A method and system for monitoring and early warning of charging piles

Abstract

This invention provides a charging pile monitoring and early warning method and system, belonging to the field of charging management technology. Specifically, it includes: determining abnormal power ranges within the charging power range based on abnormal temperature data in different ambient temperature ranges within the charging power range; determining historical charging data in different abnormal power ranges based on historical charging data of the charging station where the charging pile is located; determining whether the charging risk coefficient of the charging pile needs to output an early warning signal based on the charging risk coefficients of different charging piles in the charging station, thereby improving the operational reliability of the charging pile.

Description

Technical Field

[0001] This invention belongs to the field of charging management technology, and in particular relates to a method and system for monitoring and early warning of charging piles. Background Technology

[0002] To achieve monitoring and early warning of charging piles during the charging process, the invention patent application CN202311265654.2, "Early Warning System for Charging Process of New Energy Charging Piles Based on Artificial Intelligence," analyzes relevant data from each charging pile in the charging station to rate the risk of the charging piles. It then uses data on the charging behavior of new energy vehicle owners to intelligently recommend charging piles with different risk levels. However, the above technical solutions all have the following technical problems:

[0003] When performing early warning processing for charging piles, the probability of temperature anomalies occurring in different ambient temperature ranges varies. Furthermore, the time distribution data within different ambient temperature ranges also differs over a certain period of time. Therefore, if early warning processing for charging piles cannot be combined with ambient temperature data, the operational reliability of the charging piles cannot be guaranteed.

[0004] To address the aforementioned technical issues, this application specifically provides a method and system for monitoring and early warning of charging piles. Summary of the Invention

[0005] To achieve the objectives of this invention, the following technical solution is adopted:

[0006] Firstly, this application provides a method for monitoring and early warning of charging piles, specifically including:

[0007] S1 uses the analysis results of the monitoring data of the charging pile to determine the abnormal temperature data of the charging pile in different ambient temperature ranges, and combines the time distribution data of different ambient temperature ranges in the future preset time period to determine that the charging pile does not need to be warned, and then proceeds to the next step.

[0008] S2 divides the abnormal temperature data to obtain abnormal temperature data in different charging power ranges. Based on the abnormal temperature data in different ambient temperature ranges within the charging power range, the abnormal power range in the charging power range is determined.

[0009] S3 determines the historical charging data in different abnormal power ranges based on the historical charging data of the charging station where the charging pile is located, and uses the historical charging data in different abnormal power ranges to determine that the charging risk coefficient of the charging pile is within a preset range, and then proceeds to the next step.

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

[0011] The beneficial effects of this invention are as follows:

[0012] Based on temperature anomaly data of charging piles in different ambient temperature ranges and time period distribution data of different ambient temperature ranges in the future preset time period, it is determined whether charging piles need to be given an early warning. This takes into account both temperature anomalies in different ambient temperature ranges and the proportion of time periods in different ambient temperature ranges in the future preset time period, thus enabling the determination of temperature anomaly risks of charging piles from the perspective of weather data and ensuring the reliability of charging pile charging processing.

[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 an early warning signal. This not only considers the magnitude of the charging risk coefficient of the charging pile itself, but also the impact of abnormal charging piles on normal charging due to the magnitude of their charging risk coefficients, thereby improving the reliability of the charging station's charging process.

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

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

[0016] A further technical solution is that the preset time period is determined based on the historical charging data of the charging station, wherein the more vehicles the charging station charges on average per day, the shorter the preset time period.

[0017] A further technical solution is that the preset time period is determined based on the correspondence between the average number of vehicles charging per day 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 involves determining whether the charging pile needs to output a warning signal, specifically including:

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

[0021] Based on the proportion of risky charging piles, determine whether the charging pile needs to output a warning signal.

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

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

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

[0025] Other features and advantages will be set forth in the following description, and the objects and other advantages of the invention are realized and obtained through the structures particularly pointed out in the description and the drawings.

[0026] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, preferred embodiments are described below in detail with reference to the accompanying drawings. Attached Figure Description

[0027] The above and other features and advantages of the present invention will become more apparent from a detailed description of exemplary embodiments thereof with reference to the accompanying drawings.

[0028] Figure 1 This is a flowchart of a charging pile monitoring and early warning method;

[0029] Figure 2 This is a flowchart for determining whether a charging station does not require early warning processing;

[0030] Figure 3 This is a flowchart of a method for determining abnormal power ranges within the charging power range;

[0031] Figure 4 This is a flowchart illustrating the method for determining the charging risk coefficient of a charging station.

[0032] Figure 5 It is a framework diagram of a computer system. Detailed Implementation

[0033] 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 with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this specification, and not all embodiments. Based on the embodiments of this specification, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of this specification.

[0034] In this application, charging piles with high temperature anomalies are screened and early warning is issued by using data on abnormal temperature rises in different temperature ranges and future distribution data of different temperature ranges, thereby improving the operational reliability of charging piles.

[0035] The charging pile is identified by the number of temperature anomalies in different ambient temperature ranges. Ambient temperature ranges with more than a preset number of anomalies are defined as abnormal ranges. The weighting coefficients of different abnormal ranges are determined by the proportion of time periods in different ambient temperature ranges within a preset future time period. When the sum of the weighting coefficients of different abnormal ranges is greater than 0.6, it is determined that the charging pile needs to be given an early warning.

[0036] The abnormal power range is the charging power range where the number of temperature anomalies exceeds 20.

[0037] The charging risk coefficient of a charging pile is determined based on the sum of the proportions of historical charging times within different abnormal power ranges. When the charging risk coefficient of a charging pile is between 0.3 and 0.7, the charging risk coefficient of the charging pile is determined to be within the preset range.

[0038] When the proportion of charging piles with a charging risk coefficient greater than that of the charging pile in a charging station is less than 0.2, it is determined that the charging pile needs to output a warning signal.

[0039] Example 1

[0040] like Figure 1 As shown, this application provides a first aspect, namely, a method for monitoring and early warning of charging piles, specifically including:

[0041] S1 uses the analysis results of the monitoring data of the charging pile to determine the abnormal temperature data of the charging pile in different ambient temperature ranges, and combines the time distribution data of different ambient temperature ranges in the future preset time period to determine that the charging pile does not need to be 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 the preset temperature interval.

[0043] Specifically, the temperature anomaly data includes the number of temperature anomalies, the temperature at different times of the anomaly, and the duration of the anomaly.

[0044] It should be noted that the preset time period is determined based on the historical charging data of the charging station. The more vehicles the charging station charges on average per day, the shorter the preset time period will be.

[0045] It is understood that the preset time period is determined based on the correspondence between the average number of vehicles charging per day 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, such as Figure 2 As shown, determining that the charging pile does not require early warning processing specifically includes:

[0048] Using temperature anomaly data of charging piles in different ambient temperature ranges, the number of temperature anomalies of charging piles in different ambient temperature ranges is determined, and the total duration of different ambient temperature ranges is determined by combining the duration of different temperature anomalies.

[0049] Based on the time period distribution data of different ambient temperature ranges within a future preset time period, determine the proportion of time periods in different ambient temperature ranges, and use the proportion of time periods to determine the weighting coefficient of different ambient temperature ranges.

[0050] Based on the weighting coefficients and the total duration of different ambient temperature ranges, 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 given an early warning.

[0051] Furthermore, the estimated abnormal duration of the charging pile is the sum of the products of the total duration of different ambient temperature ranges and the weighting coefficient.

[0052] It is understandable that when the estimated abnormal duration of the charging pile exceeds the preset abnormal duration, it is determined that the charging pile needs to be given an early warning.

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

[0054] Using temperature anomaly data of charging piles in different ambient temperature ranges, the number of temperature anomalies of charging piles in different ambient temperature ranges is determined, and the total duration of different ambient temperature ranges is determined by combining the duration of different temperature anomalies.

[0055] The abnormal intervals within the ambient temperature range are determined using the total duration. The distribution data of time periods within different ambient temperature ranges in a future preset time period are used to determine the proportion of time periods in different ambient temperature ranges. The weighting coefficients of different abnormal intervals are then determined using the proportion of time periods.

[0056] Whether the charging pile needs to be given an early warning is determined by summing the weighting coefficients of different abnormal intervals.

[0057] Furthermore, when the sum of the weight coefficients of different abnormal intervals is greater than the preset weight coefficient, it is determined that the charging pile needs to be given an early warning.

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

[0059] S11 uses temperature anomaly data of charging piles in different ambient temperature ranges to determine the number of temperature anomalies in different ambient temperature ranges, and combines the duration of different temperature anomalies to determine the temperature anomaly coefficient for different ambient temperature ranges.

[0060] S12 uses the total duration to determine the abnormal temperature range within the ambient temperature range, uses the time period distribution data of different ambient temperature ranges within a future preset time period to determine the proportion of time periods in different ambient temperature ranges, and uses the proportion of time periods to determine the weighting coefficient of different temperature ranges.

[0061] S13 determines the weighted sum of the temperature anomaly coefficients based on the weighting coefficients of different ambient temperature ranges and the temperature anomaly coefficients, and uses this sum as the comprehensive anomaly coefficient. The comprehensive anomaly coefficient is then used to determine whether the charging pile needs to be given an early warning.

[0062] Furthermore, if the comprehensive anomaly coefficient does not meet the requirements, it is determined that the charging pile needs to be subject to early warning processing.

[0063] S2 divides the abnormal temperature data to obtain abnormal temperature data in different charging power ranges. Based on the abnormal temperature data in different ambient temperature ranges within the charging power range, the abnormal power range in the charging power range is determined.

[0064] Specifically, such as Figure 3 As shown, the method for determining the abnormal power range within the charging power range is as follows:

[0065] Based on the temperature anomaly data in different ambient temperature ranges within the charging power range, determine the number of temperature anomalies in different ambient temperature ranges.

[0066] The abnormal temperature range within the ambient temperature range is determined based on the number of temperature anomalies.

[0067] The number of abnormal temperature ranges determines whether the charging power range is an abnormal power range.

[0068] It should be noted that the abnormal temperature range refers to the ambient temperature range in which the number of abnormal temperature occurrences does not meet the requirements.

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

[0070] In another embodiment, the method for determining the abnormal power range within the charging power range is as follows:

[0071] Based on the temperature anomaly data in different ambient temperature ranges within the charging power range, determine the number of temperature anomalies in different ambient temperature ranges.

[0072] The total number of temperature anomalies in the charging power range is determined based on the number of temperature anomalies within different ambient temperature ranges.

[0073] The total number of temperature anomalies determines whether the charging power range is an abnormal power range.

[0074] Furthermore, if the total number of abnormal temperature events does not meet the requirements, then the charging power range is determined to be an abnormal power range.

[0075] Optionally, the method for determining the abnormal power range within the charging power range is as follows:

[0076] S21 uses the temperature anomaly data in different ambient temperature ranges within the charging power range to determine the number of temperature anomalies in different ambient temperature ranges.

[0077] S22 determines the interval anomaly value for different ambient temperature ranges based on the number of temperature anomalies within different ambient temperature ranges and the duration of different temperature anomalies.

[0078] S23 determines the charging anomaly coefficient of the charging power range based on the range anomaly values ​​within different ambient temperature ranges, and uses the charging anomaly coefficient to determine whether the charging power range is an abnormal power range.

[0079] Furthermore, the method for determining the outliers within the ambient temperature range is as follows:

[0080] Based on the duration of different temperature anomalies, preset anomaly values ​​corresponding to different temperature anomaly frequencies are determined;

[0081] The interval anomaly value of the ambient temperature range is determined by the sum of preset anomaly values ​​based on the number of different temperature anomalies.

[0082] It should be noted that the charging anomaly coefficient of the charging power range is determined based on the weighted sum of the range anomaly values ​​within different ambient temperature ranges.

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

[0084] S211 uses the temperature anomaly data in different ambient temperature ranges within the charging power range to determine the number of temperature anomalies in different ambient temperature ranges. When the number of temperature anomalies is less than a preset threshold, proceed to step S212. When the number of temperature anomalies is not less than the preset threshold, proceed to step S213.

[0085] S212 When the number of ambient temperature ranges with abnormal temperature occurrences is less than the number of preset temperature ranges, it is determined that the charging power range does not belong to the abnormal power range. When the number of ambient temperature ranges with abnormal temperature occurrences is not less than the number of preset temperature ranges, proceed to step S213.

[0086] S213 Obtain the ambient temperature range where the number of temperature anomalies is greater than the preset number of anomalies. When the number of ambient temperature ranges where the number of temperature anomalies is greater than the preset number of anomalies is greater than the preset number of ranges, it is determined that the charging power range belongs to the abnormal power range. When the number of ambient temperature ranges where the number of temperature anomalies is greater than the preset number of anomalies is not greater than the preset number of ranges, proceed to step S22.

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

[0088] S221 determines the interval anomaly value for different ambient temperature intervals based on the number of temperature anomalies in different ambient temperature intervals and the duration of different temperature anomalies. If there is no ambient temperature interval whose interval anomaly value does not meet the requirements, proceed to step S222. If there is an ambient temperature interval whose interval anomaly value does not meet the requirements, proceed to step S223.

[0089] S222 When the sum of the abnormal values ​​of different ambient temperature ranges is less than the preset abnormal threshold, the charging power range is determined to be an abnormal power range. When the sum of the abnormal values ​​of different ambient temperature ranges is not less than the preset abnormal threshold, proceed to step S23.

[0090] S223 When the number of ambient temperature ranges whose abnormal values ​​do not meet the requirements is greater than the preset range number threshold, the charging power range is determined to be an abnormal power range. When the number of ambient temperature ranges whose abnormal values ​​do not meet the requirements is not greater than the preset range number threshold, proceed to step S23.

[0091] S3 determines the historical charging data in different abnormal power ranges based on the historical charging data of the charging station where the charging pile is located, and uses the historical charging data in different abnormal power ranges to determine that the charging risk coefficient of the charging pile is within a preset range, and then proceeds to the next step.

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

[0093] By using historical charging data within different abnormal power ranges, the number of historical charges within different abnormal power ranges can be determined.

[0094] Based on the charging duration of the historical charging times within different abnormal power ranges, the effective charging times among the historical charging times are determined.

[0095] The charging risk coefficient of the charging pile is determined based on the number of effective charging cycles.

[0096] Furthermore, the effective charging count is the number of historical charging times whose charging duration is greater than the preset charging duration.

[0097] It is understood that the charging risk coefficient of the charging pile is determined based on 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 as follows:

[0100] By using historical charging data in different abnormal power ranges, the number of historical charging times in different abnormal power ranges is determined. When the total number of historical charging times in different abnormal power ranges is greater than a preset charging time threshold, it is determined that the charging pile needs to output a warning signal.

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

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

[0103] When the total number of historical charging times in different abnormal power ranges 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 cycles within different abnormal power ranges is not less than the set value for the number of charging cycles:

[0105] The total charging time for different historical charging cycles is determined by the charging time of different historical charging cycles. When the total charging time for different historical charging cycles does not meet the requirements, it is determined 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 within different abnormal power ranges, the effective charging times in the historical charging times are determined. When the effective charging times are greater than a preset effective charging times threshold, it is determined that the charging pile needs to output a warning signal.

[0108] When the number of valid charging cycles is not greater than a preset valid cycle threshold:

[0109] Based on the historical number of charges and the charging duration of those historical charges within different abnormal power ranges, a charging demand coefficient for each abnormal power range is determined. When there is an abnormal power range where the charging demand coefficient exceeds a preset demand coefficient threshold:

[0110] When the number of abnormal power ranges where the charging demand coefficient is greater than the preset demand coefficient threshold is greater than the preset number of power ranges, it is determined that the charging pile needs to output a warning signal.

[0111] When there are no abnormal power ranges with charging demand coefficients greater than the preset demand coefficient threshold, or when the number of abnormal power ranges with charging demand coefficients greater than the preset demand coefficient threshold is not greater than the preset number of power ranges:

[0112] The charging risk coefficient of the charging pile is determined based on the charging demand coefficient for different abnormal power ranges.

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

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

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

[0116] Based on the proportion of risky charging piles, determine whether the charging pile needs to output a warning signal.

[0117] It should be noted that the risky charging pile refers to a charging pile with a charging risk coefficient greater than the charging risk coefficient of the charging pile itself.

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

[0119] Example 2

[0120] Secondly, such as Figure 5 As shown, the present invention provides a computer system, including: a memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the above-described charging pile monitoring and early warning method when running the computer program.

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

[0122] S111 uses the temperature anomaly data of the charging pile in different ambient temperature ranges to determine the number of temperature anomalies in different ambient temperature ranges. When the total number of temperature anomalies of the charging pile does not meet the requirements, it is determined that the charging pile needs to be given an early warning. When the total number of temperature anomalies of the charging pile meets the requirements, proceed to step S112.

[0123] S112 determines the total duration of different temperature anomalies based on the duration of different temperature anomalies. If the total duration does not meet the requirements, it is determined that the charging pile needs to be given an early warning. If the total duration meets the requirements, proceed to step S113.

[0124] S113 determines the basic anomaly coefficient based on the number of temperature anomalies and the duration of different temperature anomalies. When the basic anomaly coefficient is within the preset anomaly coefficient range, proceed to step S114. When the basic anomaly coefficient is not within the preset anomaly coefficient range, it is determined that the charging pile does not need to perform early warning processing.

[0125] S114 determines the temperature anomaly coefficient for different ambient temperature ranges based on the number of temperature anomalies in different ambient temperature ranges and the duration of different temperature anomalies. If there is an ambient temperature range where the temperature anomaly coefficient does not meet the requirements, proceed to step S115. If there is no ambient temperature range where the temperature anomaly coefficient does not meet the requirements, proceed to step S12.

[0126] S115 When the number of ambient temperature ranges whose temperature anomaly coefficient does not meet the requirements is greater than the number of preset temperature ranges, it is determined that the charging pile needs to be given an early warning. When the number of ambient temperature ranges whose temperature anomaly coefficient does not meet the requirements is not greater than the number of preset temperature ranges, proceed to step S12.

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

[0128] S121 uses the total duration to determine the abnormal temperature range within the ambient temperature range, uses the time period distribution data of different ambient temperature ranges within a future preset time period to determine the proportion of time periods in different ambient temperature ranges, and uses the proportion of time periods to determine the weighting coefficient of different temperature ranges.

[0129] S122 defines the ambient temperature range where the temperature anomaly coefficient does not meet the requirements as the anomaly range. When the sum of the weight coefficients of the anomaly range is greater than the preset weight coefficient, it is determined that the charging pile needs to be given an early warning. When the sum of the weight coefficients of the anomaly range is not greater than the preset weight coefficient, the process proceeds to step S123.

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

[0131] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on describing the differences from other embodiments. In particular, the embodiments of apparatus, devices, and non-volatile computer storage media are basically similar to the method embodiments, so the descriptions are relatively simple; relevant parts can be referred to the descriptions of the method embodiments.

[0132] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0133] The above description is merely one or more embodiments of this specification and is not intended to limit this specification. Various modifications and variations can be made to the one or more embodiments of this specification by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principle of one or more embodiments of this specification should be included within the scope of the claims of this specification.

Claims

1. A method for monitoring and early warning of charging piles, characterized in that, Specifically, it includes: Based on the analysis results of the monitoring data of the charging pile, the abnormal temperature data of the charging pile in different ambient temperature ranges are determined. Combined with the time distribution data of different ambient temperature ranges in the future preset time period, if it is determined that the charging pile does not need to be given an early warning, the next step is initiated. The abnormal temperature data is divided into different charging power ranges. Based on the abnormal temperature data in different ambient temperature ranges within the charging power range, the abnormal power range within the charging power range is determined. Based on the historical charging data of the charging station where the charging pile is located, the historical charging data in different abnormal power ranges is determined, and the charging risk coefficient of the charging pile is determined to be within a preset range using the historical charging data in different abnormal power ranges, and then proceeds to the next step. Based on the charging risk coefficient of different charging piles in the charging station, determine whether the charging pile needs to output a warning signal; Determining that the charging pile does not require early warning processing specifically includes: Using temperature anomaly data of charging piles in different ambient temperature ranges, the number of temperature anomalies of charging piles in different ambient temperature ranges is determined, and the total duration of different ambient temperature ranges is determined by combining the duration of different temperature anomalies. Based on the time period distribution data of different ambient temperature ranges within a future preset time period, determine the proportion of time periods in different ambient temperature ranges, and use the proportion of time periods to determine the weighting coefficient of different ambient temperature ranges. Based on the weighting coefficients and the total duration of different ambient temperature ranges, 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 given an early warning.

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

3. The charging pile monitoring and early warning method as described in claim 1, characterized in that, The temperature anomaly data includes the number of temperature anomalies, the temperature at different times of the anomaly, and the duration of the anomaly.

4. The charging pile monitoring and early warning method as described in claim 1, characterized in that, The preset time period is determined based on the historical charging data of the charging station. The more vehicles the charging station charges on average per day, the shorter the preset time period will be.

5. The charging pile monitoring and early warning method as described in claim 1, characterized in that, If the estimated abnormal duration of the charging pile exceeds the preset abnormal duration, then it is determined that the charging pile needs to be given an early warning.

6. The charging pile monitoring and early warning method as described in claim 1, characterized in that, Determining whether the charging pile needs to output a warning signal specifically includes: Based on whether the charging risk coefficient of different charging piles in the charging station is greater than the charging risk coefficient of the charging pile, the charging piles are divided into safe charging piles and risky charging piles. Based on the proportion of risky charging piles, determine whether the charging pile needs to output a warning signal.

7. The charging pile monitoring and early warning method as described in claim 6, characterized in that, The risky charging pile is a charging pile whose charging risk coefficient is greater than that of the charging pile itself.

8. The charging pile monitoring and early warning method as described in claim 6, characterized in that, When the proportion of the number of risky charging piles is greater than the preset proportion of the number of charging piles, it is determined that the charging pile needs to output a warning signal.

9. A computer system, comprising: A memory and a processor connected in communication, and a computer program stored in the memory and capable of running on the processor, characterized in that, when the processor runs the computer program, it executes a charging pile monitoring and early warning method according to any one of claims 1-8.

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