.

[0060] The impact factor of the number of charging times on the predefined charging pile scrapping time can be directly obtained in the intelligent charging pile central server through a preset mapping relationship. For example, a mapping set of the real-time charging times and its corresponding charging times on the impact factor of the predefined charging pile scrapping time is constructed, and the real-time charging times are input into the mapping set to obtain the impact factor of the charging times on the predefined charging pile scrapping time. The mapping relationship can be one-to-one or many-to-one.

[0061] Furthermore, the specific process of performing the first optimization adjustment of the smart charging pile according to the comparative analysis results of the basic detection values ​​of the smart charging pile is as follows: if the basic detection value of the smart charging pile is greater than or equal to the basic detection threshold of the smart charging pile, the system sensitivity of the temperature management system of the smart charging pile is increased, and a first notification is issued to relevant personnel, wherein the first notification is used to inform the increase of the inspection and maintenance frequency of the corresponding smart charging pile and to inform the manual inspection and analysis of the aging degree of the charging pile, and the corresponding smart charging pile is recorded as the first smart charging pile to be evaluated; if the basic detection value of the smart charging pile is less than the basic detection threshold of the smart charging pile, no adjustment is made.

[0062] In this embodiment, if the smart charging pile detection basic value is greater than or equal to the smart charging pile detection basic threshold, it means that the corresponding smart charging pile has been used for a long time, the degree of aging is more serious, the charging efficiency and temperature control management efficiency are reduced, and further evaluation and analysis are needed.

[0063] Furthermore, the specific process of obtaining the electromagnetic interference detection value of the smart charging pile is as follows: the environmental magnetic field parameters of the first smart charging pile to be evaluated are collected through a spectrum analyzer, and the environmental magnetic field parameters include the magnetic field strength value, the electromagnetic interference center frequency, and the electromagnetic interference bandwidth; if the magnetic field strength value is greater than or equal to the magnetic field strength threshold of the smart charging pile, an alarm is issued and relevant personnel are notified to add anti-electromagnetic interference equipment to the corresponding smart charging pile; if the magnetic field strength value is less than the magnetic field strength threshold of the smart charging pile, the spectrum analyzer is used to analyze the overlap between the electromagnetic interference center frequency and the communication control frequency of the smart charging pile, and the electromagnetic interference detection value of the first smart charging pile to be evaluated is obtained through comprehensive analysis.

[0064] In this embodiment, the electromagnetic interference detection value of the smart charging pile is used to describe the risk level of the smart charging pile being affected by relative electromagnetic interference.

[0065] It indicates the electromagnetic interference detection value of the smart charging pile in the CQ0th smart charging pile charging battery monitoring area.

[0066]

[0067] It indicates the magnetic field strength value of the CS0th smart charging pile charging battery monitoring time period in the CQ0th smart charging pile charging battery monitoring area, in amperes per meter.

[0068] QDY indicates the magnetic field strength threshold of the smart charging pile.

[0069] KRD means that the predefined immunity level is the immunity level defined according to international standards (such as IEC 61000-4 series), which is used to measure the immunity of charging piles to electromagnetic interference of specific intensity.

[0070] CHD represents the degree of overlap between the center frequency of the electromagnetic interference and the communication control frequency of the smart charging pile, and the value range is (0, 1).

[0071] In spectrum analysis, the center frequency of the electromagnetic interference is the frequency of the peak or main component of the interference signal. The higher the overlap between the center frequency of the electromagnetic interference and the communication control frequency of the smart charging pile, the more obvious the mutual interference.

[0072] It represents the electromagnetic interference bandwidth of the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging pile charging battery monitoring area, in Hertz.

[0073] DKY predefines the bandwidth used for communication control of smart charging piles in Hertz.

[0074] Furthermore, a second optimization adjustment of the smart charging pile is performed according to the comparative analysis results of the electromagnetic interference detection values ​​of the smart charging pile, specifically including: if the electromagnetic interference detection value of the smart charging pile of the first smart charging pile to be evaluated is less than the electromagnetic interference detection threshold of the smart charging pile, no adjustment is made, and the first smart charging pile to be evaluated is recorded as the second smart charging pile to be evaluated; if the electromagnetic interference detection value of the smart charging pile of the first smart charging pile to be evaluated is greater than or equal to the electromagnetic interference detection threshold of the smart charging pile, a moving average filter is called to perform signal averaging processing on the communication control signal of the smart charging pile of the corresponding first smart charging pile to be evaluated, and the predefined anti-interference filter of the corresponding first smart charging pile to be evaluated is controlled to increase its cutoff frequency and bandwidth until the predefined maximum cutoff frequency and the predefined maximum bandwidth.

[0075] In this embodiment, the signal is averaged by sampling the signal multiple times and then averaging the sampled values ​​through a moving average filter, which can reduce the influence of random noise.

[0076] A predefined anti-interference filter is a pre-designed electronic or digital filter used to reduce or eliminate electromagnetic interference within a specific frequency range. It can be designed specifically for the frequency of electromagnetic interference signals in the airport, and its cut-off frequency, bandwidth and other parameters can be controlled and adjusted to filter out interference signals within a specific frequency range.

[0077] In Python, you can use the convolve function in the NumPy library to implement signal averaging processing using a moving average filter.

[0078] The following is an example of a software calling function:

[0079] import numpy as np

[0080] def mov i ng_average_f il ter(si gna l,wi ndow_s i ze):

[0081] wi ndow=np.ones(wi ndow_s i ze) / wi ndow_s i ze

[0082] return np.convo l ve(si gna l,wi ndow,mode='same')

[0083] The predefined maximum cutoff frequency and the predefined maximum bandwidth are extracted from the smart charging pile central server.

[0084] Furthermore, performing a second optimization adjustment of the smart charging pile based on the comparative analysis results of the electromagnetic interference detection values ​​of the smart charging pile also includes: after a predefined electromagnetic interference time, performing a second smart charging pile detection analysis on the first smart charging pile to be evaluated again to obtain a first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated; if the first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated is greater than or equal to a smart charging pile electromagnetic interference detection threshold, an electromagnetic interference alarm is issued and relevant personnel are notified to perform maintenance; if the first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated is less than the smart charging pile electromagnetic interference detection threshold, no adjustment is made, and the first smart charging pile to be evaluated is recorded as the second smart charging pile to be evaluated.

[0085] In this embodiment, if after the predefined electromagnetic interference time, the electromagnetic interference detection value of the first smart charging pile to be evaluated is still greater than or equal to the electromagnetic interference detection threshold of the smart charging pile, it means that the electromagnetic interference exists for a long time and the interference is serious. The previous signal averaging and setting adjustment of the predefined anti-interference filter cannot effectively resist the electromagnetic interference, and an alarm is required to call for manual installation of hardware protection. Otherwise, it means that the adjustment is effective, but further evaluation and analysis is needed.

[0086] Furthermore, a comprehensive analysis is performed to obtain a comprehensive assessment analysis value of the sudden risk of the smart charging pile, specifically including: averaging the basic detection values ​​of the smart charging piles in different smart charging pile charging battery monitoring time periods in different smart charging pile charging battery monitoring areas to obtain the basic average value of the smart charging pile detection; arranging the electromagnetic interference detection values ​​of the smart charging piles in different smart charging pile charging battery monitoring time periods in the same smart charging pile charging battery monitoring area in reverse order to obtain the maximum electromagnetic interference detection value of the smart charging pile and record it as the maximum electromagnetic interference detection value of the smart charging pile; collecting the number of switch activation times of the smart charging pile switch circuit through the built-in switch circuit action sampler of the smart charging pile; comparing and analyzing the built-in charging current samplers of the smart charging pile in turn to obtain the maximum charging current of the smart charging pile; and obtaining the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated through comprehensive analysis.

[0087] In this embodiment, the built-in switch circuit action sampler of the smart charging pile is a designed switch sampling loop, which is used to monitor the state of the rechargeable battery and the number of times the switch circuit is enabled.

[0088] The comprehensive assessment analysis value of the sudden risk of smart charging piles is used to describe the relative level of the sudden risk of smart charging piles.

[0089]

[0090] It represents the comprehensive assessment and analysis value of the sudden risk of the smart charging pile in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0091] It indicates the maximum value of electromagnetic interference detection of the smart charging pile in the CQ0th smart charging pile charging battery monitoring area.

[0092] JbXj AVG Indicates the basic average value of smart charging pile detection.

[0093] Indicates the number of times the switch circuit of the smart charging pile is enabled in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area.

[0094] KGDL L Represents the average number of predefined switch activations for a switching circuit.

[0095] Frequent operation of the switching circuit will accelerate its aging, and the smart charging pile will accelerate its aging. In particular, the microscopic aging of electronic components is difficult to have a real and obvious impact on the output power under normal circumstances, and cannot be obtained through overall power parameter evaluation and analysis, but it will greatly increase the risk of subsequent overload.

[0096] The built-in charging current sampler of the smart charging pile is a designed charging current sampling circuit, which is used to monitor the charging current value.

[0097] It represents the maximum value of the smart charging pile charging current in the CS0th smart charging pile charging battery monitoring time period of the CQ0th smart charging pile charging battery monitoring area. The charging currents at each internal monitoring point of the smart charging pile are compared and analyzed in turn to obtain the maximum value of the smart charging pile charging current.

[0098] CDDL L It indicates the historical average charging current of the internal monitoring point corresponding to the maximum charging current of the smart charging pile.

[0099] The size of the charging current directly affects the charging speed and heat generation of the battery. A larger current will cause more heat to be generated inside the battery. At the same time, the switching circuit will frequently operate more frequently, and the upper and lower limits of the charging efficiency of the charging pile will be too large, which will accelerate the aging of the smart charging pile and increase the risk of overload. As the use time of the smart charging pile increases, the greater the volatility of the charging efficiency under the same switching circuit frequent operation frequency and charging current, the greater the risk of accelerated aging and overload of the smart charging pile.

[0100] It represents the correction factor of the impact of airport flight schedule on the comprehensive assessment analysis value of the sudden risk of smart charging piles.

[0101] The frequency of flights at an airport directly affects the frequency of use of vehicles in the airport. For example, during peak flight hours, the frequency of use of various types of vehicles in the airport (such as tractors, shuttle buses, etc.) will increase, and these vehicles usually need to be charged frequently. Therefore, the increase or decrease in flight frequency will directly affect the frequency of use and load of charging piles; there may be various safety risks in the operation of charging piles, such as equipment overheating, damage to the charging pile gun head, and water ingress. These risk factors will be more prominent during periods when the charging piles are used more frequently (such as peak flight hours); as the number of flights increases, the frequency of use of charging piles increases, and the corresponding maintenance and inspection frequency also needs to be increased to ensure the safe operation of charging piles; the setting of charging piles in the airport needs to take into account the limitation of power capacity. When the number of flights increases, the charging demand may exceed the power capacity, resulting in the charging piles being unable to meet the charging needs of all vehicles, thereby increasing safety risks; the impact of airport flight schedules on the sudden risk of smart charging piles is reflected in the increase in the frequency of use of charging piles, the accumulation of safety risks, the increase in maintenance needs, and the balance between power capacity and charging demand. Therefore, when evaluating the sudden risks of smart charging piles, it is necessary to consider the flight schedule and adjust the risk correction factor accordingly.

[0102] The impact correction factor of the airport flight schedule on the comprehensive assessment analysis value of the sudden risk of smart charging piles can be directly obtained from the smart charging pile central server through a pre-set mapping relationship. For example, a mapping set of the real-time number of airport flight schedules and their corresponding impact correction factors of the airport flight schedule on the comprehensive assessment analysis value of the sudden risk of smart charging piles is constructed, and the real-time number of airport flight schedules is input into the mapping set to obtain the impact correction factors of the airport flight schedule on the comprehensive assessment analysis value of the sudden risk of smart charging piles. The mapping relationship can be one-to-one or many-to-one.

[0103] φ 1 It represents the weight factor of the average charging efficiency of charging piles for the comprehensive assessment and analysis value of sudden risks of smart charging piles.

[0104] φ 2It represents the weight factor of the maximum value of the charging current of the smart charging pile for the comprehensive assessment and analysis value of the sudden risk of the smart charging pile.

[0105] φ 3 Represents the weight factor of the number of times the switch of the smart charging pile switch circuit is enabled for the comprehensive assessment and analysis value of the sudden risk of the smart charging pile.

[0106] The weight factor of the average charging efficiency of the charging pile for the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, the weight factor of the maximum charging current of the smart charging pile for the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, and the weight factor of the number of switch activations of the switch circuit of the smart charging pile for the comprehensive assessment and analysis value of the sudden risk of the smart charging pile respectively represent the numerical values ​​of the influence of the average charging efficiency of the charging pile, the maximum charging current of the smart charging pile, and the number of switch activations of the switch circuit of the smart charging pile on the comprehensive assessment and analysis value of the sudden risk of the smart charging pile.

[0107] The average charging efficiency of the charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, the maximum value of the charging current of the smart charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, and the number of switch activations of the switch circuit of the smart charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile can be directly obtained from the smart charging pile central server through a pre-set mapping relationship. For example, a mapping set of the real-time ambient temperature and its corresponding average charging efficiency of the charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, the maximum value of the charging current of the smart charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, and the number of switch activations of the switch circuit of the smart charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile is constructed, and the real-time ambient temperature is input into the mapping set to obtain the average charging efficiency of the charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, the maximum value of the charging current of the smart charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, and the number of switch activations of the switch circuit of the smart charging pile for the weight factor of the comprehensive assessment and analysis value of the sudden risk of the smart charging pile, wherein the mapping relationship can be one-to-one or many-to-one.

[0108] In the actual fault detection of smart charging piles, many faults occur suddenly, and by the time the fault is detected, great losses have already been caused. Due to the influence of airport flight schedules, the actual electricity demand of electric vehicle charging piles near the airport is relatively concentrated and huge, which can easily cause huge fluctuations in concentrated charging demand. The load pressure will rise rapidly in a short period of time. Due to the influence of flight schedules, the actual electricity demand of electric vehicle charging piles near the airport may show concentrated and huge fluctuations.

[0109] This rapid increase in load pressure in a short period of time may cause the following problems: the sudden increase in load may cause grid voltage fluctuations, affecting the stability of the grid, resulting in short-term undervoltage of the smart charging pile; the charging pile may not be able to withstand the load of a large number of electric vehicles charging at the same time in a short period of time, causing the charging pile to overheat or be damaged; under high load conditions, the charging efficiency volatility of the charging pile increases, because the concentrated fluctuations in charging and discharging demand will affect the charging speed; due to overload or voltage instability, the electronic components of the charging pile may be damaged, resulting in equipment failure; overload may cause the internal temperature of the charging pile to rise, increasing safety risks such as fire.

[0110] A high degree of electromagnetic interference will also increase the risk of loss of control of the internal program adjustment control when the smart charging pile is overloaded. The higher the degree of electromagnetic interference, the greater the risk of loss of control of the internal program adjustment control when the smart charging pile is overloaded.

[0111] Although the previous evaluation analysis of the second smart charging pile to be evaluated did not show any abnormalities, the risk of sudden overload failure of the smart charging piles for electric vehicles around the airport under the combined influence still needs to be considered when comprehensively evaluating the above parameters.

[0112] Furthermore, a third optimization adjustment of the smart charging pile is performed based on the comparative analysis results of the comprehensive assessment analysis value of the sudden risk of the smart charging pile, specifically including: if the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated is less than the comprehensive assessment analysis threshold of the sudden risk of the smart charging pile, no adjustment is made; if the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated is greater than or equal to the comprehensive assessment analysis threshold of the sudden risk of the smart charging pile, then the predefined charging current peak of the corresponding smart charging pile is reduced, and the corresponding inspection frequency increase plan stored in the smart charging pile central server is obtained by matching the difference between the comprehensive assessment analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated and the comprehensive assessment analysis threshold of the sudden risk of the smart charging pile.

[0113] In this embodiment, the inspection frequency increase plan can be set according to predefined rules. For example, when the difference between the smart charging pile sudden risk comprehensive assessment analysis value of the second smart charging pile to be evaluated and the smart charging pile sudden risk comprehensive assessment analysis threshold is 0.5, the corresponding inspection frequency increase plan is to add an inspector and increase the inspection frequency by 20%.

[0114] Furthermore, the third optimization adjustment of the smart charging pile is performed according to the comparative analysis results of the comprehensive assessment analysis values ​​of the sudden risks of the smart charging piles, and also includes: if the comprehensive assessment analysis value of the sudden risks of the smart charging piles of the second smart charging pile to be assessed is greater than or equal to the comprehensive assessment analysis threshold of the sudden risks of the smart charging piles, recording the ratio of the corresponding second smart charging pile to be assessed to all smart charging piles, and recording it as the ratio of the smart charging piles with risks to be assessed; if the ratio of the smart charging piles with risks to be assessed is greater than or equal to the ratio threshold of the smart charging piles with risks to be assessed, then the corresponding charging energy storage addition plan stored in the smart charging pile central server is obtained by matching the difference between the ratio of the smart charging piles with risks to be assessed and the ratio threshold of the smart charging piles with risks to be assessed; if the ratio of the smart charging piles with risks to be assessed is less than the ratio threshold of the smart charging piles with risks to be assessed, no adjustment is made.

[0115] In this embodiment, the charging energy storage addition plan can be set according to predefined rules. For example, when the difference between the risk-assessed smart charging pile ratio and the risk-assessed smart charging pile ratio threshold is 10%, the corresponding charging energy storage addition plan is to increase the energy storage system capacity of the smart charging pile by 15%.

[0116] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0117] The present invention is described with reference to flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0118] These computer program instructions may also be stored in a computer readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture including an instruction device, which implements the process Figure 1A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0119] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0120] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0121] Obviously, those skilled in the art may make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. Intelligent charging pile health diagnosis and fault prediction system, characterized by: It includes an electric vehicle intelligent charging pile standard identification prompt module, an intelligent charging pile central server, an intelligent charging pile detection first detection and analysis module, an intelligent charging pile detection first comparative analysis module, an intelligent charging pile detection second detection and analysis module, an intelligent charging pile detection second comparative analysis module, an intelligent charging pile detection third detection and analysis module and an intelligent charging pile detection third comparative analysis module; The electric vehicle intelligent charging pile standard identification prompt module is used to obtain the electric vehicle type identification result of the airport electric vehicle user according to the predefined electric vehicle intelligent charging pile type matched in the electric vehicle intelligent charging pile database; The smart charging pile central server is used to send notifications to electric vehicle users; The first detection and analysis module of the smart charging pile detection is used to analyze the output power parameter data of the smart charging pile to obtain the basic value of the smart charging pile detection; The first comparison and analysis module for detecting the smart charging pile is used to perform a first optimization adjustment of the smart charging pile according to the comparison and analysis result of the basic value of the smart charging pile detection; The second detection and analysis module of the smart charging pile detection is used to analyze the electromagnetic environment parameter data of the smart charging pile to obtain the electromagnetic interference detection value of the smart charging pile; The second comparison and analysis module for detecting the smart charging pile is used to perform a second optimization adjustment of the smart charging pile according to the comparison and analysis results of the electromagnetic interference detection value of the smart charging pile; The third detection and analysis module of the smart charging pile detection is used to comprehensively analyze and obtain a comprehensive assessment and analysis value of the sudden risk of the smart charging pile; The third comparison and analysis module for detecting smart charging piles is used to perform a third optimization adjustment of the smart charging piles according to the comparison and analysis results of the comprehensive assessment and analysis values ​​of the sudden risks of the smart charging piles.

2. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The method of obtaining the electric vehicle type identification result of the airport electric vehicle user specifically includes: When an electric vehicle user at the airport applies for the use of an electric vehicle charging pile, the electric vehicle image of the electric vehicle user is captured by a smart camera, and the electric vehicle image is matched with the electric vehicle image in the electric vehicle smart charging pile database. If the match is successful, the standard type of the electric vehicle charging pile is obtained. If the match fails, a notification is sent to relevant personnel. Send the electric vehicle charging pile standard type to the smart charging pile central server; The intelligent charging pile central server receives the electric vehicle charging pile standard type, matches the corresponding predefined target charging area according to the electric vehicle charging pile standard type, and sends a charging area notification to the electric vehicle user, wherein the charging area notification is used to describe the predefined target charging area.

3. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The analysis of the power parameter data output by the smart charging pile specifically includes: When the smart charging pile starts charging, after the predefined smart charging pile charging time, the smart charging pile output power parameters are collected. The smart charging pile output power parameters include the smart charging pile output power, the insulation resistance value of the charging pile charging gun detection circuit, the charging pile average charging efficiency, the charging pile internal temperature and the total use time of the charging pile; If the output power of the smart charging pile is less than or equal to the output power threshold of the smart charging pile, an alarm is issued and relevant personnel are notified for maintenance; If the output power of the smart charging pile is greater than the output power threshold of the smart charging pile, the insulation resistance value of the charging pile charging gun detection circuit is compared and analyzed. If the insulation resistance value of the charging pile charging gun detection circuit is less than or equal to the predefined charging pile charging gun detection circuit insulation resistance threshold, an alarm is issued and relevant personnel are notified for maintenance. If the insulation resistance value of the charging pile charging gun detection circuit is greater than the predefined charging pile charging gun detection circuit insulation resistance threshold, the output power parameters of the smart charging pile are analyzed and evaluated to obtain the basic value of the smart charging pile detection.

4. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The specific process of performing the first optimization adjustment of the smart charging pile according to the comparison and analysis results of the basic value of the smart charging pile detection is as follows: If the basic value of the smart charging pile detection is greater than or equal to the basic threshold of the smart charging pile detection, the system sensitivity of the temperature management system of the smart charging pile is increased, and a first notification is issued to relevant personnel, wherein the first notification is used to notify the increase of the inspection and maintenance frequency of the corresponding smart charging pile and to notify the manual inspection and analysis of the aging degree of the charging pile, and the corresponding smart charging pile is recorded as the first smart charging pile to be evaluated; If the smart charging pile detection basic value is less than the smart charging pile detection basic threshold, no adjustment will be made.

5. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The specific process of obtaining the electromagnetic interference detection value of the smart charging pile is as follows: Collecting environmental magnetic field parameters of the first smart charging pile to be evaluated through a spectrum analyzer, the environmental magnetic field parameters including the magnetic field strength value, the electromagnetic interference center frequency, and the electromagnetic interference bandwidth; If the magnetic field strength value is greater than or equal to the magnetic field strength threshold of the smart charging pile, an alarm is issued and relevant personnel are notified to add anti-electromagnetic interference equipment to the corresponding smart charging pile; If the magnetic field strength value is less than the magnetic field strength threshold of the smart charging pile, the spectrum analyzer is used to analyze the overlap between the center frequency of the electromagnetic interference and the communication control frequency of the smart charging pile, and a comprehensive analysis is performed to obtain the electromagnetic interference detection value of the first smart charging pile to be evaluated.

6. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The second optimization adjustment of the smart charging pile according to the comparison and analysis results of the electromagnetic interference detection value of the smart charging pile specifically includes: If the electromagnetic interference detection value of the first intelligent charging pile to be evaluated is less than the electromagnetic interference detection threshold of the intelligent charging pile, no adjustment is made, and the first intelligent charging pile to be evaluated is recorded as the second intelligent charging pile to be evaluated; If the electromagnetic interference detection value of the smart charging pile of the first smart charging pile to be evaluated is greater than or equal to the electromagnetic interference detection threshold of the smart charging pile, the communication control signal of the corresponding smart charging pile of the first smart charging pile to be evaluated is averaged by calling the moving average filter and the predefined anti-interference filter of the corresponding first smart charging pile to be evaluated is controlled to increase its cutoff frequency and bandwidth until the predefined maximum cutoff frequency and the predefined maximum bandwidth.

7. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The second optimization adjustment of the smart charging pile according to the comparison and analysis results of the electromagnetic interference detection value of the smart charging pile also includes: After a predefined electromagnetic interference time, the first smart charging pile to be evaluated is subjected to a second smart charging pile detection analysis again to obtain a first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated; if the first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated is greater than or equal to a smart charging pile electromagnetic interference detection threshold, an electromagnetic interference alarm is issued and relevant personnel are notified for maintenance; if the first smart charging pile electromagnetic interference detection value of the first smart charging pile to be evaluated is less than the smart charging pile electromagnetic interference detection threshold, no adjustment is made and the first smart charging pile to be evaluated is recorded as the second smart charging pile to be evaluated.

8. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The comprehensive analysis obtains the comprehensive assessment value of the sudden risk of the smart charging pile, which specifically includes: Performing average processing on the basic values ​​of smart charging pile detection in different smart charging pile charging battery monitoring time periods in different smart charging pile charging battery monitoring areas to obtain a basic average value of smart charging pile detection; Arrange all the electromagnetic interference detection values ​​of the smart charging piles in different smart charging pile charging battery monitoring time periods in the same smart charging pile charging battery monitoring area in reverse order, obtain the maximum electromagnetic interference detection value of the smart charging pile and record it as the maximum electromagnetic interference detection value of the smart charging pile; The number of times the switch circuit of the smart charging pile is enabled is collected through the built-in switch circuit action sampler of the smart charging pile; Compare and analyze the charging current samplers built into the smart charging pile in turn to obtain the maximum value of the charging current of the smart charging pile; The comprehensive analysis results show the comprehensive assessment value of the sudden risk of the second smart charging pile to be evaluated.

9. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The third optimization adjustment of the smart charging pile according to the comparison analysis result of the sudden risk comprehensive assessment analysis value of the smart charging pile specifically includes: If the smart charging pile sudden risk comprehensive assessment analysis value of the second smart charging pile to be assessed is less than the smart charging pile sudden risk comprehensive assessment analysis threshold, no adjustment is made; If the comprehensive assessment and analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated is greater than or equal to the comprehensive assessment and analysis threshold of the sudden risk of the smart charging pile, the predefined charging current peak of the corresponding smart charging pile is reduced, and the corresponding inspection frequency increase plan is matched according to the difference between the comprehensive assessment and analysis value of the sudden risk of the smart charging pile of the second smart charging pile to be evaluated and the comprehensive assessment and analysis threshold of the sudden risk of the smart charging pile.

10. The smart charging pile health diagnosis and fault prediction system according to claim 1, characterized in that: The third optimization adjustment of the smart charging pile according to the comparison analysis result of the sudden risk comprehensive assessment analysis value of the smart charging pile also includes: If the comprehensive assessment and analysis value of the sudden risk of the second smart charging pile to be assessed is greater than or equal to the comprehensive assessment and analysis threshold of the sudden risk of the smart charging pile, the ratio of the corresponding second smart charging pile to be assessed to all smart charging piles is recorded as the ratio of the risk smart charging pile to be assessed; If the risk-to-be-assessed smart charging pile ratio is greater than or equal to the risk-to-be-assessed smart charging pile ratio threshold, then the corresponding charging energy storage addition plan is matched according to the difference between the risk-to-be-assessed smart charging pile ratio and the risk-to-be-assessed smart charging pile ratio threshold; If the risk-to-be-assessed smart charging pile ratio is less than the risk-to-be-assessed smart charging pile ratio threshold, no adjustment will be made.

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