Charging pile monitoring system based on artificial intelligence

Abstract

The invention discloses a charging pile monitoring system based on artificial intelligence, which relates to the field of charging pile monitoring and comprises a data acquisition module, a user demand analysis module, a charging index analysis module, a temperature monitoring and adjusting module, a charging state monitoring and early warning module, a man-machine interaction platform and a database. A charging demand alternative set, a temperature state value and a charging state value of a charging pile corresponding to a charging pile user are obtained by judging and analyzing a charging pile user behavior characteristic demand parameter and a charging pile user charging association demand parameter and then counting and analyzing a charging pile temperature state parameter and a charging pile charging state parameter; the charging pile can be ensured to operate in a proper temperature range interval, the charging pile can immediately remind a worker in an abnormal working state, the working pressure and heating of internal elements of the charging pile are reduced in a low charging peak period, the stability of a power grid of the charging pile is ensured in a high charging peak period, and the service life of the charging pile is prolonged.

Description

Technical Field

[0001] The present invention relates to the technical field of charging pile monitoring, and in particular to a charging pile monitoring system based on artificial intelligence. Background Art

[0002] With the continuous development of the economy and the increasing emphasis on sustainable development, energy transformation has become an inevitable trend. As a clean and convenient means of transportation, electric vehicles have become an increasingly popular choice, but the development of electric vehicles is also inseparable from charging infrastructure. An artificial intelligence-based charging pile monitoring system has emerged.

[0003] The current charging pile monitoring system cannot comprehensively consider the charging behavior characteristics and charging-related needs of charging pile users when in operation, and cannot adjust the temperature of the charging pile when the charging pile is in operation, resulting in the burning of the charging pile from time to time.

[0004] The current charging pile monitoring system is unable to monitor the charging status of the charging pile when it is in operation, resulting in the inability to adjust the abnormal charging status in time, which greatly increases the incidence of safety accidents. At the same time, the current charging piles are unable to make corresponding adjustments according to the low and peak periods of electricity consumption when charging, resulting in idle waste of the power grid and instability of the charging pile power grid.

[0005] In order to solve the above defects, a technical solution is now provided. Summary of the invention

[0006] In order to solve the technical problems raised by the above background technology, the present invention is proposed. An embodiment of the present invention provides a charging pile monitoring system based on artificial intelligence.

[0007] The purpose of the present invention can be achieved by the following technical solutions:

[0008] A charging pile monitoring system based on artificial intelligence includes a data acquisition module, a user demand analysis module, a charging index analysis module, a temperature monitoring and adjustment module, a charging status monitoring and early warning module, a human-computer interaction platform and a database.

[0009] The user demand analysis module is used to receive the charging pile user behavior characteristic demand parameters and the charging pile user charging-related demand parameters, and perform determination and analysis of the user behavior characteristic demand and the charging pile charging-related demand, and send them to the charging status monitoring and early warning module;

[0010] The charging index analysis module is used to receive the temperature state parameters of the charging pile and the charging state parameters of the charging pile, and analyze them to obtain the temperature state value of the charging pile and the charging state value of the charging pile, and send them to the temperature monitoring and adjustment module and the charging state monitoring and early warning module;

[0011] The temperature monitoring and adjustment module counts and analyzes the temperature status values ​​of the charging piles and automatically adjusts the temperature of the charging piles;

[0012] The charging status monitoring and early warning module counts and analyzes the charging status value of the charging pile, generates a corresponding signal, and adjusts the working power of the charging pile accordingly.

[0013] Furthermore, the specific operation steps for determining and analyzing the behavior characteristic requirements of charging pile users and the charging-related requirements of charging pile users are as follows:

[0014] Obtain the charging records of each charging pile user, where the charging records include the number of charging times and the start and end times of each charging. Calculate the time difference between the start and end times of charging to obtain the charging time of the charging pile user, recorded as Cs i , charging times, recorded as Cc i , i is the number of the charging pile user, where i is a positive integer; the charging start time is taken as the charging time of this time; the coordinate system is constructed with time as the horizontal axis of the two-dimensional coordinate system and the charging time as the vertical axis, the charging time corresponding to the charging time is plotted, and a broken line is used to connect them to obtain a charging record change broken line graph, and the slope of two adjacent points is calculated and recorded as r is the number of times the charging pile user charges, where r ranges from 1, 2, 3, ...R, R is the maximum value of the charging number, which is a positive integer, and the average of all slopes is taken, which is recorded as The time difference between the charging start time and the last charging end time is calculated to obtain the charging time interval of the charging pile user, which is recorded as According to the set formula Calculate to get the charging fluctuation value Cb of the charging pile user i ;

[0014] According to the set formula Get the charging behavior characteristic demand index TH of the charging pile user i , where a1, a2, a3, a4 are the set weight factor coefficients, e is a constant with a specific value of 2.718, Z1, Z2, Z3 are the set charging pile user's reference charging time, reference slope, and reference charging times;

[0015] Set the gradient comparison intervals T1, T2 and T3 of the charging behavior characteristic demand index, and substitute the charging behavior characteristic demand index of each charging pile user into the preset gradient comparison intervals T1, T2 and T3 for comparative analysis, wherein the comparison intervals T1, T2 and T3 increase in a gradient manner;

[0016] When the charging behavior characteristic demand index is within the preset gradient comparison interval T1, the charging behavior characteristic value of the charging pile user is recorded as x1 points; when the charging behavior characteristic demand index is within the preset gradient comparison interval T2, the charging behavior characteristic value of the charging pile user is recorded as x2 points; when the charging behavior characteristic demand index is within the preset gradient comparison interval T3, the charging behavior characteristic value of the charging pile user is recorded as x3 points, where x1<x2<x3;

[0017] The remaining power of the charging pile user's vehicle is obtained through the power detection sensor, which is recorded as Sd i ; Get the vehicle types of charging pile users, which can be divided into electric buses, electric taxis, electric family cars, hybrid electric vehicles and other vehicles, corresponding to w1, w2, w3, w4, w5 values, where w5<w4<w3<w2<w1, and recorded as Cz i ; Get the distance between the charging pile user’s home address and company address, recorded as Jg i ; According to the set formula The charging-related demand index of the charging pile user is obtained, where f1, f2, and f3 are the set weight factor coefficients, Sd′, Cz′, and Jg′ represent the set reference remaining power of the charging pile user's vehicle, the reference vehicle type value, and the reference distance between the home address and the company address, respectively, and ΔSd, ΔCz, and ΔJg represent the set reference remaining power difference, the reference vehicle type value difference, and the reference distance difference between the home address and the company address, respectively;

[0018] Set a complete reference threshold TH1 for the charging-related demand index, and substitute the charging-related demand indexes of the charging pile users into the preset complete reference threshold TH1 for comparative analysis;

[0019] When the charging pile user's charging-related demand index is less than the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y1 points; when the charging pile user's charging-related demand index is equal to the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y2 points; when the charging pile user's charging-related demand index is greater than the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y3 points, where y1<y2<y3;

[0020] The score value of the charging behavior characteristic demand data item of each charging pile user is added to the score value of the charging associated demand index data item to obtain the total score value of each charging pile user, and each charging pile user is graded according to the total score value. When the total score value is x3+y3 or x2+y3 or x3+y2, the corresponding charging pile user is divided into the first-level charging demand candidate set B1; when the total score value is x2+y2 or x1+y3 or x3+y1, the corresponding charging pile user is divided into the second-level charging demand candidate set B2; when the total score value is x1+y2 or x2+y1, the corresponding charging pile user is divided into the third-level charging demand candidate set B3; when the total score value is x1+y1, the corresponding charging pile user is divided into the fourth-level charging demand candidate set B4;

[0021] The obtained first-level charging demand candidate set B1, second-level charging demand candidate set B2, third-level charging demand candidate set B3 and fourth-level charging demand candidate set B4 are sent to the charging status monitoring and early warning module.

[0022] Furthermore, the specific operation steps of the temperature status value of the charging pile are as follows:

[0023] The temperature of the charging pile power module is measured by a thermocouple. The measurement time is used as the horizontal axis and the temperature of the power module is used as the vertical axis to establish a two-dimensional coordinate system. The temperature points corresponding to each measurement time are plotted. The points are connected with a broken line to obtain a temperature line. The slope of each temperature line value and the angle with the horizontal line are calculated. When the angle between the temperature line value and the horizontal line is an acute angle, it is recorded as the first slope and recorded as Wy t , t is the number of the measurement time, where t ranges from 1, 2, 3, ... T, T represents the maximum value of the number, and is a positive integer. When the angle between the temperature value line and the horizontal line is an obtuse angle, it is recorded as the second slope and is recorded as We t ; Read the highest temperature value in the line graph, record it as Tg, read the lowest temperature value in the line graph, record it as Tx; Calculate to get the temperature state value Wp of the charging pile, where b1, b2, b3, and b4 are the set proportional coefficients respectively. are the first slope average values ​​of the temperature corresponding to different measurement moments, is the average value of the second slope of the temperature corresponding to different measurement times, is the average value of the temperature slope corresponding to different measurement times, BW is the standard value of the temperature slope corresponding to different measurement times, Tg′ is the maximum reference value of the temperature, and Tx′ is the minimum reference value of the temperature.

[0024] Furthermore, the specific operation steps of the charging pile charging status value are as follows:

[0025] The actual electrical operating parameters of the charging pile are obtained, including the current value and voltage value of the charging pile; the real-time current value and voltage value of the charging pile are displayed through the curve of the coordinate system, and a standard current value line and a standard voltage value line are respectively established in the coordinate system, and the closed area formed by the two curves and the two standard lines is measured respectively, and the reference value is accumulated and used as the standard of the actual electrical operating parameters of the charging pile; the energy consumption of the charging pile can be measured by the smart electric energy meter, and the active power value is calculated according to the measurement time; the reference value, active power value and temperature state value are normalized, and an ellipse is constructed with the reference value and active power value as the major axis and minor axis respectively, and a cone is constructed with the temperature state value as the high axis, and the volume of the cone is extracted as a custom result, which is calibrated as the charging state value of the charging pile.

[0026] Furthermore, the specific operation steps for statistics and analysis of the temperature status values ​​of the charging pile are as follows:

[0027] The operating temperature value of the charging pile is divided into n temperature values, each temperature value corresponds to a value range, Q1 (0, q1), Q2 (q1, q2), Q3 (q2, q3)...Qn (qn-1, qn), where Q1, Q2, Q3...Qn are specific temperature value numbers, q1, q2, q3...qn are temperature values, and the temperature state values ​​corresponding to various charging piles are matched with the value range of the temperature value. If the temperature state value corresponding to the charging pile is within the value range of the temperature value, then the value range is the adjusted temperature value for the operation of the charging pile, and the charging pile automatically adjusts the temperature according to the adjusted temperature value.

[0028] Furthermore, the specific operation steps for statistics and analysis of charging pile charging status values ​​are as follows:

[0029] Setting gradient reference thresholds Yu1, Yu2, Yu3, and Yu4 for the charging status value of the charging pile, and comparing and analyzing the charging status value of the charging pile with the preset gradient reference thresholds Yu1, Yu2, Yu3, and Yu4, wherein the gradient reference thresholds Yu1, Yu2, Yu3, and Yu4 increase in a gradient manner;

[0030] When the charging state value is less than the preset gradient reference threshold value Yu1, an abnormal signal of the working current and voltage of the charging pile is generated, and sent to the charging pile human-computer interaction platform for display in the form of a description of "the charging pile is in an abnormal state of working current and voltage being too small, please ask the staff to troubleshoot the line fault";

[0031] When the charging state value is between the preset gradient reference thresholds Yu1 and Yu2, a charging pile underutilization recognition signal is generated, and the difference with the reference threshold Yu2 is calculated to obtain a custom value, the custom value is multiplied by the charging pile working power conversion coefficient, and the charging demand candidate set is matched to obtain the working power adjustment value corresponding to the charging demand candidate set, which is adjusted to the first-level charging demand candidate set B1 multiplied by the adjustment coefficient m1, the second-level charging demand candidate set B2 multiplied by the adjustment coefficient m2, the third-level charging demand candidate set B3 multiplied by the adjustment coefficient m3, the fourth-level charging demand candidate set B4 multiplied by the adjustment coefficient m4, and the charging piles not in use multiplied by the adjustment coefficient m5, where m1>m2>m3>m4>m5;

[0032] When the charging state value is between the preset gradient reference thresholds Yu2 and Yu3, a normal state signal of the charging pile is generated, and the charging pile has no operation;

[0033] When the charging state value is between the preset gradient reference thresholds Yu3 and Yu4, a charging pile is generated to be in a high charging load recognition signal, and the difference with the reference threshold Yu3 is calculated to obtain a custom value, the custom value is multiplied by the charging pile working power conversion coefficient, and the charging demand candidate set is matched to obtain the working power adjustment value corresponding to the charging demand candidate set, which is adjusted to the first-level charging demand candidate set B1 multiplied by the adjustment coefficient d1, the second-level charging demand candidate set B2 multiplied by the adjustment coefficient d2, the third-level charging demand candidate set B3 multiplied by the adjustment coefficient d3, and the fourth-level charging demand candidate set B4 multiplied by the adjustment coefficient d4, where d1>d2>d3>d4;

[0034] When the charging status value is greater than the preset gradient reference threshold Yu4, an abnormal signal of excessive working current and voltage of the charging pile is generated and sent to the charging pile human-computer interaction platform for display with the text description "The charging pile is working in an abnormal state of excessive working current and voltage, please ask staff to troubleshoot the line fault."

[0035] Compared with the prior art, the present invention has the following beneficial effects:

[0036] 1. The present invention collects the demand parameters of charging pile user behavior characteristics and charging pile charging-related demand parameters, and performs judgment and analysis on them to obtain alternative sets of charging demands at various levels, and integrates the user situations of charging piles in various situations, so that the system can more accurately monitor charging users at different levels.

[0037] 2. The present invention obtains the charging status value of the charging pile by statistics and analysis of the current value, voltage value, active power and temperature status value of the charging pile operation, and detects, warns and adjusts the charging status value of the charging pile, which is beneficial to reducing the working pressure and heat generation of the internal components of the charging pile during the low-peak charging period, alleviating the idle waste of the power grid during the low-peak period, and ensuring the stability of the charging pile power grid during the peak charging period, reducing the occurrence of safety accidents, reminding the staff when the charging pile is working abnormally, and promptly troubleshooting the corresponding line faults.

[0038] 3. The present invention obtains the temperature status value by detecting the temperature of the charging pile and analyzes it. The charging pile automatically adjusts the temperature according to the adjusted temperature value, thereby ensuring that the temperature of the charging pile is within a suitable range, and also greatly reducing the incidence of safety accidents. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. The following drawings are not intentionally scaled to the actual size, and the focus is on illustrating the main purpose of the present invention.

[0040] Figure 1 is a system block diagram of the present invention;

[0041] Figure 2 It is a charging record change line graph of the present invention;

[0042] Figure 3 It is a temperature line graph of the present invention;

[0043] Figure 4 It is a schematic diagram of a vertebral body of the present invention. DETAILED DESCRIPTION

[0044] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work also fall within the scope of protection of the present invention.

[0045] like Figure 1 As shown, a charging pile monitoring system based on artificial intelligence includes a data acquisition module, a user demand analysis module, a charging index analysis module, a temperature monitoring and adjustment module, a charging status monitoring and early warning module, a human-computer interaction platform and a database.

[0046] The data acquisition module is used to collect the demand parameters of the user behavior characteristics of the charging pile, the charging-related demand parameters of the charging pile user, the temperature state parameters of the charging pile and the charging state parameters of the charging pile, and send them to the user demand analysis module and the charging index analysis module. The demand parameters of the user behavior characteristics of the charging pile include the charging time, charging times and charging time interval of the user of the charging pile; the charging-related demand parameters of the charging pile include the remaining power of the user's vehicle, the type of vehicle of the charging pile user and the distance between the user's home address and the company address; the temperature state parameters of the charging pile include the temperature value of the charging pile power module; the charging state parameters of the charging pile include the real-time current value, voltage value and active power value of the charging pile operation.

[0047] The user demand analysis module is used to receive the charging pile user behavior characteristic demand parameters and the charging pile user charging-related demand parameters, and to perform determination and analysis of the charging pile user behavior characteristic demand and the charging pile charging-related demand, and send them to the charging status monitoring and early warning module. The specific analysis is as follows:

[0048] Obtain the charging records of each charging pile user, where the charging records include the number of charging times and the start and end times of each charging. Calculate the time difference between the start and end times of charging to obtain the charging time of the charging pile user, recorded as Cs i , charging times, recorded as Cc i , i is the number of the charging pile user, where i is a positive integer; the charging start time is taken as the current charging time; Figure 2 As shown, a coordinate system is constructed with time as the horizontal axis of the two-dimensional coordinate system and charging time as the vertical axis. The charging time corresponding to the charging time is plotted and connected with a broken line to obtain a charging record change line graph. The slope of two adjacent points is calculated and recorded as r is the number of times the charging pile user charges, where r ranges from 1, 2, 3, ...R, R is the maximum value of the charging number, which is a positive integer, and the average of all slopes is taken, which is recorded as The time difference between the charging start time and the last charging end time is calculated to obtain the charging time interval of the charging pile user, which is recorded as According to the set formula Calculate to get the charging fluctuation value Cb of the charging pile user i .

[0049] According to the set formula Get the charging behavior characteristic demand index TH of the charging pile user i, where a1, a2, a3, and a4 are the set weight factor coefficients, and their sizes are custom settings, with values ​​of 10.1, 10.2, 16.2, and 9.8 respectively. The weight factor coefficients are used to balance the weights of each data in the formula calculation, thereby promoting the accuracy of the calculation results. e is a constant with a specific value of 2.718. Z1, Z2, and Z3 are the reference charging time, reference slope, and reference charging times of the set charging pile users. It can be seen from the formula that the longer the charging time, the closer the charging time slope of the two adjacent points is to the reference slope, the more charging times, and the greater the charging behavior characteristic demand index.

[0050] Set the gradient comparison intervals T1, T2 and T3 of the charging behavior characteristic demand index, and substitute the charging behavior characteristic demand index of each charging pile user into the preset gradient comparison intervals T1, T2 and T3 for comparative analysis, wherein the comparison intervals T1, T2 and T3 increase in a gradient manner;

[0051] It should be noted that, assuming that T1, T2 and T3 increase in a gradient of 10, when the comparison interval T1 is set to [10, 20), the comparison interval T2 is [20, 30), and the comparison interval T3 is [30, 40), and the interval value settings of the comparison intervals T1, T2 and T3, as well as the setting of the gradient increase value, are all specifically set by those skilled in the art in specific cases;

[0052] When the charging behavior characteristic demand index is within the preset gradient comparison interval T1, the charging behavior characteristic value of the charging pile user is recorded as x1 points; when the charging behavior characteristic demand index is within the preset gradient comparison interval T2, the charging behavior characteristic value of the charging pile user is recorded as x2 points; when the charging behavior characteristic demand index is within the preset gradient comparison interval T3, the charging behavior characteristic value of the charging pile user is recorded as x3 points, where x1<x2<x3;

[0053] The remaining power of the charging pile user's vehicle is obtained through the power detection sensor, which is recorded as Sd i ; Get the vehicle types of charging pile users, which can be divided into electric buses, electric taxis, electric family cars, hybrid electric vehicles and other vehicles, corresponding to w1, w2, w3, w4, w5 values, where w5<w4<w3<w2<w1, and recorded as Cz i ; Get the distance between the charging pile user’s home address and company address, recorded as Jg i ; According to the set formula The charging-related demand index of the charging pile user is obtained, where f1, f2, and f3 are the set weight factor coefficients, which are custom settings and take values ​​of 5.2, 5.7, and 9.2, respectively. Sd′, Cz′, and Jg′ represent the reference remaining power of the charging pile user’s vehicle, the reference vehicle type value, and the reference distance between the home address and the company address, respectively. ΔSd, ΔCz, and ΔJg represent the reference remaining power difference, the reference vehicle type value difference, and the reference distance difference between the home address and the company address, respectively. It can be seen from the formula that the smaller the remaining power, the larger the vehicle type value, the larger the distance between the home address and the company address, and the larger the charging-related demand index.

[0054] Set a complete reference threshold TH1 for the charging-related demand index, and substitute the charging-related demand indexes of the charging pile users into the preset complete reference threshold TH1 for comparative analysis;

[0055] When the charging pile user's charging-related demand index is less than the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y1 points; when the charging pile user's charging-related demand index is equal to the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y2 points; when the charging pile user's charging-related demand index is greater than the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y3 points, where y1<y2<y3;

[0056] The score value of the charging behavior characteristic demand data item of each charging pile user is added to the score value of the charging associated demand index data item to obtain the total score value of each charging pile user, and each charging pile user is graded according to the total score value. When the total score value is x3+y3 or x2+y3 or x3+y2, the corresponding charging pile user is divided into the first-level charging demand candidate set B1; when the total score value is x2+y2 or x1+y3 or x3+y1, the corresponding charging pile user is divided into the second-level charging demand candidate set B2; when the total score value is x1+y2 or x2+y1, the corresponding charging pile user is divided into the third-level charging demand candidate set B3; when the total score value is x1+y1, the corresponding charging pile user is divided into the fourth-level charging demand candidate set B4;

[0057] The obtained first-level charging demand candidate set B1, second-level charging demand candidate set B2, third-level charging demand candidate set B3 and fourth-level charging demand candidate set B4 are sent to the charging status monitoring and early warning module;

[0058] The charging index analysis module is used to receive the temperature status parameters of the charging pile and the charging status parameters of the charging pile, and analyze them to obtain the temperature status value of the charging pile and the charging status value of the charging pile, the temperature monitoring and adjustment module and the charging status monitoring and early warning module, as follows:

[0059] The temperature of the charging pile power module is measured by a thermocouple. The measured time is used as the horizontal axis and the temperature of the power module is used as the vertical axis. A two-dimensional coordinate system is established. The temperature points corresponding to each measurement time are plotted, and the temperature lines are obtained by connecting the points with broken lines, such as Figure 3 As shown, the slope of each temperature line value and the angle with the horizontal line are calculated. When the angle between the temperature line value and the horizontal line is an acute angle, it is recorded as the first slope and recorded as Wy t , t is the number of the measurement time, where t ranges from 1, 2, 3, ... T, T represents the maximum value of the number, and is a positive integer. When the angle between the temperature value line and the horizontal line is an obtuse angle, it is recorded as the second slope and is recorded as We t ; Read the highest temperature value in the line graph, record it as Tg, read the lowest temperature value in the line graph, record it as Tx; Calculate to get the temperature state value Wp of the charging pile, where b1, b2, b3, and b4 are set proportional coefficients, and their sizes are custom settings, with values ​​of 1.2, 1.6, 2.5, and 1.8, respectively. are the first slope average values ​​of the temperature corresponding to different measurement moments, is the average value of the second slope of the temperature corresponding to different measurement times, is the average value of the slope of the temperature corresponding to different measurement times, BW is the standard value of the temperature slope corresponding to different measurement times, the maximum reference value of Tg' temperature, and the minimum reference value of Tx' temperature; it should be noted that when the temperature data change slope of the charging pile is more concentrated, the maximum and minimum temperature values ​​are closer to the reference value, the greater the temperature state value;

[0060] Analyze the charging status of the charging pile equipment: obtain the actual electrical operating parameters of the charging pile, including the current value and voltage value of the charging pile; display the real-time current value and voltage value of the charging pile through the curve of the coordinate system, and establish a standard current value line and a standard voltage value line in the coordinate system respectively, measure the closed area formed by the two curves and the two standard lines respectively, and sum and accumulate to obtain the reference deviation value, which is used as the standard of the actual electrical operating parameters of the charging pile; the energy consumption of the charging pile can be measured by the smart electric energy meter, and the active power value can be calculated according to the measurement time; after the reference deviation value, active power value and temperature state value are normalized, an ellipse is constructed with the reference deviation value and active power value as the major axis and minor axis respectively, and a cone is constructed with the temperature state value as the high axis, and the volume of the cone is extracted. The numerical value of the volume is calibrated as the charging state value of the charging pile, such as Figure 4 shown.

[0061] The temperature monitoring and adjustment module counts and analyzes the temperature status values ​​of the charging piles and automatically adjusts the temperature of the charging piles. The specific analysis is as follows:

[0062] The operating temperature value of the charging pile is divided into n temperature values, each temperature value corresponds to a value range, Q1 (0, q1), Q2 (q1, q2), Q3 (q2, q3)...Qn (qn-1, qn), where Q1, Q2, Q3...Qn are specific temperature value numbers, q1, q2, q3...qn are temperature values, and the temperature state values ​​corresponding to various charging piles are matched with the value range of the temperature value. If the temperature state value corresponding to the charging pile is within the value range of the temperature value, then the value range is the adjusted temperature value for the operation of the charging pile, and the charging pile automatically adjusts the temperature according to the adjusted temperature value.

[0063] The charging status monitoring and early warning module counts and analyzes the charging status values ​​of the charging piles, generates corresponding signals, and adjusts the working power of the charging piles accordingly. The specific analysis is as follows:

[0064] Setting gradient reference thresholds Yu1, Yu2, Yu3, and Yu4 for the charging status value of the charging pile, and comparing and analyzing the charging status value of the charging pile with the preset gradient reference thresholds Yu1, Yu2, Yu3, and Yu4, wherein the gradient reference thresholds Yu1, Yu2, Yu3, and Yu4 increase in a gradient manner;

[0065] When the charging state value is less than the preset gradient reference threshold value Yu1, an abnormal signal of the working current and voltage of the charging pile is generated, and sent to the charging pile human-computer interaction platform for display in the form of a description of "the charging pile is in an abnormal state of working current and voltage being too small, please ask the staff to troubleshoot the line fault";

[0066] When the charging state value is between the preset gradient reference thresholds Yu1 and Yu2, a charging pile underutilization recognition signal is generated, and the difference with the reference threshold Yu2 is calculated to obtain a custom value, which is multiplied by the charging pile working power conversion coefficient, and matched with the charging demand candidate set to obtain the working power adjustment value corresponding to the charging demand candidate set, which is specifically adjusted to multiply the first-level charging demand candidate set B1 by the adjustment coefficient m1, the second-level charging demand candidate set B2 by the adjustment coefficient m2, and the third-level charging demand candidate set B3 by the adjustment coefficient m3. The fourth-level charging demand alternative set B4 is multiplied by the adjustment coefficient m4, and the charging piles not in use are multiplied by the adjustment coefficient m5, where m1>m2>m3>m4>m5. The specific values ​​are 95-100% for m1, 90-95% for m2, 90-95% for m3, 85-90% for m4, and 60-70% for m5. It should be noted that for charging piles that are not fully utilized or during off-peak charging periods, reducing the working power of the charging piles is beneficial to reducing the working pressure and heat of the internal components of the charging piles and alleviating the idle waste of the power grid during off-peak periods.

[0067] When the charging state value is between the preset gradient reference thresholds Yu2 and Yu3, a charging pile normal state signal is generated, and the charging pile has no operation.

[0068] When the charging state value is between the preset gradient reference thresholds Yu3 and Yu4, a charging pile is generated to be in a large charging load recognition signal, and the difference with the reference threshold Yu3 is calculated to obtain a custom value, the custom value is multiplied by the charging pile working power conversion coefficient, and the charging demand candidate set is matched to obtain the working power adjustment value corresponding to the charging demand candidate set, which is specifically adjusted to multiply the first-level charging demand candidate set B1 by the adjustment coefficient d1, the second-level charging demand candidate set B2 by the adjustment coefficient d2, the third-level charging demand candidate set B3 by the adjustment coefficient d3, and the fourth-level charging demand candidate set B4 by the adjustment coefficient d4, wherein d1>d2>d3>d4, and the specific values ​​can be d1 taking a value of 90-100%, d2 taking a value of 80-90%, d3 taking a value of 70-80%, and d4 taking a value of 65-70%; it should be noted that for charging piles that are in a large charging load or charging peak period, reducing the working power of the charging pile is conducive to ensuring the stability of the charging pile power grid.

[0069] When the charging state value is greater than the preset gradient reference threshold value Yu4, an abnormal signal of excessive current and voltage of the charging pile is generated, and sent to the charging pile human-computer interaction platform for display in the form of a description of "the charging pile is in an abnormal state of excessive current and voltage, please ask the staff to troubleshoot the line fault";

[0070] The human-computer interaction platform is used to receive the text messages "The charging pile is working in an abnormal state of too low working current and voltage. Please ask the staff to troubleshoot the line fault" and "The charging pile is working in an abnormal state of too high working current and voltage. Please ask the staff to troubleshoot the line fault", display the instructions and remind the relevant staff.

[0071] The database stores the reference remaining power of the charging pile user's vehicle, the reference vehicle type value, the reference distance between the home address and the company address, the gradient reference threshold of the charging pile charging status value, etc.

[0072] The above is an explanation of the present invention and should not be considered as a limitation thereof. Although several exemplary embodiments of the present invention have been described, it will be readily appreciated by those skilled in the art that many modifications may be made to the exemplary embodiments without departing from the novel teachings and advantages of the present invention. Therefore, all such modifications are intended to be included within the scope of the present invention as defined in the claims. It should be understood that the above is an explanation of the present invention and should not be considered as being limited to the specific embodiments disclosed, and modifications to the disclosed embodiments and other embodiments are intended to be included within the scope of the appended claims. The present invention is defined by the claims and their equivalents.

Claims

1. A charging pile monitoring system based on artificial intelligence, including a data acquisition module, a human-computer interaction platform and a database, characterized in that: Also includes: A user demand analysis module is used to receive the charging pile user behavior characteristic demand parameters and the charging-related demand parameters of the charging pile user, and to perform determination and analysis on the charging pile user behavior characteristic demand and the charging-related demand of the charging pile user, and send them to the charging status monitoring and early warning module; The charging index analysis module is used to receive the temperature state parameters and the charging state parameters of the charging pile, analyze them, obtain the temperature state value and the charging state value of the charging pile, and send them to the temperature monitoring and adjustment module and the charging state monitoring and early warning module; The temperature monitoring and adjustment module is used to collect statistics and analyze the temperature status values ​​of the charging piles and automatically adjust the temperature of the charging piles; The charging status monitoring and early warning module is used to collect statistics and analyze the charging status values ​​of the charging piles, generate corresponding signals and make corresponding adjustments to the working power of the charging piles.

2. The charging pile monitoring system based on artificial intelligence according to claim 1 is characterized in that: The specific analysis method of the charging pile user behavior characteristic requirements and the charging-related requirements determination analysis of the charging pile user is as follows: Obtain the charging records of each charging pile user, where the charging records include the number of charging times and the start and end times of each charging. Calculate the time difference between the start and end times of charging to obtain the charging duration and number of charging times of the charging pile user, and record them as Cs i and Cc i , i is the number of the charging pile user; the charging start time is taken as the charging time of this time; the coordinate system is constructed with time as the horizontal axis of the two-dimensional coordinate system and the charging time as the vertical axis, the charging time corresponding to the charging time is plotted, and a broken line is used to connect them to obtain a charging record change broken line graph, and the slope of two adjacent points is calculated and recorded as r is the number of times the charging pile user charges, where r ranges from 1, 2, 3, ...R, R is the maximum value of the charging number, and the average of all slopes is recorded as The time difference between the charging start time and the last charging end time is calculated to obtain the charging time interval of the charging pile user, which is recorded as According to the set formula Calculate to get the charging fluctuation value Cb of the charging pile user i ; According to the set formula Get the charging behavior characteristic demand index TH of the charging pile user i , where a1, a2, a3, a4 are the set weight factor coefficients, e is a constant, and Z1, Z2, Z3 are the set reference charging time, reference slope, and reference charging times of the charging pile user; Set the gradient comparison intervals T1, T2 and T3 of the charging behavior characteristic demand index, and substitute the charging behavior characteristic demand index of each charging pile user into the preset gradient comparison intervals T1, T2 and T3 for comparative analysis; When the charging behavior characteristic demand index is within the preset gradient comparison interval T1, the charging behavior characteristic value of the charging pile user is recorded as x1 points; when the charging behavior characteristic demand index is within the preset gradient comparison interval T2, the charging behavior characteristic value of the charging pile user is recorded as x2 points; when the charging behavior characteristic demand index is within the preset gradient comparison interval T3, the charging behavior characteristic value of the charging pile user is recorded as x3 points; The remaining power of the charging pile user's vehicle is obtained through the power detection sensor, which is recorded as Sd i ; Get the vehicle types of charging pile users, including electric buses, electric taxis, electric family cars, hybrid electric vehicles and other vehicles, corresponding to w1, w2, w3, w4, w5 values, and recorded as Cz i ; Get the distance between the charging pile user’s home address and company address, recorded as Jg i ; According to the set formula The charging-related demand index of the charging pile user is obtained, where f1, f2, and f3 are the set weight factor coefficients, Sd′, Cz′, and Jg′ represent the set reference remaining power of the charging pile user's vehicle, the reference vehicle type value, and the reference distance between the home address and the company address, respectively, and ΔSd, ΔCz, and ΔJg represent the set reference remaining power difference, the reference vehicle type value difference, and the reference distance difference between the home address and the company address, respectively; Set a complete reference threshold TH1 for the charging-related demand index, and substitute the charging-related demand indexes of the charging pile users into the preset complete reference threshold TH1 for comparative analysis; When the charging-related demand index of the charging pile user is less than the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y1 points; when the charging-related demand index of the charging pile user is equal to the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y2 points; when the charging-related demand index of the charging pile user is greater than the preset complete reference threshold TH1, the corresponding charging pile user is additionally assigned y3 points; The score value of the charging behavior characteristic demand data item of each charging pile user is added to the score value of the charging associated demand index data item to obtain the total score value of each charging pile user, and each charging pile user is graded according to the total score value. When the total score value is x3+y3 or x2+y3 or x3+y2, the corresponding charging pile user is divided into the first-level charging demand candidate set B1; when the total score value is x2+y2 or x1+y3 or x3+y1, the corresponding charging pile user is divided into the second-level charging demand candidate set B2; when the total score value is x1+y2 or x2+y1, the corresponding charging pile user is divided into the third-level charging demand candidate set B3; when the total score value is x1+y1, the corresponding charging pile user is divided into the fourth-level charging demand candidate set B4; The obtained first-level charging demand candidate set B1, second-level charging demand candidate set B2, third-level charging demand candidate set B3 and fourth-level charging demand candidate set B4 are sent to the charging status monitoring and early warning module.

3. The charging pile monitoring system based on artificial intelligence according to claim 1 is characterized in that: The specific analysis method of the temperature state value of the charging pile is: The temperature of the charging pile power module is measured by a thermocouple. The measurement time is used as the horizontal axis and the temperature of the power module is used as the vertical axis to establish a two-dimensional coordinate system. The temperature points corresponding to each measurement time are plotted. The points are connected with a broken line to obtain a temperature line. The slope of each temperature line value and the angle with the horizontal line are calculated. When the angle between the temperature line value and the horizontal line is an acute angle, it is recorded as the first slope and recorded as Wy t , t is the number of the measurement time, where t ranges from 1, 2, 3, ... T, T represents the maximum value of the number, when the angle between the temperature value line and the horizontal line is an obtuse angle, it is recorded as the second slope We t ; Read the highest temperature value in the line graph, record it as Tg, read the lowest temperature value in the line graph, record it as Tx; Calculate to get the temperature state value Wp of the charging pile, where b1, b2, b3, and b4 are the set proportional coefficients respectively. are the first slope average values ​​of the temperature corresponding to different measurement moments, is the average value of the second slope of the temperature corresponding to different measurement times, is the average value of the temperature slope corresponding to different measurement times, BW is the standard value of the temperature slope corresponding to different measurement times, Tg′ is the maximum reference value of the temperature, and Tx′ is the minimum reference value of the temperature.

4. The charging pile monitoring system based on artificial intelligence according to claim 1 is characterized in that: The specific analysis method of the charging status value of the charging pile is: The actual electrical operating parameters of the charging pile are obtained, and the actual electrical operating parameters include the current value and voltage value of the charging pile; the real-time current value and voltage value of the charging pile are displayed through the curve of the coordinate system, and a standard current value line and a standard voltage value line are respectively established in the coordinate system, and the closed area formed by the two curves and the two standard lines is measured, and the reference value is accumulated and used as the standard of the actual electrical operating parameters of the charging pile; the power consumption of the charging pile is measured by the intelligent power meter, and the active power value is calculated according to the measurement time; the reference value, active power value and temperature state value are normalized, and an ellipse is constructed with the reference value and active power value as the major axis and minor axis respectively, and a cone is constructed with the temperature state value as the height, and the volume of the cone is extracted, and the numerical value of the volume is calibrated as the charging state value of the charging pile.

5. The charging pile monitoring system based on artificial intelligence according to claim 1 is characterized in that: The temperature status values ​​of the charging piles are counted and analyzed, and the specific analysis method is as follows: The operating temperature value of the charging pile is divided into n temperature values, each temperature value corresponds to a value range, Q1 (0, q1), Q2 (q1, q2), Q3 (q2, q3)...Qn (qn-1, qn), where Q1, Q2, Q3...Qn are specific temperature value numbers, q1, q2, q3...qn are temperature values, and the temperature state values ​​corresponding to various charging piles are matched with the value range of the temperature value. If the temperature state value corresponding to the charging pile is within the value range of the temperature value, then the value range is the adjusted temperature value for the operation of the charging pile, and the charging pile automatically adjusts the temperature according to the adjusted temperature value.

6. The charging pile monitoring system based on artificial intelligence according to claim 1 is characterized in that: The charging status value of the charging pile is counted and analyzed, and the specific analysis method is as follows: Set gradient reference thresholds Yu1, Yu2, Yu3, and Yu4 for the charging state value of the charging pile, and compare and analyze the charging state value of the charging pile with the preset gradient reference thresholds Yu1, Yu2, Yu3, and Yu4; When the charging state value is less than the preset gradient reference threshold value Yu1, an abnormal signal of the working current and voltage of the charging pile is generated, and is sent to the charging pile human-computer interaction platform for display in the form of a description of "the charging pile is in an abnormal state of working current and voltage being too small, please ask the staff to troubleshoot the line fault"; When the charging state value is between the preset gradient reference thresholds Yu1 and Yu2, a charging pile underutilization recognition signal is generated, and the difference with the reference threshold Yu2 is calculated to obtain a custom value, the custom value is multiplied by the charging pile working power conversion coefficient, and the charging demand candidate set is matched to obtain the working power adjustment value corresponding to the charging demand candidate set, which is adjusted to the working power corresponding to the first-level charging demand candidate set B1 multiplied by the adjustment coefficient m1, the working power corresponding to the second-level charging demand candidate set B2 multiplied by the adjustment coefficient m2, the working power corresponding to the third-level charging demand candidate set B3 multiplied by the adjustment coefficient m3, the working power corresponding to the fourth-level charging demand candidate set B4 multiplied by the adjustment coefficient m4, and the working power corresponding to the charging pile not in use multiplied by the adjustment coefficient m5; When the charging state value is between the preset gradient reference thresholds Yu3 and Yu4, a charging pile is generated to be in a large charging load recognition signal, and the difference with the reference threshold Yu3 is calculated to obtain a custom value, the custom value is multiplied by the charging pile working power conversion coefficient, and the charging demand candidate set is matched to obtain the working power adjustment value corresponding to the charging demand candidate set, which is adjusted to the working power corresponding to the first-level charging demand candidate set B1 multiplied by the adjustment coefficient d1, the working power corresponding to the second-level charging demand candidate set B2 multiplied by the adjustment coefficient d2, the working power corresponding to the third-level charging demand candidate set B3 multiplied by the adjustment coefficient d3, and the working power corresponding to the fourth-level charging demand candidate set B4 multiplied by the adjustment coefficient d4; When the charging status value is greater than the preset gradient reference threshold value Yu4, an abnormal signal of excessive working current and voltage of the charging pile is generated, and is sent to the charging pile human-computer interaction platform for display in the form of a description of the text "The charging pile is working in an abnormal state of excessive working current and voltage, please ask the staff to troubleshoot the line fault."

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