Charging pile monitoring and early warning method and system

Abstract

The invention provides a charging pile monitoring and early warning method and system, and belongs to the technical field of charging management, and the method specifically comprises the steps: determining an abnormal power interval in a charging power interval based on the temperature abnormal data in different environment temperature intervals in the charging power interval, and determining the abnormal power interval in the charging power interval based on the historical charging data of a charging station where the charging pile is located; according to the method, historical charging data in different abnormal power intervals are determined, and when the historical charging data in the different abnormal power intervals are utilized to determine that the charging risk coefficient of the charging pile is in a preset interval, whether the charging pile needs to output an early warning signal or not is determined on the basis of the charging risk coefficients of different charging piles in the charging station. And the operation reliability of the charging pile is improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of charging management, and in particular relates to a charging pile monitoring and early warning method and system. Background Art

[0002] In order to realize the monitoring and early warning of charging piles during the charging process, the invention patent application CN202311265654.2 "Charging process early warning system of new energy charging piles based on artificial intelligence" analyzes the relevant data of each charging pile in the charging station, thereby rating the risk of the charging piles, and intelligently recommends charging piles of different risk levels in conjunction with the charging behavior data of new energy vehicle owners. However, the above technical solutions all have the following technical problems:

[0003] When performing early warning processing for charging piles, the probability of abnormal temperature occurring in charging piles in different ambient temperature ranges varies. At the same time, the time period distribution data in different ambient temperature ranges in a certain period of time in the future also differs. Therefore, if the early warning processing of the charging pile cannot be performed in combination with the ambient temperature data, the operational reliability of the charging pile cannot be guaranteed.

[0004] In response to the above technical problems, the present application specifically provides a charging pile monitoring and early warning method and system. Summary of the invention

[0005] To achieve the purpose of the present invention, the present invention adopts the following technical solutions:

[0006] In a first aspect, the present application provides a charging pile monitoring and early warning method, which specifically includes:

[0007] S1 determines the temperature abnormality data of the charging pile in different ambient temperature intervals based on the analysis results of the monitoring data of the charging pile, and combines the time distribution data of different ambient temperature intervals in the future preset time period to determine that the charging pile does not need to be pre-warned, and then proceeds to the next step;

[0008] S2: dividing the abnormal temperature data to obtain abnormal temperature data in different charging power intervals, and determining an abnormal power interval in the charging power interval based on the abnormal temperature data in different ambient temperature intervals in the charging power interval;

[0009] S3: based on the historical charging data of the charging station where the charging pile is located, determining the historical charging data in different abnormal power intervals, and using the historical charging data in different abnormal power intervals to determine that the charging risk coefficient of the charging pile is within a preset interval, then proceeding to the next step;

[0010] S4 determines whether the charging pile needs to output a warning signal based on the charging risk coefficients of different charging piles in the charging station.

[0011] The beneficial effects of the present invention are:

[0012] Based on the temperature anomaly data of the charging pile in different ambient temperature ranges and the time period distribution data in different ambient temperature ranges in the future preset time period, it is determined whether the charging pile needs early warning processing. This not only takes into account the temperature anomaly conditions in different ambient temperature ranges, but also takes into account the proportion of the number of time periods in different ambient temperature ranges in the future preset time period. It realizes the determination of the temperature anomaly risk of the charging pile from the perspective of weather data, and ensures the reliability of the charging processing of the charging pile.

[0013] Based on the charging risk coefficients of different charging piles in the charging station, it is determined whether the charging pile needs to output a warning signal. Not only the size of the charging risk coefficient of the charging pile itself is taken into consideration, but also the impact of abnormalities of other charging piles in the charging station on normal charging due to the size of the charging risk coefficients is considered, thereby improving the reliability of the charging processing of the charging station.

[0014] A further technical solution is that the ambient temperature range is divided according to the historical ambient temperature of the charging pile and a preset temperature interval.

[0015] A further technical solution is that the temperature anomaly data includes the number of temperature anomalies, the temperatures of different temperature anomaly numbers, and the durations.

[0016] A further technical solution is that the preset time period is determined according to the historical charging data of the charging station, wherein the more vehicles are charged per day at the charging station, the shorter the preset time period is.

[0017] A further technical solution is that the preset time period is determined according to the corresponding relationship between the average daily number of charging vehicles and the preset duration.

[0018] A further technical solution is that the time period distribution data within the ambient temperature range is determined based on weather forecast data for different time periods within a future preset time period.

[0019] A further technical solution is to determine whether the charging pile needs to output a warning signal, specifically including:

[0020] Based on whether the charging risk coefficients of different charging piles in the charging station are greater than the charging risk coefficient of the charging pile, the charging piles are divided into safe charging piles and risky charging piles;

[0021] According to the proportion of risky charging piles, it is determined whether the charging piles need to output warning signals.

[0022] A further technical solution is that the risky charging pile is a charging pile whose charging risk coefficient is greater than the charging risk coefficient of the charging pile.

[0023] A further technical solution is that when the proportion of the number of risky charging piles is less than the proportion of the preset number of charging piles, it is determined that the charging piles need to output a warning signal.

[0024] In a second aspect, the present invention provides a computer system comprising: a memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned charging pile monitoring and early warning method when running the computer program.

[0025] Other features and advantages will be described in the following description. The objects and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description and drawings.

[0026] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0028] Figure 1 It is a flow chart of a charging pile monitoring and early warning method;

[0029] Figure 2 It is a flow chart for determining that the charging pile does not need to be processed for early warning;

[0030] Figure 3 is a flowchart of a method for determining an abnormal power interval in a charging power interval;

[0031] Figure 4 It is a flow chart of a method for determining a charging risk factor of a charging pile;

[0032] Figure 5 It is a framework diagram of a computer system. DETAILED DESCRIPTION

[0033] In order to enable those skilled in the art to better understand the technical solutions in this specification, the technical solutions in the embodiments of this specification will be clearly and completely described below in conjunction with the drawings in the embodiments of this specification. Obviously, the described embodiments are only part of the embodiments of this specification, not all of the embodiments. Based on the embodiments of this specification, all other embodiments obtained by ordinary technicians in this field without creative work should fall within the scope of protection of this specification.

[0034] In this application, the abnormal temperature rise of charging piles in different temperature ranges and the distribution data of different temperature ranges in the future are used to screen charging piles with higher temperature abnormalities, and perform early warning processing to improve the operating reliability of the charging piles.

[0035] Based on the number of temperature anomalies of the charging pile in different ambient temperature intervals, the ambient temperature interval in which the number of temperature anomalies is greater than the preset number of temperature anomalies is taken as the abnormal interval. The sum of the weight coefficients of the different abnormal intervals is determined based on the proportion of the number of time periods in different ambient temperature intervals in the future preset time period. When the sum of the weight coefficients of the different abnormal intervals is greater than 0.6, it is determined that the charging pile needs to be warned.

[0036] The abnormal power range is the charging power range in which the number of temperature abnormalities is greater than 20 times.

[0037] The charging risk coefficient of the charging pile is determined based on the sum of the proportions of historical charging times in different abnormal power intervals, wherein when the charging risk coefficient of the charging pile is between 0.3 and 0.7, it is determined that the charging risk coefficient of the charging pile is within the preset range.

[0038] When the number of charging piles in the charging station whose charging risk coefficient is greater than that of the charging piles accounts for less than 0.2, it is determined that the charging piles need to output a warning signal.

[0039] Example 1

[0040] like Figure 1 As shown, the present application provides a first aspect, the present application provides a charging pile monitoring and early warning method, specifically including:

[0041] S1 determines the temperature abnormality data of the charging pile in different ambient temperature intervals based on the analysis results of the monitoring data of the charging pile, and combines the time distribution data of different ambient temperature intervals in the future preset time period to determine that the charging pile does not need to be pre-warned, and then proceeds to the next step;

[0042] Furthermore, the ambient temperature range is divided according to the historical ambient temperature of the charging pile and a preset temperature interval.

[0043] Specifically, the temperature anomaly data includes the number of temperature anomalies, the temperatures of different temperature anomaly numbers, and the durations.

[0044] It should be noted that the preset time period is determined based on the historical charging data of the charging station, wherein the more vehicles are charged per day at the charging station, the shorter the preset time period is.

[0045] It can be understood that the preset time period is determined according to the corresponding relationship between the average daily number of charging vehicles and the preset duration.

[0046] Specifically, the time period distribution data within the ambient temperature range is determined based on weather forecast data for different time periods within a future preset time period.

[0047] Specifically, Figure 2 As shown, determining that the charging pile does not need to be pre-warned includes:

[0048] The temperature anomaly data of the charging pile in different ambient temperature intervals are used to determine the number of temperature anomalies of the charging pile in different ambient temperature intervals, and the total duration of the different ambient temperature intervals is determined in combination with the duration of different temperature anomalies.

[0049] Determine the time period distribution data in different ambient temperature intervals within a future preset time period, determine the time period quantity ratio in different ambient temperature intervals, and determine the weight coefficient of different ambient temperature intervals using the time period quantity ratio;

[0050] Based on the weight coefficient and the total duration of different ambient temperature intervals, the estimated abnormal duration of the charging pile is determined, and the estimated abnormal duration is used to determine whether the charging pile needs to be warned.

[0051] Furthermore, the estimated abnormal duration of the charging pile is the sum of the product of the total duration of different ambient temperature intervals and the weight coefficient.

[0052] It is understandable that when the estimated abnormal duration of the charging pile is greater than the preset abnormal duration, it is determined that the charging pile needs to be warned.

[0053] Optionally, determining that the charging pile does not need to perform early warning processing specifically includes:

[0054] The temperature anomaly data of the charging pile in different ambient temperature intervals are used to determine the number of temperature anomalies of the charging pile in different ambient temperature intervals, and the total duration of the different ambient temperature intervals is determined in combination with the duration of different temperature anomalies.

[0055] Determine the abnormal interval within the ambient temperature interval using the total duration, determine the time period ratio within different ambient temperature intervals using the time period distribution data within different ambient temperature intervals within a future preset period, and determine the sum of weight coefficients of different abnormal intervals using the time period ratio;

[0056] Whether the charging pile needs to be pre-warned is determined based on the sum of weight coefficients of different abnormal intervals.

[0057] Furthermore, when the sum of the weight coefficients of different abnormal intervals is greater than a preset weight coefficient, it is determined that the charging pile needs to be pre-warned.

[0058] Optionally, determining that the charging pile does not need to perform early warning processing specifically includes:

[0059] S11 determines the number of temperature anomalies of the charging pile in different ambient temperature intervals based on the temperature anomaly data of the charging pile in different ambient temperature intervals, and determines the temperature anomaly coefficients of the different ambient temperature intervals in combination with the duration of different temperature anomaly times;

[0060] S12 determines the abnormal temperature interval within the ambient temperature interval by using the total duration, determines the time period ratio in different ambient temperature intervals based on the time period distribution data in different ambient temperature intervals in a future preset period, and determines the weight coefficients of different temperature intervals by using the time period ratio;

[0061] S13 determines the weight sum of the temperature anomaly coefficients based on the weight coefficients of different ambient temperature intervals and the temperature anomaly coefficients, and uses it as a comprehensive anomaly coefficient, and uses the comprehensive anomaly coefficient to determine whether the charging pile needs to be warned.

[0062] Furthermore, when the comprehensive abnormality coefficient does not meet the requirement, it is determined that the charging pile needs to be pre-warned.

[0063] S2: dividing the abnormal temperature data to obtain abnormal temperature data in different charging power intervals, and determining an abnormal power interval in the charging power interval based on the abnormal temperature data in different ambient temperature intervals in the charging power interval;

[0064] Specifically, Figure 3 As shown, the method for determining the abnormal power interval in the charging power interval is:

[0065] Determine the number of temperature anomalies in different ambient temperature intervals based on the temperature anomaly data in different ambient temperature intervals within the charging power interval;

[0066] Determining an abnormal temperature interval within the ambient temperature interval based on the number of temperature anomalies;

[0067] Whether the charging power interval is an abnormal power interval is determined according to the number of the abnormal temperature intervals.

[0068] It should be noted that the abnormal temperature interval is an ambient temperature interval in which the number of temperature anomalies does not meet the requirements.

[0069] It can be understood that when the number of the abnormal temperature intervals is greater than the number of preset intervals, the charging power interval is determined to be an abnormal power interval.

[0070] In another embodiment, the method for determining the abnormal power interval in the charging power interval is:

[0071] Determine the number of temperature anomalies in different ambient temperature intervals based on the temperature anomaly data in different ambient temperature intervals within the charging power interval;

[0072] Determining the total number of temperature anomalies in the charging power interval based on the number of temperature anomalies in different ambient temperature intervals;

[0073] Whether the charging power interval is an abnormal power interval is determined according to the total number of temperature anomalies.

[0074] Further, when the total number of temperature anomalies does not meet the requirement, the charging power interval is determined to be an abnormal power interval.

[0075] Optionally, a method for determining an abnormal power interval in the charging power interval is:

[0076] S21 determines the number of temperature anomalies in different ambient temperature intervals based on the temperature anomaly data in different ambient temperature intervals within the charging power interval;

[0077] S22 determines interval abnormality values ​​of different ambient temperature intervals based on the number of temperature abnormalities in different ambient temperature intervals and the duration of different temperature abnormalities;

[0078] S23 determines the charging abnormality coefficient of the charging power interval based on the interval abnormality values ​​in different ambient temperature intervals, and determines whether the charging power interval is an abnormal power interval by using the charging abnormality coefficient.

[0079] Furthermore, the method for determining the interval abnormal value of the ambient temperature interval is:

[0080] Determine preset abnormal values ​​corresponding to different numbers of temperature abnormalities according to the duration of different numbers of temperature abnormalities;

[0081] The interval abnormality value of the ambient temperature interval is determined based on the sum of preset abnormality values ​​of different temperature abnormality times.

[0082] It should be noted that the charging anomaly coefficient of the charging power interval is determined according to the weighted sum of interval anomaly values ​​in different ambient temperature intervals.

[0083] Optionally, the above step S21 includes the following contents:

[0084] S211 determines the number of temperature anomalies in different ambient temperature intervals based on the temperature anomaly data in the charging power interval and in different ambient temperature intervals. When the number of temperature anomalies is less than a preset number threshold, the process proceeds to step S212. When the number of temperature anomalies is not less than the preset number threshold, the process proceeds to step S213.

[0085] S212: When the number of ambient temperature intervals with temperature anomalies is less than the preset number of temperature intervals, it is determined that the charging power interval does not belong to the abnormal power interval; when the number of ambient temperature intervals with temperature anomalies is not less than the preset number of temperature intervals, the process proceeds to step S213;

[0086] S213 obtains the ambient temperature intervals in which the number of temperature anomalies is greater than the preset number of anomalies. When the number of ambient temperature intervals in which the number of temperature anomalies is greater than the preset number of anomalies is greater than the preset interval number threshold, it is determined that the charging power interval belongs to the abnormal power interval. When the number of ambient temperature intervals in which the number of temperature anomalies is greater than the preset number of anomalies is not greater than the preset interval number threshold, proceed to step S22.

[0087] Optionally, the above step S22 includes the following contents:

[0088] S221 determines the interval abnormal values ​​of different ambient temperature intervals based on the number of temperature abnormalities in different ambient temperature intervals and the duration of different temperature abnormalities. When there is no interval abnormal value that does not meet the required ambient temperature interval, the process proceeds to step S222. When there is an interval abnormal value that does not meet the required ambient temperature interval, the process proceeds to step S223.

[0089] S222: When the sum of the interval abnormal values ​​of different ambient temperature intervals is less than the preset abnormal threshold, it is determined that the charging power interval belongs to the abnormal power interval; when the sum of the interval abnormal values ​​of different ambient temperature intervals is not less than the preset abnormal threshold, the process proceeds to step S23;

[0090] S223 When the number of ambient temperature intervals whose interval abnormal values ​​do not meet the requirements is greater than the preset interval number threshold, it is determined that the charging power interval belongs to the abnormal power interval. When the number of ambient temperature intervals whose interval abnormal values ​​do not meet the requirements is not greater than the preset interval number threshold, proceed to step S23.

[0091] S3: based on the historical charging data of the charging station where the charging pile is located, determining the historical charging data in different abnormal power intervals, and using the historical charging data in different abnormal power intervals to determine that the charging risk coefficient of the charging pile is within a preset interval, then proceeding to the next step;

[0092] Specifically, Figure 4 As shown, the method for determining the charging risk coefficient of the charging pile is:

[0093] Using historical charging data in different abnormal power intervals, determine the number of historical charging times in different abnormal power intervals;

[0094] Determining the valid charging times in the historical charging times based on the charging times of the historical charging times in different abnormal power intervals;

[0095] A charging risk coefficient of the charging pile is determined according to the effective charging times.

[0096] Furthermore, the effective charging times are the historical charging times in which the charging time is greater than the preset charging time.

[0097] It can be understood that the charging risk coefficient of the charging pile is determined according to the ratio of the effective charging times to the preset charging times.

[0098] It should be noted that when the charging risk coefficient of the charging pile is not within the preset range, it is determined whether the charging risk coefficient of the charging pile is greater than the preset risk coefficient threshold. If so, it is determined that the charging pile needs to output a warning signal. If not, it is determined that the charging pile does not need to output a warning signal.

[0099] Optionally, the method for determining the charging risk coefficient of the charging pile is:

[0100] Using historical charging data in different abnormal power intervals, determine the number of historical charging times in different abnormal power intervals, and when the total number of historical charging times in different abnormal power intervals is greater than a preset charging number threshold, determine that the charging pile needs to output a warning signal;

[0101] When the total number of historical charging times in different abnormal power intervals is not greater than the preset charging times threshold:

[0102] When the total number of historical charging times in different abnormal power intervals is within the preset charging times range:

[0103] When the total number of historical charging times in different abnormal power intervals is less than the set value of the number of charging times, it is determined that the charging pile does not need to output a warning signal;

[0104] When the total number of historical charging times in different abnormal power intervals is not less than the set value of charging times:

[0105] Determine the total charging time of different historical charging times according to the charging time of different historical charging times, and when the total charging time of different historical charging times does not meet the requirements, determine that the charging pile needs to output a warning signal;

[0106] When the total charging time of different historical charging times meets the requirements:

[0107] Based on the charging duration of the historical charging times in different abnormal power intervals, determining the effective charging times in the historical charging times, when the effective charging times are greater than a preset effective times threshold, determining that the charging pile needs to output a warning signal;

[0108] When the effective charging times are not greater than the preset effective times threshold:

[0109] The charging demand coefficients of different abnormal power intervals are determined based on the historical charging times and the charging durations of the historical charging times in different abnormal power intervals. When there is an abnormal power interval with a charging demand coefficient greater than a preset demand coefficient threshold:

[0110] When the number of abnormal power intervals in which the charging demand coefficient is greater than the preset demand coefficient threshold is greater than the preset power interval number, it is determined that the charging pile needs to output a warning signal;

[0111] When there is no abnormal power interval with a charging demand coefficient greater than the preset demand coefficient threshold or the number of abnormal power intervals with a charging demand coefficient greater than the preset demand coefficient threshold is not greater than the preset number of power intervals:

[0112] The charging risk coefficient of the charging pile is determined based on the charging demand coefficients in different abnormal power intervals.

[0113] S4 determines whether the charging pile needs to output a warning signal based on the charging risk coefficients of different charging piles in the charging station.

[0114] Specifically, determining whether the charging pile needs to output a warning signal specifically includes:

[0115] Based on whether the charging risk coefficients of different charging piles in the charging station are greater than the charging risk coefficient of the charging pile, the charging piles are divided into safe charging piles and risky charging piles;

[0116] According to the proportion of risky charging piles, it is determined whether the charging piles need to output warning signals.

[0117] It should be noted that the risky charging pile is a charging pile whose charging risk coefficient is greater than the charging risk coefficient of the charging pile.

[0118] Optionally, when the proportion of the number of risky charging piles is less than the proportion of the preset number of charging piles, it is determined that the charging piles need to output a warning signal.

[0119] Example 2

[0120] Second, as Figure 5 As shown, the present invention provides a computer system, comprising: a memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-mentioned charging pile monitoring and early warning method when running the computer program.

[0121] Optionally, the above step S11 includes the following contents:

[0122] S111 determines the number of temperature anomalies of the charging pile in different ambient temperature intervals based on the temperature anomaly data of the charging pile in different ambient temperature intervals. When the total number of temperature anomalies of the charging pile does not meet the requirement, it is determined that the charging pile needs to be pre-warned. When the total number of temperature anomalies of the charging pile meets the requirement, the process proceeds to step S112.

[0123] S112 determines the total duration of different temperature anomalies based on the duration of different temperature anomalies. When the total duration does not meet the requirement, it is determined that the charging pile needs to be pre-warned. When the total duration meets the requirement, the process proceeds to step S113.

[0124] S113 determines a basic abnormality coefficient based on the number of temperature abnormalities and the duration of different temperature abnormalities. When the basic abnormality coefficient is within the preset abnormality coefficient interval, the process proceeds to step S114. When the basic abnormality coefficient is not within the preset abnormality coefficient interval, it is determined that the charging pile does not need to be pre-warned.

[0125] S114 determines the temperature anomaly coefficients of different ambient temperature intervals based on the number of temperature anomalies of the charging pile in different ambient temperature intervals and the duration of different temperature anomalies. If there is an ambient temperature interval where the temperature anomaly coefficient does not meet the requirements, the process proceeds to step S115. If there is no ambient temperature interval where the temperature anomaly coefficient does not meet the requirements, the process proceeds to step S12.

[0126] S115 When the number of ambient temperature intervals whose temperature anomaly coefficients do not meet the requirements is greater than the preset number of temperature intervals, it is determined that the charging pile needs to be early-warning processed; when the number of ambient temperature intervals whose temperature anomaly coefficients do not meet the requirements is not greater than the preset number of temperature intervals, proceed to step S12.

[0127] Optionally, the above step S12 includes the following contents:

[0128] S121 determines the abnormal temperature interval within the ambient temperature interval by using the total duration, determines the time period ratios within different ambient temperature intervals based on the time period distribution data within different ambient temperature intervals within a future preset time period, and determines the weight coefficients of different temperature intervals by using the time period ratios;

[0129] S122: The ambient temperature interval in which the temperature anomaly coefficient does not meet the requirement is regarded as an abnormal interval. When the sum of the weight coefficients of the abnormal interval is greater than the preset weight coefficient, it is determined that the charging pile needs to be pre-warned. When the sum of the weight coefficients of the abnormal interval is not greater than the preset weight coefficient, the process proceeds to step S123.

[0130] S123 obtains the ambient temperature range of the weight coefficient within the preset weight coefficient range. When the average value of the temperature anomaly coefficient of the ambient temperature range of the weight coefficient within the preset weight coefficient range does not meet the requirements, it is determined that the charging pile needs to be early warned. When the average value of the temperature anomaly coefficient of the ambient temperature range of the weight coefficient within the preset weight coefficient range meets the requirements, proceed to step S13.

[0131] Each embodiment in this specification is described in a progressive manner, and the same or similar parts between the embodiments can be referred to each other, and each embodiment focuses on the differences from other embodiments. In particular, for the device, equipment, and non-volatile computer storage medium embodiments, since they are basically similar to the method embodiments, the description is relatively simple, and the relevant parts can be referred to the partial description of the method embodiment.

[0132] The above is a description of a specific embodiment of the specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the embodiments and still achieve the desired results. In addition, the processes depicted in the drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0133] The above description is only one or more embodiments of this specification and is not intended to limit this specification. For those skilled in the art, one or more embodiments of this specification may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of one or more embodiments of this specification shall be included in the scope of the claims of this specification.

Claims

1. A charging pile monitoring and early warning method, characterized in that: Specifically include: Based on the analysis results of the monitoring data of the charging pile, the temperature abnormality data of the charging pile in different ambient temperature intervals is determined, and combined with the time distribution data in different ambient temperature intervals in the future preset time period, when it is determined that the charging pile does not need to be pre-warned, the next step is entered; Dividing the abnormal temperature data to obtain abnormal temperature data in different charging power intervals, and determining an abnormal power interval in the charging power interval based on the abnormal temperature data in different ambient temperature intervals in the charging power interval; Based on the historical charging data of the charging station where the charging pile is located, the historical charging data in different abnormal power intervals are determined, and when the charging risk coefficient of the charging pile is determined to be within a preset interval by using the historical charging data in different abnormal power intervals, the next step is entered; Based on the charging risk coefficients of different charging piles in the charging station, it is determined whether the charging pile needs to output a warning signal.

2. The charging pile monitoring and early warning method according to claim 1, characterized in that: The ambient temperature range is divided according to the historical ambient temperature of the charging pile and a preset temperature interval.

3. The charging pile monitoring and early warning method according to claim 1, characterized in that: The temperature anomaly data includes the number of temperature anomalies, the temperatures of different temperature anomaly numbers, and the duration.

4. The charging pile monitoring and early warning method according to claim 1, characterized in that: The preset period is determined according to historical charging data of the charging station, wherein the more vehicles are charged per day at the charging station, the shorter the preset period is.

5. The charging pile monitoring and early warning method according to claim 1, characterized in that: Determining that the charging pile does not need to be pre-warned includes: The temperature anomaly data of the charging pile in different ambient temperature intervals are used to determine the number of temperature anomalies of the charging pile in different ambient temperature intervals, and the total duration of the different ambient temperature intervals is determined in combination with the duration of different temperature anomalies. Determine the time period distribution data in different ambient temperature intervals within a future preset time period, determine the time period quantity ratio in different ambient temperature intervals, and determine the weight coefficient of different ambient temperature intervals using the time period quantity ratio; Based on the weight coefficient and the total duration of different ambient temperature intervals, the estimated abnormal duration of the charging pile is determined, and the estimated abnormal duration is used to determine whether the charging pile needs to be warned.

6. The charging pile monitoring and early warning method according to claim 5, characterized in that: When the estimated abnormal duration of the charging pile is greater than the preset abnormal duration, it is determined that the charging pile needs to be warned.

7. The charging pile monitoring and early warning method according to claim 1, characterized in that: Determining whether the charging pile needs to output a warning signal specifically includes: Based on whether the charging risk coefficients of different charging piles in the charging station are greater than the charging risk coefficient of the charging pile, the charging piles are divided into safe charging piles and risky charging piles; According to the proportion of risky charging piles, it is determined whether the charging piles need to output warning signals.

8. The charging pile monitoring and early warning method according to claim 7, characterized in that: The risky charging pile is a charging pile whose charging risk coefficient is greater than the charging risk coefficient of the charging pile.

9. The charging pile monitoring and early warning method according to claim 7, characterized in that: When the proportion of the number of risky charging piles is less than the proportion of the preset number of charging piles, it is determined that the charging piles need to output a warning signal.

10. A computer system comprising: A memory and a processor that are communicatively connected, and a computer program stored in the memory and capable of running on the processor, characterized in that the processor executes a charging pile monitoring and early warning method as described in any one of claims 1-9 when running the computer program.

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