Intelligent management system of charging piles based on data analysis

Abstract

The present invention discloses a charging pile intelligent management system based on data analysis, which relates to the technical field of charging pile management. The data acquisition module collects multi-source data related to the health status of the charging pile, the state evaluation module comprehensively analyzes the multi-source data of the charging pile and establishes a state coefficient, judges the health status of the charging pile by comparing the state coefficient with the health threshold and formulates a corresponding strategy, the sorting module regularly obtains the average state coefficient of the charging pile, and sorts all the charging piles from small to large according to the average state coefficient, generates a sorting table, and the administrator generates a dynamic plan view of the charging station through a plan view generation module according to user needs. The present invention not only comprehensively analyzes the health status of the charging pile, which is convenient for timely management, but also can select the charging pile maintenance order according to the state of the charging pile when regularly maintaining the charging pile, effectively improving the maintenance efficiency of the charging pile.

Description

Technical Field

[0001] The present invention relates to the technical field of charging pile management, and in particular to a charging pile intelligent management system based on data analysis. Background Art

[0002] With the increasing awareness of environmental protection and concerns about the exhaust emissions of traditional fuel vehicles, the demand for electric vehicles is growing worldwide. Governments and enterprises are actively promoting the popularization of electric vehicles and encouraging people to adopt environmentally friendly travel methods, which has given rise to the demand for the construction of large-scale charging stations. Large-scale charging stations refer to large-scale charging facilities dedicated to providing charging services for electric vehicles. Large-scale charging stations have become an important place for electric vehicle users to travel long distances and charge quickly, and are also an important part of the electric vehicle charging infrastructure in cities and regions.

[0003] The charging pile intelligent management system is an advanced technical solution developed to meet the growing demand for electric vehicles. The intelligent management system aims to optimize the operation and management of charging piles and provide users with more convenient, efficient and safe charging services.

[0004] The prior art has the following deficiencies:

[0005] 1. The existing management system usually monitors the charging process of the charging pile when it is put into use. The management system does not have a comprehensive evaluation and management of the charging pile, so it is impossible to analyze the health status of each charging pile and make corresponding management;

[0006] 2. Large charging stations cover a large area and have a large number of charging piles. When the charging piles are regularly maintained and managed, the management and maintenance order of the charging piles is usually randomly selected. This often results in charging piles with poor operating conditions not receiving preferential maintenance treatment, reducing the management and maintenance efficiency of the charging piles. Summary of the invention

[0007] The purpose of the present invention is to provide a charging pile intelligent management system based on data analysis to solve the shortcomings of the background technology.

[0008] In order to achieve the above-mentioned object, the present invention provides the following technical solutions: a charging pile intelligent management system based on data analysis, comprising a data acquisition module, a state evaluation module, a sorting module, a floor plan generation module, a partitioning module, a decision module and a display module;

[0009] Data acquisition module: used to collect multi-source data related to the health status of charging piles;

[0010] Status evaluation module: Comprehensively analyze the multi-source data of the charging pile and establish the status coefficient. By comparing the status coefficient with the health threshold, the health status of the charging pile is judged and corresponding strategies are formulated;

[0011] Sorting module: regularly obtain the average state coefficient of the charging piles, and sort all the charging piles from small to large according to the average state coefficient to generate a sorting table;

[0012] Plan generation module: The administrator generates a dynamic plan of the charging station through the plan generation module according to user needs;

[0013] Partitioning module: divides the charging piles into several charging areas based on dynamic floor plan information;

[0014] Decision-making module: After obtaining the usage frequency and status coefficient of the charging piles in the charging area, comprehensively analyze the efficiency indicators of the charging piles in the charging area, and make corresponding decisions based on the big database;

[0015] Display module: used to display charging pile evaluation results, ranking tables, dynamic floor plans, charging areas and decisions.

[0016] In a preferred embodiment, the state evaluation module comprehensively analyzes multi-source data of the charging pile and establishes a state coefficient, wherein the multi-source data includes a volume floating coefficient of the charging interface material, a dynamic and static power loss index, a software error rate, and an environmental electromagnetic interference degree.

[0017] In a preferred embodiment, the state evaluation module comprehensively calculates the volume floating coefficient of the charging interface material, the dynamic and static power loss index, the software error rate, and the environmental electromagnetic interference to obtain the state coefficient ztx, and the calculation expression is:

[0018]

[0019] Where, djs is the dynamic and static power loss index, jkf is the volume floating coefficient of the charging interface material, rjb is the software error rate, dcg is the environmental electromagnetic interference, and a 1 、a 2 、a 3 、a 4 Dynamic and static power loss index, charging interface material volume floating coefficient, software error rate, environmental electromagnetic interference coefficient, and a 1 、a 2 、a 3 、a 4 Both are greater than 0.

[0020] In a preferred embodiment, after the state evaluation module obtains the state coefficient ztx, it compares the state coefficient with the health threshold. If the state coefficient ztx of the charging pile is ≥ the health threshold, it is judged that the health state of the charging pile supports car charging. If the state coefficient ztx of the charging pile is < the health threshold, it is judged that the health state of the charging pile does not support car charging.

[0021] In a preferred embodiment, the calculation expression of the volume floating coefficient of the charging interface material is:

[0022]

[0023] TJ(t) is the real-time volume change of the charging interface material, [t x , t y ] is the period of temperature fluctuation warning at the charging interface.

[0024] In a preferred embodiment, the calculation expression of the dynamic and static power loss index is:

[0025]

[0026] Where bzd is the static standard energy loss, bze is the dynamic standard energy loss, jtd is the static real-time energy loss, and dtd is the dynamic real-time energy loss.

[0027] In a preferred embodiment, the calculation expression of the software error rate is:

[0028] rjb=bc / zsc

[0029] In the formula, bc is the number of software error reports, and zsc is the monitoring time period;

[0030] The calculation expression of environmental electromagnetic interference degree dcg is:

[0031] dcg=dcx / sbx

[0032] In the formula, dcx is the environmental electromagnetic interference signal strength, and sbx is the equipment working signal strength.

[0033] In a preferred embodiment, the sorting module generates a sorting table comprising the following steps:

[0034] Obtain all status coefficients of all charging piles every 30 days;

[0035] Calculate the average state coefficient of each charging pile;

[0036] Sort all charging piles according to the average state coefficient of each charging pile from small to large to generate a sorting table.

[0037] In a preferred embodiment, after the decision module obtains the usage frequency and state coefficient of the charging piles in the charging area, the comprehensive analysis of the efficiency index of the charging piles in the charging area includes the following steps:

[0038] Obtain the usage frequency and status coefficient of charging piles in each charging area over a period of time;

[0039] Obtain the number of times when the state coefficient is ≥ the health threshold and the number of times when the state coefficient is < the health threshold, and calculate the good-bad ratio of the charging pile during a period of operation. The calculation expression is: hb = hz2 / hz1, where hb is the good-bad ratio of the charging pile during a period of operation, hz1 is the number of times when the state coefficient is ≥ the health threshold, and hz2 is the number of times when the state coefficient is < the health threshold;

[0040] The efficiency index of the charging pile in the charging area is calculated by the usage frequency and the good-bad ratio of the charging pile during a period of operation. The expression is:

[0041]

[0042] Where pl is the usage frequency of the charging pile in the charging area, and hb is the good-bad ratio of the charging pile during operation for a period of time;

[0043] If the charging pile efficiency index in the charging area is less than the efficiency threshold, it is judged that the efficiency of the charging area is poor. If the charging pile efficiency index in the charging area is greater than or equal to the efficiency threshold, it is judged that the efficiency of the charging area is good.

[0044] In a preferred embodiment, the calculation expression for the usage frequency of the charging piles in the charging area is:

[0045]

[0046] In the formula, cdz i is the number of times the i-th charging pile is used, and T is the operating time period of the charging pile.

[0047] In the above technical solution, the technical effects and advantages provided by the present invention are:

[0048] 1. The present invention collects multi-source data related to the health status of the charging pile through the data acquisition module, the status evaluation module comprehensively analyzes the multi-source data of the charging pile and establishes a status coefficient, judges the health status of the charging pile by comparing the status coefficient with the health threshold and formulates a corresponding strategy, the sorting module regularly obtains the average status coefficient of the charging pile, and sorts all the charging piles from small to large according to the average status coefficient to generate a sorting table, and the administrator generates a dynamic plan view of the charging station through the plan view generation module according to user needs, and the display module displays the charging pile evaluation results, sorting table, dynamic plan view, charging area and decision together, which not only comprehensively analyzes the health status of the charging pile, but also facilitates timely management, and when regularly maintaining the charging pile, the charging pile maintenance order can be selected according to the status of the charging pile, effectively improving the maintenance efficiency of the charging pile.

[0049] 2. The present invention comprehensively analyzes the multi-source data of the charging pile through the state evaluation module and establishes a state coefficient. The multi-source data includes the volume floating coefficient of the charging interface material, the dynamic and static power loss index, the software error rate and the environmental electromagnetic interference degree. The volume floating coefficient of the charging interface material, the dynamic and static power loss index, the software error rate and the environmental electromagnetic interference degree are comprehensively calculated to obtain the state coefficient, thereby effectively improving the comprehensive data processing efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in the present invention. For ordinary technicians in this field, other drawings can also be obtained based on these drawings.

[0051] Figure 1 It is a system module diagram of the present invention. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0053] Example 1: Please refer to Figure 1 As shown, the charging pile intelligent management system based on data analysis described in this embodiment includes a data acquisition module, a state evaluation module, a sorting module, a floor plan generation module, a partitioning module, a decision module and a display module;

[0054] A. Data acquisition module: used to collect multi-source data related to the health status of the charging pile and send the multi-source data to the status assessment module;

[0055] Determine which data related to the health status of the charging pile needs to be collected, deploy appropriate sensor equipment to collect relevant data, connect the sensor to the data acquisition module, and ensure that the data collected by the sensor can be transmitted to the data acquisition module for processing and storage. The data acquisition module is responsible for real-time collection of data obtained by the sensor and storing it in a database or cloud platform. The collected data is cleaned and preprocessed to remove outliers and noise to ensure the accuracy and reliability of the data, and the data from different sensors are integrated to form complete information on the health status of the charging pile.

[0056] B. Status evaluation module: Comprehensively analyze the multi-source data of the charging pile and establish the status coefficient. By comparing the status coefficient with the health threshold, the health status of the charging pile is judged and corresponding strategies are formulated. The status coefficient is sent to the sorting module and the decision module, and the evaluation results are sent to the display module.

[0057] C. Sorting module: regularly obtain the average state coefficient of the charging piles, and sort all the charging piles from small to large according to the average state coefficient, generate a sorting table, and send the sorting table data to the display module.

[0058] D. Plan generation module: The administrator generates a dynamic plan of the charging station through the plan generation module according to user needs, and the dynamic plan is sent to the display module and the partition module;

[0059] D1. Administrators must first fully communicate with users to understand their specific requirements and expectations for dynamic floor plans, including display content, interactive functions, etc.

[0060] D2. The administrator needs to obtain the floor plan data of the charging station, usually a CAD file of the building floor plan or an electronic map in other formats;

[0061] D3. Preprocess the obtained plan view data, including data format conversion, coordinate system adjustment, data cleaning, etc., for subsequent processing;

[0062] D4. Add dynamic elements that need to be displayed on the floor plan, such as charging pile icons, etc., according to user needs;

[0063] D5. According to user needs, set the interactive functions that users can perform on the dynamic plan, such as zooming, dragging, and clicking on the charging pile to view detailed information;

[0064] D6. The administrator needs to use appropriate development tools and programming languages ​​to develop a dynamic floor plan generation module for charging stations based on user needs and designs;

[0065] D76. Integrate the pre-processed floor plan data and the designed dynamic elements into the generation module to ensure that the data and elements can be displayed and interacted correctly.

[0066] E. Partitioning module: Based on the dynamic floor plan information, the charging piles are divided into several charging areas, and the charging area information is sent to the display module and the decision module;

[0067] F. Decision-making module: After obtaining the usage frequency and status coefficient of the charging piles in the charging area, the efficiency indicators of the charging piles in the charging area are comprehensively analyzed, and corresponding decisions are made in combination with the big database. The decision information is sent to the display module.

[0068] G. Display module: used to display the charging pile evaluation results, ranking table, dynamic floor plan, charging area and decision together. The display module includes a dynamic floor plan display area, a ranking table display area and a suggestion area. The dynamic floor plan display area displays the boundary of the charging station and the location of each charging pile, and each charging pile is equipped with an indicator light to indicate the health status of the charging pile (for example, the charging pile is equipped with red and green indicators, when the health status of the charging pile is good, the green light corresponding to the charging pile is always on, and when the health status of the charging pile is poor, the red light corresponding to the charging pile is always on). The ranking table display area is used to display the dynamic ranking of the health status of the charging stations, and the suggestion area is used to display decision information.

[0069] The present application collects multi-source data related to the health status of charging piles through the data acquisition module, the status evaluation module comprehensively analyzes the multi-source data of the charging piles and establishes a status coefficient, judges the health status of the charging piles by comparing the status coefficient with the health threshold and formulates corresponding strategies, the sorting module regularly obtains the average status coefficient of the charging piles, and sorts all the charging piles from small to large according to the average status coefficient to generate a sorting table, and the administrator generates a dynamic floor plan of the charging station through the floor plan generation module according to user needs, and the display module displays the charging pile evaluation results, sorting table, dynamic floor plan, charging area and decision together, which not only comprehensively analyzes the health status of the charging piles and facilitates timely management, but also can select the charging pile maintenance order according to the status of the charging piles when regularly maintaining the charging piles, effectively improving the maintenance efficiency of the charging piles.

[0070] Embodiment 2: The status evaluation module comprehensively analyzes the multi-source data of the charging pile and establishes the status coefficient. By comparing the status coefficient with the health threshold, the health status of the charging pile is judged and corresponding strategies are formulated. The status coefficient is sent to the sorting module and the decision module, and the evaluation result is sent to the display module.

[0071] The status assessment module comprehensively analyzes the multi-source data of the charging pile and establishes the status coefficient. The multi-source data includes the volume floating coefficient of the charging interface material, the dynamic and static power loss index, the software error rate, and the environmental electromagnetic interference degree;

[0072] The volume floating coefficient of the charging interface material, the dynamic and static power loss index, the software error rate, and the environmental electromagnetic interference are comprehensively calculated to obtain the state coefficient ztx. The calculation expression is:

[0073]

[0074] Where, djs is the dynamic and static power loss index, jkf is the volume floating coefficient of the charging interface material, rjb is the software error rate, dcg is the environmental electromagnetic interference, and a 1 、a 2 、a 3 、a 4Dynamic and static power loss index, charging interface material volume floating coefficient, software error rate, environmental electromagnetic interference coefficient, and a 1 、a 2 、a 3 、a 4 Both are greater than 0.

[0075] After obtaining the state coefficient ztx, the state coefficient is compared with the health threshold. If the state coefficient ztx of the charging pile is ≥ the health threshold, it is judged that the health state of the charging pile can support the charging of the car. If the state coefficient ztx of the charging pile is < the health threshold, it is judged that the health state of the charging pile cannot support the charging of the car.

[0076] This application uses a status evaluation module to comprehensively analyze the multi-source data of the charging pile and establish a status coefficient. The multi-source data includes the volume floating coefficient of the charging interface material, the dynamic and static power loss index, the software error rate, and the environmental electromagnetic interference degree. The volume floating coefficient of the charging interface material, the dynamic and static power loss index, the software error rate, and the environmental electromagnetic interference degree are comprehensively calculated to obtain the status coefficient, thereby effectively improving the comprehensive data processing efficiency.

[0077] The calculation expression of the volume floating coefficient of the charging interface material is:

[0078]

[0079] TJ(t) is the real-time volume change of the charging interface material, [t x , t y ] is the period of temperature fluctuation warning at the charging interface. A temperature sensor is set at the charging interface and the temperature stability range wd is set min ~wd max , in the temperature stability range wd min ~wd max The charging interface material will not expand or contract significantly. At this time, the real-time volume change of the charging interface material is small. When the monitored temperature is not within the temperature stability range wd min ~wd max When the charging interface material is inside, the charging interface material will expand or contract significantly. At this time, the real-time volume change of the charging interface material is large. When the expansion of the charging interface material causes the real-time volume to increase, it will cause the charging interface to be difficult to insert into the car's charging port during charging, which is inconvenient to use. When the expansion of the charging interface material causes the real-time volume to decrease, it will cause the charging interface to have poor contact with the car's charging port after being inserted into the car's charging port, reducing the charging rate or even making it impossible to charge.

[0080] The calculation expression of dynamic and static power loss index is:

[0081]

[0082] In the formula, bzd is the static standard energy loss, bze is the dynamic standard energy loss, jtd is the static real-time energy loss, and dtd is the dynamic real-time energy loss. When the charging pile is idle, there will be a static energy loss to support the operation of the display device, etc. When the charging pile is in use, it will input current to the car and there will be a dynamic energy loss. The larger the dynamic and static energy loss index, the smaller the static real-time energy loss or the dynamic real-time energy loss, and the better the charging pile performance. The smaller the dynamic and static energy loss index, the larger the static real-time energy loss or the dynamic real-time energy loss, and the worse the charging pile performance.

[0083] The calculation expression of software error rate is:

[0084] rjb=bc / zsc

[0085] In the formula, bc is the number of software errors, and zsc is the monitoring time period. For example, the number of software errors of the charging pile can be monitored within 60 minutes to calculate the software error rate. The larger the software error rate, the more unstable the operation of the charging pile, which may cause frequent charging interruptions during the charging process.

[0086] The calculation expression of environmental electromagnetic interference degree dcg is:

[0087] dcg=dcx / sbx

[0088] In the formula, dcx is the environmental electromagnetic interference signal strength, sbx is the equipment working signal strength, the environmental electromagnetic interference signal strength indicates the electromagnetic interference signal power in the environment, and the equipment working signal strength indicates the signal power generated when the equipment is working normally. The greater the environmental electromagnetic interference, the following effects will be brought to the charging pile:

[0089] 1) Unstable performance: High electromagnetic interference may cause interference to the electronic components of the charging pile, resulting in unstable performance of the charging pile, which may cause abnormalities or failures;

[0090] 2) Increased failures: Charging piles are susceptible to interference in high electromagnetic interference environments, which increases the risk of failures;

[0091] 3) Data transmission errors: High electromagnetic interference may cause communication problems between the charging pile and the background management system, affecting the accuracy of data transmission;

[0092] 4) Safety hazards: In a high electromagnetic interference environment, the protection measures of the charging pile may be interfered with, thereby increasing electrical safety hazards.

[0093] The sorting module periodically obtains the average state coefficient of the charging piles, and sorts all the charging piles from small to large according to the average state coefficient, generates a sorting table, and sends the sorting table data to the display module.

[0094] Specifically:

[0095] In this application, the status coefficient is obtained every 60 minutes, and the sorting module obtains the average status coefficient of the charging pile every 30 days, specifically:

[0096] Get all status coefficients of all charging piles;

[0097] Calculate the average state coefficient of each charging pile;

[0098] All charging piles are sorted from small to large according to the average state coefficient of each charging pile to generate a sorting table. The sorting table data is sent to the display module. When all charging piles are maintained, the maintenance personnel select the maintenance order of the charging piles according to the positive order of the sorting table, so as to give priority to maintaining the charging piles with poor health status.

[0099] Embodiment 3: The partitioning module divides the charging pile into several charging areas based on the dynamic plan information, and the charging area information is sent to the display module and the decision module, including the following steps:

[0100] 1) Obtain dynamic floor plan information: First, it is necessary to obtain the dynamic floor plan information of the area where the charging pile is located; the dynamic floor plan includes the location and layout of the charging pile, as well as the surrounding buildings, roads and other information;

[0101] 2) Determine the zoning rules: Next, determine the rules for dividing the charging piles into charging areas; the zoning rules can be determined according to different needs, such as the density, distance, power supply and other factors of the charging piles;

[0102] 3) Calculate the distance between charging piles: Calculate the distance between charging piles based on the dynamic floor plan information; this can help determine which charging piles should belong to the same charging area;

[0103] 4) Determine the scope of the charging area: divide the charging piles into several charging areas according to the calculated distance between the charging piles; usually, charging piles that are close to each other are classified into the same charging area;

[0104] 5) Marking and recording: Mark and record each charging area for subsequent management and maintenance; different charging areas can be marked with numbers or names;

[0105] 6) Optimization and division: Certain optimization and adjustments can be made to ensure that the charging area is divided reasonably and to avoid charging piles being too dense or too sparse;

[0106] 7) Real-time update: Since the dynamic floor plan information may change over time, it needs to be updated regularly in real time to maintain the accuracy of the charging area division.

[0107] After obtaining the usage frequency and status coefficient of the charging piles in the charging area, the decision module comprehensively analyzes the efficiency indicators of the charging piles in the charging area, and makes corresponding decisions in combination with the big database, and the decision information is sent to the display module.

[0108] After the decision module obtains the usage frequency and status coefficient of the charging piles in the charging area, the comprehensive analysis of the charging pile efficiency indicators in the charging area includes the following steps:

[0109] Obtain the usage frequency and status coefficient of charging piles in each charging area over a period of time;

[0110] Obtain the number of times when the state coefficient is ≥ the health threshold and the number of times when the state coefficient is < the health threshold, and calculate the good-bad ratio of the charging pile during a period of operation. The calculation expression is: hb = hz2 / hz1, where hb is the good-bad ratio of the charging pile during a period of operation, hz1 is the number of times when the state coefficient is ≥ the health threshold, and hz2 is the number of times when the state coefficient is < the health threshold;

[0111] The efficiency index of the charging pile in the charging area is calculated by the usage frequency and the good-bad ratio of the charging pile during a period of operation. The expression is:

[0112]

[0113] Where pl is the usage frequency of the charging pile in the charging area, hb is the good-bad ratio of the charging pile during a period of operation, and the calculation expression for the usage frequency of the charging pile in the charging area is:

[0114]

[0115] In the formula, cdz i is the number of times the i-th charging pile is used, and T is the operating time period of the charging pile.

[0116] The present application calculates the efficiency index of the charging piles in the charging area by using the frequency of use and the good-bare ratio of the charging piles during a period of operation, and when the efficiency index of the charging piles in the charging area is less than the efficiency threshold and the efficiency of the charging area is judged to be poor, the charging area is managed accordingly, thereby optimizing the layout and facilities of the charging area, providing more convenient and efficient charging services, and reducing the operating costs of the charging piles.

[0117] If the charging pile efficiency index in the charging area is less than the efficiency threshold, it is judged that the efficiency of the charging area is poor. If the charging pile efficiency index in the charging area is greater than or equal to the efficiency threshold, it is judged that the efficiency of the charging area is good.

[0118] When it is judged that the efficiency of the charging area is poor, the following management measures need to be taken:

[0119] 1) Adjust the number or power of charging piles to meet actual needs;

[0120] 2) Move some charging piles to more suitable locations to improve the utilization rate of charging piles;

[0121] 3) Cancel the charging area directly.

[0122] The above formulas are all dimensionless and numerical calculations. The formula is a formula for the most recent real situation obtained by collecting a large amount of data and performing software simulation. The preset parameters in the formula are set by technicians in this field according to actual conditions.

[0123] The above embodiments can be implemented in whole or in part by software, hardware, firmware or any other combination. When implemented by software, the above embodiments can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions can be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired or wireless (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium can be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium can be a solid-state hard disk.

[0124] It should be understood that the term "and / or" in this article is only a description of the association relationship of associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. A and B can be singular or plural. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship, but it may also indicate an "and / or" relationship. Please refer to the context for specific understanding.

[0125] In this application, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refers to any combination of these items, including any combination of single or plural items. For example, at least one of a, b, or c can be represented by: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple.

[0126] It should be understood that in the various embodiments of the present application, the size of the serial numbers of the above-mentioned processes does not mean the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present application.

[0127] Those of ordinary skill in the art will appreciate that the units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0128] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0129] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0130] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0131] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0132] If the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium and includes several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

[0133] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. Intelligent management system for charging piles based on data analysis, characterized by: It includes data acquisition module, status assessment module, sorting module, floor plan generation module, partitioning module, decision module and display module; Data acquisition module: used to collect multi-source data related to the health status of charging piles; Status evaluation module: Comprehensively analyze the multi-source data of the charging pile and establish the status coefficient. By comparing the status coefficient with the health threshold, the health status of the charging pile is judged and corresponding strategies are formulated. The multi-source data includes the volume floating coefficient of the charging interface material. The calculation expression is: TJ(t) is the real-time volume change of the charging interface material, [t x , t y ] is the period of temperature fluctuation warning at the charging interface; Sorting module: regularly obtain the average state coefficient of the charging piles, and sort all the charging piles from small to large according to the average state coefficient to generate a sorting table; Plan generation module: The administrator generates a dynamic plan of the charging station through the plan generation module according to user needs; Partitioning module: divides the charging piles into several charging areas based on dynamic floor plan information; Decision-making module: After obtaining the usage frequency and status coefficient of the charging piles in the charging area, comprehensively analyze the efficiency indicators of the charging piles in the charging area, and make corresponding decisions based on the big database; Display module: used to display charging pile evaluation results, ranking tables, dynamic floor plans, charging areas and decisions.

2. The charging pile intelligent management system based on data analysis according to claim 1 is characterized in that: The state evaluation module comprehensively analyzes multi-source data of the charging pile and establishes a state coefficient. The multi-source data also includes dynamic and static power loss index, software error rate and environmental electromagnetic interference.

3. The charging pile intelligent management system based on data analysis according to claim 2 is characterized in that: The state evaluation module comprehensively calculates the volume floating coefficient of the charging interface material, the dynamic and static power loss index, the software error rate, and the environmental electromagnetic interference to obtain the state coefficient ztx, and the calculation expression is: Wherein, djs is the dynamic and static power loss index, jkf is the volume floating coefficient of the charging interface material, rjb is the software error rate, dcg is the environmental electromagnetic interference degree, a1, a2, a3, a4 are the proportional coefficients of the dynamic and static power loss index, the volume floating coefficient of the charging interface material, the software error rate, and the environmental electromagnetic interference degree, and a1, a2, a3, a4 are all greater than 0.

4. The charging pile intelligent management system based on data analysis according to claim 3 is characterized by: After the state evaluation module obtains the state coefficient ztx, the state coefficient is compared with the health threshold. If the state coefficient ztx of the charging pile is ≥ the health threshold, it is determined that the health state of the charging pile supports vehicle charging. If the state coefficient ztx of the charging pile is < the health threshold, it is determined that the health state of the charging pile does not support vehicle charging.

5. The charging pile intelligent management system based on data analysis according to claim 4 is characterized in that: The calculation expression of the dynamic and static power loss index is: Where bzd is the static standard energy loss, bze is the dynamic standard energy loss, jtd is the static real-time energy loss, and dtd is the dynamic real-time energy loss.

6. The charging pile intelligent management system based on data analysis according to claim 5 is characterized by: The calculation expression of the software error rate is: rjb=bc / zsc In the formula, bc is the number of software error reports, and zsc is the monitoring time period; The calculation expression of environmental electromagnetic interference degree dcg is: dcg=dcx / sbx In the formula, dcx is the environmental electromagnetic interference signal strength, and sbx is the equipment working signal strength.

7. The charging pile intelligent management system based on data analysis according to claim 6 is characterized by: The sorting module generates a sorting table comprising the following steps: Obtain all status coefficients of all charging piles every 30 days; Calculate the average state coefficient of each charging pile; Sort all charging piles according to the average state coefficient of each charging pile from small to large to generate a sorting table.

8. The charging pile intelligent management system based on data analysis according to claim 7 is characterized in that: After the decision module obtains the usage frequency and status coefficient of the charging piles in the charging area, the comprehensive analysis of the charging pile efficiency index in the charging area includes the following steps: Obtain the usage frequency and status coefficient of charging piles in each charging area over a period of time; Obtain the number of times when the state coefficient is ≥ the health threshold and the number of times when the state coefficient is < the health threshold, and calculate the good-bad ratio of the charging pile during a period of operation. The calculation expression is: hb = hz2 / hz1, where hb is the good-bad ratio of the charging pile during a period of operation, hz1 is the number of times when the state coefficient is ≥ the health threshold, and hz2 is the number of times when the state coefficient is < the health threshold; The efficiency index of the charging pile in the charging area is calculated by the usage frequency and the good-bad ratio of the charging pile during a period of operation. The expression is: Where pl is the usage frequency of the charging pile in the charging area, and hb is the good-bad ratio of the charging pile during operation for a period of time; If the charging pile efficiency index in the charging area is less than the efficiency threshold, it is judged that the efficiency of the charging area is poor. If the charging pile efficiency index in the charging area is greater than or equal to the efficiency threshold, it is judged that the efficiency of the charging area is good.

9. The charging pile intelligent management system based on data analysis according to claim 8 is characterized by: The calculation expression for the usage frequency of the charging piles in the charging area is: In the formula, cdz i is the number of times the i-th charging pile is used, and T is the operating time period of the charging pile.

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