Method, system and device for monitoring the whole life cycle of a charging facility and storage medium

Abstract

The application provides a full life cycle monitoring method, system and device of a charging facility and a storage medium, relates to the technical field of charging facility operation and maintenance, and comprises the following steps: determining the remaining use duration of a charging pile according to the used duration of the charging pile; generating a correction coefficient according to the use data of the charging pile within the used duration, adjusting the remaining use duration according to the correction coefficient, and generating a first remaining use duration; generating an environment adjustment coefficient according to the environment parameters of the environment in which the charging pile is located, adjusting the first remaining use duration according to the environment adjustment coefficient, and generating a second remaining use duration; calculating an interference coefficient according to the operation data of other charging piles within the used duration according to the operation data; and adjusting the second remaining use duration according to the interference coefficient, and generating a target remaining use duration. The application has the technical effect of reducing the deviation between the prediction result and the actual remaining life.

Description

Technical Field

[0001] This application relates to the field of charging facility monitoring and maintenance technology, specifically to a method, system, device, and storage medium for monitoring the entire life cycle of charging facilities. Background Technology

[0002] With the rapid development of the new energy vehicle industry, the large-scale deployment of charging infrastructure has become a crucial support for the industry's development. Accurately predicting the remaining lifespan of charging piles is essential for equipment maintenance and upgrade planning during the operation of charging facilities.

[0003] In existing technologies, the remaining lifespan of a charging pile is usually predicted based on its standard service life, combined with its operating time and usage intensity. While this method can meet the basic requirements for predicting the remaining lifespan of a charging pile, it ignores various dynamic influencing factors that exist during the use of the charging pile, resulting in a large deviation between the predicted results and the actual remaining lifespan. Summary of the Invention

[0004] This application provides a method, system, device, and storage medium for monitoring the entire lifecycle of charging facilities, which reduces the deviation between the predicted results and the actual remaining lifespan.

[0005] Firstly, this application provides a method for monitoring the entire lifecycle of charging facilities. The method includes: determining the remaining usage time of a charging pile based on its standard service life and the usage time already taken; acquiring usage data of the charging pile within the used time, generating a correction coefficient based on the usage data, and adjusting the remaining usage time based on the correction coefficient to generate a first remaining usage time; acquiring environmental parameters of the environment where the charging pile is located within the used time, generating an environmental adjustment coefficient based on the environmental parameters, and adjusting the first remaining usage time based on the environmental adjustment coefficient to generate a second remaining usage time; calculating an interference coefficient based on the operating data of other charging piles within the used time, wherein the other charging piles are those connected to the same distribution transformer as the charging pile; and adjusting the second remaining usage time based on the interference coefficient to generate a target remaining usage time.

[0006] By adopting the above technical solution, based on the standard service life of charging piles, a correction coefficient is generated by combining the actual usage data of charging piles, an environmental adjustment coefficient is generated by combining environmental parameters, and a mutual interference coefficient is calculated by combining the operating data of other charging piles under the same distribution transformer. The remaining usage time is adjusted in multiple dimensions and at multiple levels, and a more accurate target remaining usage time is finally obtained. This effectively improves the accuracy and reliability of the prediction of the remaining life of charging facilities and reduces the deviation between the prediction results and the actual remaining life.

[0007] Optionally, the usage data includes the number of charging cycles and the average charge amount per charge. The step of generating a correction coefficient based on the usage data includes: calculating a first difference between the number of charging cycles and the standard number of charging cycles, and generating a first correction coefficient based on the first difference; calculating a second difference between the average charge amount and the rated charging capacity, and generating a second correction coefficient based on the second difference; and performing a weighted summation of the first correction coefficient and the second correction coefficient to generate a correction coefficient.

[0008] By adopting the above technical solution, a first correction coefficient and a second correction coefficient are generated by the first difference between the number of charging times and the standard number of charging times, and the second difference between the average charging amount and the rated charging capacity, respectively. The two correction coefficients are then weighted and summed to obtain the correction coefficient. This achieves a comprehensive quantitative assessment of the charging pile usage intensity, taking into account both the impact of charging frequency on equipment lifespan and the effect of charging load on equipment wear and tear. This makes the correction coefficient more objectively reflect the actual usage status of the charging pile, thereby improving the accuracy of the remaining usage time prediction.

[0009] Optionally, adjusting the remaining usage time according to the correction coefficient to generate a first remaining usage time includes: performing an arithmetic multiplication of the correction coefficient and the remaining usage time to generate the first remaining usage time.

[0010] By adopting the above technical solution, the first remaining usage time is obtained by arithmetically multiplying the correction coefficient with the remaining usage time, which realizes the linear adjustment of the remaining lifespan by the usage intensity. This makes the adjustment process of the remaining usage time simple and intuitive, has high calculation efficiency, and can accurately reflect the degree of influence of the actual usage intensity of the charging pile on its remaining lifespan.

[0011] Optionally, generating an environmental adjustment coefficient based on the environmental parameters includes: determining, based on the environmental parameters, a first duration during which the temperature of the environment where the charging pile is located exceeds a first preset temperature and a second duration during which the temperature is below a second preset temperature within the used time period, wherein the first preset temperature is greater than the second preset temperature; determining a temperature influence coefficient of the charging pile based on the sum of the first duration and the second duration; determining, based on the environmental parameters, a third duration during which the humidity of the environment where the charging pile is located exceeds a third preset humidity and a fourth duration during which the humidity is below a fourth preset humidity within the used time period, wherein the third preset humidity is greater than the fourth preset humidity; determining a humidity influence coefficient of the charging pile based on the sum of the third duration and the fourth duration; determining the influence level of the environment on the charging pile from a preset database based on the magnitudes of the temperature influence coefficient and the humidity influence coefficient, and generating an environmental adjustment coefficient based on the influence level.

[0012] By adopting the above technical solution, the temperature influence coefficient and humidity influence coefficient are determined by statistically analyzing the duration of ambient temperature exceeding the first preset temperature and falling below the second preset temperature, and the duration of ambient humidity exceeding the third preset humidity and falling below the fourth preset humidity. Based on these two influence coefficients, the environmental impact level is determined from the preset database, and then the environmental adjustment coefficient is generated. This achieves accurate statistical and quantitative evaluation of the charging pile's operating time under extreme temperature and humidity conditions, so that the impact of environmental factors on the charging pile's lifespan can be more accurately reflected in the calculation of the remaining usage time.

[0013] Optionally, adjusting the first remaining usage time according to the environmental adjustment coefficient to generate a second remaining usage time includes: arithmetically multiplying the environmental adjustment coefficient by the first remaining usage time to generate the second remaining usage time.

[0014] By adopting the above technical solution, the second remaining usage time is obtained by arithmetically multiplying the environmental adjustment coefficient with the first remaining usage time. This achieves a direct linear adjustment of the remaining lifespan by environmental factors, enabling the environmental impact to be quantified into the calculation of the remaining usage time in a simple and clear manner. This ensures both the efficiency of the calculation process and the accurate reflection of the impact of environmental factors on the lifespan of the charging pile.

[0015] Optionally, calculating the mutual interference coefficient based on the operating data includes: obtaining the first charging duration of the other charging piles within the used time period and the second charging duration of the charging piles within the used time period; calculating the overlap duration of the first charging duration and the second charging duration; obtaining the power ratio of the total charging power of the other charging piles to the rated power of the distribution transformer within the overlap duration; determining the power occupancy coefficient based on the power ratio; and generating the mutual interference coefficient based on the power occupancy coefficient, wherein the power occupancy coefficient is positively correlated with the mutual interference coefficient.

[0016] By adopting the above technical solution, the overlap of charging time between charging piles and other charging piles is calculated, and the power occupancy factor is determined based on the ratio of the total charging power of other charging piles to the rated power of the distribution transformer within the overlap period. Then, a mutual interference factor positively correlated with the power occupancy factor is generated, which realizes the accurate quantification of the load superposition effect of multiple charging piles running in parallel under the same distribution transformer, and effectively reflects the actual impact of mutual influence between charging piles on the equipment life.

[0017] Optionally, adjusting the second remaining usage time according to the mutual interference coefficient to generate a target remaining usage time includes: determining the attenuation time corresponding to the mutual interference coefficient; and subtracting the attenuation time from the second remaining usage time to obtain the target remaining usage time.

[0018] By adopting the above technical solution, the attenuation time is determined based on the mutual interference coefficient, and the target remaining usage time is obtained by subtracting the attenuation time from the second remaining usage time. This achieves a quantitative reduction in the impact of mutual interference between charging piles on the equipment lifespan, so that the final remaining lifespan prediction result can accurately reflect the actual wear and tear of the equipment lifespan caused by the load superposition effect of multiple charging piles running in parallel.

[0019] Secondly, this application provides a full lifecycle monitoring system for charging facilities, the system comprising: a determining module, a first adjusting module, a second adjusting module, a calculating module, and a third adjusting module; wherein,

[0020] The determining module is used to determine the remaining usage time of the charging pile based on its standard service life and the usage time already taken. The first adjustment module is used to acquire usage data of the charging pile within the usage time, generate a correction coefficient based on the usage data, and adjust the remaining usage time according to the correction coefficient to generate a first remaining usage time. The second adjustment module is used to acquire environmental parameters of the environment where the charging pile is located within the usage time, generate an environmental adjustment coefficient based on the environmental parameters, and adjust the first remaining usage time according to the environmental adjustment coefficient to generate a second remaining usage time. The calculation module is used to calculate an interference coefficient based on the operating data of other charging piles within the usage time, wherein the other charging piles are those connected to the same distribution transformer as the charging pile. The third adjustment module is used to adjust the second remaining usage time according to the interference coefficient to generate a target remaining usage time.

[0021] Thirdly, this application provides an electronic device that adopts the following technical solution: including a processor, a memory, a user interface, and a network interface, wherein the memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to enable the electronic device to execute a computer program such as the full life cycle monitoring method of any of the above-mentioned charging facilities.

[0022] Fourthly, this application provides a computer-readable storage medium that stores a computer program capable of being loaded by a processor and executing any of the above-mentioned charging facility lifecycle monitoring methods.

[0023] In summary, this application includes at least one of the following beneficial technical effects:

[0024] Based on the standard service life of charging piles, correction coefficients are generated by combining actual usage data of charging piles, environmental adjustment coefficients are generated by combining environmental parameters, and mutual interference coefficients are calculated by combining the operating data of other charging piles under the same distribution transformer. The remaining usage time is adjusted in multiple dimensions and at multiple levels, and finally a more accurate target remaining usage time is obtained. This effectively improves the accuracy and reliability of the prediction of the remaining life of charging facilities and reduces the deviation between the prediction results and the actual remaining life. Attached Figure Description

[0025] Figure 1 This is a flowchart illustrating a method for monitoring the entire lifecycle of charging facilities according to an embodiment of this application;

[0026] Figure 2This is a schematic diagram of the structure of a full life-cycle monitoring system for charging facilities provided in an embodiment of this application;

[0027] Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application.

[0028] Explanation of reference numerals in the attached figures: 1000, electronic device; 1001, processor; 1002, communication bus; 1003, user interface; 1004, network interface; 1005, memory. Detailed Implementation

[0029] 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 application, and not all embodiments.

[0030] In the description of the embodiments in this application, words such as "illustrative," "for example," or "for example" are used to indicate examples, illustrations, or explanations. Any embodiment or design described as "illustrative," "for example," or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or designs. Rather, the use of words such as "illustrative," "for example," or "for example" is intended to present the relevant concepts in a specific manner.

[0031] Figure 1 This is a flowchart illustrating a method for monitoring the entire lifecycle of charging facilities according to an embodiment of this application. Figure 1 As shown, the method includes S101-S105:

[0032] S101 determines the remaining usage time of a charging pile based on its standard service life and the usage time already accumulated, according to the charging pile's existing usage time.

[0033] As a crucial component of electric vehicle charging infrastructure, the lifespan of charging piles directly impacts the reliability of charging services and operating costs. Standard lifespan refers to the expected duration a charging pile can operate normally under ideal operating conditions and standard usage intensity. It is typically determined by the charging pile manufacturer based on design specifications and test data; for example, the standard lifespan of a certain model of charging pile may be 10 years.

[0034] In this embodiment, the standard service life data of the charging pile can be obtained from its equipment file information, and the installation time of the charging pile can be obtained from the charging pile's operation management system. The time difference between the current time and the installation time is determined as the usage time. By subtracting the usage time from the standard service life, the remaining usage time of the charging pile can be obtained. For example, if the standard service life of a charging pile is 10 years (equivalent to 87,600 hours), and the current usage time is 3 years (equivalent to 26,280 hours), then its remaining usage time is 61,320 hours. This preliminary assessment based on the standard service life provides a benchmark value for subsequent life correction based on actual usage, helping charging facility operators to rationally plan equipment maintenance and upgrades, and improve the operational efficiency of charging infrastructure. However, since the actual usage intensity, usage environment, and mutual interference of charging piles differ from the standard state, the accuracy of remaining life assessment based solely on the standard service life is limited. Therefore, further adjustments are needed based on multiple influencing factors.

[0035] S102, obtain the usage data of the charging pile within the usage time, generate a correction coefficient based on the usage data, adjust the remaining usage time based on the correction coefficient, and generate the first remaining usage time.

[0036] Specifically, the first step is to calculate the difference between the number of charging attempts and the standard number of charging attempts. The standard number of charging attempts refers to the expected number of charging attempts within the charging station's existing usage time, which can be determined according to the charging station's design specifications. For example, a charging station has been in use for 3 years, with an actual charging attempt of 4500 times and an expected charging attempt of 3600 times. Then, the first difference is calculated: Actual charging attempts - Expected charging attempts = 4500 - 3600 = 900 times. In this example, the first difference is positive (900 times), indicating that the charging station's usage frequency over the past 3 years is higher than expected. Therefore, the first correction factor should be less than 1, used to reduce the remaining usage time. When the first difference is negative, it indicates that the charging station's usage frequency is lower than expected, and the first correction factor is greater than 1, used to increase the remaining usage time.

[0037] Simultaneously, a second difference between the average charging amount and the rated charging capacity is calculated. The rated charging capacity refers to the product of the charging pile's designed charging power and the standard charging time. For example, if the actual average charging amount of the charging pile is 80 kWh and the rated charging capacity is 60 kWh, then the second difference is 20 kWh. A second correction coefficient is generated based on the magnitude of this second difference. When the second difference is positive, it indicates that the charging load is higher than the design value, and the second correction coefficient is less than 1; when the second difference is negative, it indicates that the charging load is lower than the design value, and the second correction coefficient is greater than 1.

[0038] The first and second correction coefficients are weighted and summed to generate the final correction coefficient. The weighting coefficients can be set according to the influence of the number of charging cycles and average charging amount on the lifespan of the charging station. For example, if the first correction coefficient is 0.9 with a weight of 0.6, and the second correction coefficient is 0.8 with a weight of 0.4, then the final correction coefficient is 0.9 × 0.6 + 0.8 × 0.4 = 0.86.

[0039] Finally, the correction factor is arithmetically multiplied by the remaining usage time obtained in S101 to generate the first remaining usage time. For example, if the original remaining usage time is 84 months and the correction factor is 0.86, then the first remaining usage time is 72.24 months.

[0040] Based on the above embodiments, as an optional implementation, in S102, the data used includes the number of charging cycles and the average charging amount per charge. The generation of correction coefficients based on the data specifically includes S21-S23:

[0041] S21, calculate the first difference between the number of charging cycles and the standard number of charging cycles, and generate a first correction coefficient based on the first difference.

[0042] The standard number of charging cycles refers to the expected number of charging cycles for a charging station within its usage period, which can be determined according to the charging station's design specifications. For example, if a charging station has been in use for 3 years, the actual number of charging cycles in these 3 years is 4500, and the expected number of charging cycles is 3600. Then, calculate the first difference: actual number of charging cycles - expected number of charging cycles = 4500 - 3600 = 900 cycles. Since the first difference is 900, the average monthly difference is: 900 ÷ 36 months = 25 times / month. Based on the average monthly difference, a first correction coefficient is generated according to the preset correction rules: when the average monthly difference is in the range of 0-15 times / month, the first correction coefficient is 1.0; when the average monthly difference is in the range of 16-30 times / month, the first correction coefficient is 0.9; when the average monthly difference is in the range of 31-45 times / month, the first correction coefficient is 0.8; when the average monthly difference exceeds 45 times / month, the first correction coefficient is 0.7; when the average monthly difference is less than 0 times / month, the first correction coefficient is 1.1.

[0043] S22, calculate the second difference between the average charging amount and the rated charging capacity, and generate a second correction coefficient based on the second difference.

[0044] Rated charging capacity refers to the designed charging capacity of a charging pile under standard charging conditions, determined by the charging pile's rated power and standard charging duration. For example, if a charging pile has a rated charging capacity of 60 kWh and the actual average charging capacity is 75 kWh, then the second difference is 15 kWh. Similarly, based on the magnitude of the second difference, a similar segmented approach is used to generate a second correction coefficient: when the second difference is in the range of -10 to 10 kWh, the second correction coefficient is 0.95-1.05; when the second difference is in the range of 11 to 20 kWh, the second correction coefficient is 0.85-0.95; when the second difference exceeds 20 kWh, the second correction coefficient is 0.7-0.85; and when the second difference is less than -10 kWh, the second correction coefficient is 1.05-1.15.

[0045] S23, the first correction coefficient and the second correction coefficient are weighted and summed to generate the correction coefficient.

[0046] The first and second correction coefficients are weighted and summed to generate the final correction coefficient. The weighting needs to consider the relative importance of charging frequency and charging load on the charging pile's lifespan. Generally, charging frequency has a slightly greater impact on the charging pile's lifespan than charging load; therefore, the weight of the first correction coefficient can be set to 0.6, and the weight of the second correction coefficient to 0.4. The specific method for determining the weight coefficients depends on the actual situation. For example, if the first correction coefficient is 0.9 and the second correction coefficient is 0.85, then the final correction coefficient is 0.9 × 0.6 + 0.85 × 0.4 = 0.88.

[0047] Based on the above embodiments, as an optional implementation method, in S102, adjusting the remaining usage time according to the correction coefficient to generate the first remaining usage time specifically includes: multiplying the correction coefficient and the remaining usage time arithmetically to generate the first remaining usage time.

[0048] S103: Obtain the environmental parameters of the charging pile's environment within the usage time, generate an environmental adjustment coefficient based on the environmental parameters, adjust the first remaining usage time based on the environmental adjustment coefficient, and generate a second remaining usage time.

[0049] In this embodiment, since charging piles are typically installed outdoors, their performance and lifespan are significantly affected by environmental factors. To accurately assess the impact of the environment on the charging pile's lifespan, it is necessary to obtain environmental parameters of the charging pile's location over the duration of its use through an environmental monitoring system. These parameters primarily include temperature and humidity data. These environmental parameters are collected in real-time by sensors installed around the charging pile and recorded and stored periodically.

[0050] Regarding the temperature impact assessment, the first step is to determine the first duration during which the ambient temperature of the charging pile exceeds a first preset temperature and the second duration during which it falls below a second preset temperature within the total usage time. The first preset temperature is typically set at 40℃, and the second preset temperature is typically set at -10℃. These two temperature values ​​are determined based on the temperature resistance characteristics of the charging pile's electronic components. For example, in 36 months of use for a certain charging pile, the cumulative duration of ambient temperature exceeding 40℃ (i.e., the first duration) is 360 hours, and the cumulative duration of temperature below -10℃ (i.e., the second duration) is 240 hours. The temperature impact coefficient of the charging pile is determined based on the proportion of the sum of the first and second durations (600 hours in this example) to the total usage time.

[0051] In assessing the impact of humidity, it is also necessary to determine the third duration for which the ambient humidity exceeds the third preset humidity level, and the fourth duration for which it falls below the fourth preset humidity level. The third preset humidity level is typically set at 85% RH, and the fourth preset humidity level is typically set at 20% RH. These two humidity values ​​are determined based on the charging pile's protection level and component reliability requirements. For example, within the total usage time, the cumulative duration for which the ambient humidity exceeds 85% RH (i.e., the third duration) is 480 hours, and the cumulative duration for which it falls below 20% RH (i.e., the fourth duration) is 120 hours. The humidity impact coefficient of the charging pile is determined based on the proportion of the sum of the third and fourth durations (600 hours in this example) to the total usage time.

[0052] The system determines the level of environmental impact on charging stations based on the magnitude of temperature and humidity influence coefficients from a preset database. This database stores the impact levels corresponding to different combinations of temperature and humidity influence coefficients, categorized as, for example, minor, moderate, and severe impacts. Each impact level corresponds to a preset environmental adjustment coefficient; the more severe the impact, the smaller the environmental adjustment coefficient. For example, when the impact is determined to be moderate, the corresponding environmental adjustment coefficient is 0.9.

[0053] The pre-built database is primarily based on the following data sources and analysis methods: First, it uses component reliability data provided by charging pile equipment manufacturers as a fundamental reference. Key components in charging piles, such as power modules, control circuits, and communication modules, all have their own operating environment specifications. For example, data includes performance curves of power modules at different temperatures and failure rates of electronic components under different humidity environments. This data comes from laboratory test results and long-term usage statistics from component manufacturers.

[0054] Secondly, statistical analysis is conducted using a large amount of historical data from actual charging piles in operation. For example, the failure rate of the same model of charging piles operating in different climate zones is compared with environmental conditions. Specifically, samples of charging piles operating in different environments, such as typical cold northern regions, humid southern regions, and high-salt coastal regions, can be selected to collect their operating data and failure records, and the correlation between environmental factors and equipment lifespan can be analyzed.

[0055] Secondly, data support is obtained through accelerated aging tests. Under laboratory conditions, charging piles are subjected to environmental stress tests such as high temperature, low temperature, high humidity, and alternating temperature and humidity to record the patterns of equipment performance degradation and failure occurrence. For example, continuous operation at 40℃ for 100 hours is equivalent to operation time at normal temperature, thereby establishing a quantitative relationship between environmental stress and lifespan loss.

[0056] Based on the above data, the preset database adopts the following structure design: Temperature impact assessment matrix: When the duration of temperature anomalies accounts for less than 5%: slight impact, the temperature impact coefficient ranges from 0.95 to 1.0; when the duration of temperature anomalies accounts for 5% to 15%: moderate impact, the temperature impact coefficient ranges from 0.85 to 0.95; when the duration of temperature anomalies accounts for more than 15%: severe impact, the coefficient ranges from 0.7 to 0.85, where the duration of temperature anomalies = first duration + second duration.

[0057] Humidity impact assessment matrix: When the percentage of abnormal humidity duration is <8%: slight impact, humidity impact coefficient ranges from 0.95 to 1.0; when the percentage of abnormal humidity duration is 8% to 20%: moderate impact, humidity impact coefficient ranges from 0.85 to 0.95; when the percentage of abnormal humidity duration is >20%: severe impact, humidity impact coefficient ranges from 0.7 to 0.85, where the duration of abnormal humidity = third duration + fourth duration.

[0058] Comprehensive Impact Level Judgment Table: The impact levels of temperature and humidity are combined to form a judgment matrix of 9 situations. For example: Slight temperature + Slight humidity: The comprehensive impact is slight, and the final environmental regulation coefficient ranges from 0.95 to 1.0; Severe temperature + Severe humidity: The comprehensive impact is severe, and the final environmental regulation coefficient ranges from 0.6 to 0.7. The final environmental adjustment coefficient is calculated as follows: First, take the median value of each of the temperature influence coefficient (T) and humidity influence coefficient (H) ranges, and perform a weighted calculation with a temperature weight of 0.6 and a humidity weight of 0.4 to obtain the preliminary weighted value W = T × 0.6 + H × 0.4. Then, introduce an adjustment coefficient K based on the combination of influence levels: when both temperature and humidity have a slight influence, K = 0; when one is slight and the other is moderate, K = 0.02; when one is slight and the other is severe, K = 0.05; when both are moderate, K = 0.05; when one is moderate and the other is severe, K = 0.08; when both are severe, K = 0.1. The final environmental adjustment coefficient E = WK, and the range of values ​​is formed by fluctuating by 0.05 above and below E. For example, when the temperature is slightly elevated (T = 0.975) and the humidity is slightly elevated (H = 0.975), W = 0.975, K = 0, and the final E = 0.975, with a value range of 0.95-1.0; when the temperature is severely elevated (T = 0.775) and the humidity is severely elevated (H = 0.775), W = 0.775, K = 0.1, and the final E = 0.675, with a value range of 0.6-0.7. This calculation method fully considers the degree of influence of a single environmental factor, the weight differences of different factors, and the synergistic effect of multiple adverse environmental factors, ensuring the scientific and rational nature of the environmental regulation coefficient.

[0059] Finally, the environmental adjustment coefficient is arithmetically multiplied by the first remaining usage time obtained in S102 to generate the second remaining usage time. For example, if the first remaining usage time is 72.24 months and the environmental adjustment coefficient is 0.9, then the second remaining usage time is 65.02 months.

[0060] Based on the above embodiments, as an optional implementation, in S103, generating the environmental adjustment coefficient according to the environmental parameters specifically includes S31-S35:

[0061] S31, based on environmental parameters, determine the first duration during which the temperature of the environment where the charging pile is located exceeds the first preset temperature and the second duration during which the temperature is lower than the second preset temperature within the usage time, wherein the first preset temperature is greater than the second preset temperature.

[0062] The system analyzes the temperature of the environment in which the charging pile is located within the usage period based on environmental monitoring data. The first preset temperature is typically set to 40℃, and the second preset temperature is set to -10℃. These two temperature values ​​are critical values ​​determined based on the charging pile's environmental adaptability indicators. The system will calculate the cumulative time the ambient temperature exceeds 40℃ (i.e., the first duration) and the cumulative time the ambient temperature is below -10℃ (i.e., the second duration). For example, within 36 months of use of a certain charging pile, the cumulative time the ambient temperature exceeds 40℃ is 720 hours (first duration), and the cumulative time below -10℃ is 480 hours (second duration).

[0063] S32, determine the temperature influence coefficient of the charging pile based on the sum of the first duration and the second duration.

[0064] The system determines the temperature impact coefficient based on the proportion of the sum of the first and second durations to the total used time. For example, when the total duration of temperature anomalies accounts for less than 5%, the temperature impact coefficient is 0.95-1.0; when it accounts for 5%-15%, the coefficient is 0.85-0.95; and when it accounts for more than 15%, the coefficient is 0.7-0.85. In the example above, the total duration of temperature anomalies is 1200 hours, accounting for approximately 5.5% of the total 36-month duration, and the corresponding temperature impact coefficient might be 0.92.

[0065] S33, based on environmental parameters, determine the duration for which the humidity of the environment where the charging pile is located exceeds the third preset humidity and the duration for which it is lower than the fourth preset humidity within the usage period, where the third preset humidity is greater than the fourth preset humidity.

[0066] The system also needs to analyze the ambient humidity. The third preset humidity is usually set to 85% RH, and the fourth preset humidity is set to 20% RH. These two humidity values ​​are also determined based on the charging pile's environmental adaptability indicators. The system will count the cumulative time when the ambient humidity exceeds 85% RH (i.e., the third duration) and the cumulative time when the ambient humidity is below 20% RH (i.e., the fourth duration). For example, within the same period, the cumulative time when the ambient humidity exceeds 85% RH is 960 hours (the third duration), and the cumulative time when the ambient humidity is below 20% RH is 360 hours (the fourth duration).

[0067] S34. Determine the humidity influence coefficient of the charging pile based on the sum of the third and fourth durations.

[0068] The system determines the humidity impact coefficient based on the combined percentage of the third and fourth time periods. The relationship between the percentage of abnormal humidity duration and the impact coefficient is similar to that of temperature: when the percentage is below 8%, the humidity impact coefficient is 0.95-1.0; when the percentage is between 8% and 20%, it is 0.85-0.95; and when the percentage exceeds 20%, it is 0.7-0.85. In the example above, the total duration of abnormal humidity is 1320 hours, accounting for approximately 6.1%, and the corresponding humidity impact coefficient is likely 0.96.

[0069] S35: Based on the magnitude of the temperature influence coefficient and humidity influence coefficient, determine the level of environmental impact on the charging pile from the preset database, and generate an environmental adjustment coefficient based on the level of impact.

[0070] The system determines the environmental impact level by querying a preset database based on the magnitudes of the temperature and humidity influence coefficients. The database stores environmental impact levels corresponding to different combinations of temperature and humidity influence coefficients. For example, when both coefficients are greater than 0.95, it is classified as a slight impact; when one coefficient is between 0.85 and 0.95, it is classified as a moderate impact; and when either coefficient is less than 0.85, it is classified as a severe impact. Different environmental impact levels correspond to different ranges of environmental adjustment coefficients: slight impact corresponds to 0.95-1.0, moderate impact to 0.85-0.95, and severe impact to 0.7-0.85. In the example above, the temperature influence coefficient is 0.92, and the humidity influence coefficient is 0.96, corresponding to a moderate impact level. The final environmental adjustment coefficient might be 0.90.

[0071] Based on the above embodiments, as an optional implementation method, in S103, adjusting the first remaining usage time according to the environmental adjustment coefficient to generate the second remaining usage time specifically includes: multiplying the environmental adjustment coefficient by the first remaining usage time arithmetically to generate the second remaining usage time.

[0072] S104. Based on the operating data of other charging piles within the usage period, calculate the mutual interference coefficient; other charging piles are those connected to the same distribution transformer as the charging pile.

[0073] In this embodiment, since multiple charging piles are typically connected to the same distribution transformer, the simultaneous operation of these charging piles will generate a superposition effect of power load, causing changes in the operating conditions of each charging pile and thus affecting its service life. To accurately assess this mutual interference, it is necessary to analyze the operating data of other charging piles connected to the same distribution transformer as the target charging pile. The distribution transformer is a device that converts the grid voltage into the operating voltage of the charging pile, and its rated power determines the total charging load it can support simultaneously.

[0074] Specifically, the first step is to obtain the initial charging time of other charging stations within their usage period, and the second charging time of the target charging station within its usage period. Here, charging time refers to the actual time the charging station is charging the electric vehicle. For example, two charging stations, A and B, are connected to a certain power distribution transformer, with A being the target charging station. In the past month, charging station B's cumulative charging time (i.e., the first charging time) was 300 hours, and charging station A's cumulative charging time (i.e., the second charging time) was 250 hours.

[0075] Next, the system will calculate the overlap between the first and second charging times, i.e., the time period during which multiple charging piles charge simultaneously. By analyzing the timestamps in the charging pile operation logs, the duration of this overlap can be accurately calculated. For example, the duration of simultaneous operation (i.e., overlap) of charging piles A and B mentioned above within a month is 150 hours.

[0076] After determining the overlap duration, the system obtains the total charging power of other charging piles within the overlap duration and calculates its ratio to the rated power of the distribution transformer, i.e., the power ratio. The power ratio refers to the proportion of the total charging power of other charging piles within the overlap duration to the rated power of the distribution transformer. The calculation formula is: Power Ratio = Total Charging Power of Other Charging Piles within the Overlap Duration ÷ Rated Power of Distribution Transformer. For example, if the rated power of the distribution transformer is 400kW, and the average charging power of charging pile B within the overlap duration is 240kW, then the power ratio is 0.6. Based on this power ratio, the power occupancy factor is determined. The power occupancy factor reflects the degree to which other charging piles occupy the transformer capacity and directly affects the power supply quality of the target charging pile.

[0077] Finally, the crosstalk coefficient is generated based on the power occupancy factor, and the two are positively correlated. Specifically, it can be determined through the following correspondence: when the power occupancy factor is below 0.3, the crosstalk coefficient ranges from 0.95 to 1.0; when the power occupancy factor is between 0.3 and 0.6, the crosstalk coefficient ranges from 0.85 to 0.95; when the power occupancy factor is above 0.6, the crosstalk coefficient may be 0.7 to 0.85. For example, when the power occupancy factor is 0.6, the corresponding crosstalk coefficient may be 0.85.

[0078] Based on the above embodiments, as an optional implementation, in S104, calculating the mutual interference coefficient according to the operating data specifically includes S41-S44:

[0079] S41, obtain the first charging time of other charging piles within the used time, and the second charging time of the charging piles within the used time.

[0080] The system needs to obtain the first charging duration of other charging piles connected to the same distribution transformer as the target charging pile within the used time period, and the second charging duration of the target charging pile within the same time period. Charging duration refers to the cumulative time that a charging pile actually provides charging services to an electric vehicle. For example, a distribution transformer connects three charging piles A, B, and C, where A is the target charging pile. In the past 36 months, the cumulative charging duration (i.e., the first charging duration) of charging piles B and C are 8000 hours and 7500 hours respectively, and the cumulative charging duration (i.e., the second charging duration) of charging pile A is 7800 hours.

[0081] S42, calculate the overlap duration of the first charging duration and the second charging duration.

[0082] When analyzing the impact of mutual interference, the overlapping operating time of different charging pile combinations needs to be considered: the overlapping operating time of A and B is 5000 hours, the overlapping operating time of A and C is 4800 hours, and the overlapping operating time of A with B and C simultaneously is 3000 hours. Therefore, the total time that charging pile A operates simultaneously with at least one other charging pile is (5000 + 4800 - 3000) = 6800 hours. This means that out of its cumulative charging time of 7800 hours, charging pile A completes 6800 hours while operating simultaneously with other charging piles, accounting for 87.2%.

[0083] S43, obtain the power ratio of the total charging power of other charging piles to the rated power of the distribution transformer within the overlapping time period, and determine the power occupancy factor based on the power ratio.

[0084] The system obtains the total charging power of other charging piles within the overlapping time period and calculates its ratio to the rated power of the distribution transformer, i.e., the power ratio. For example, if the rated power of the distribution transformer is 500kW, and the average total charging power of charging piles B and C within the overlapping time period is 350kW, then the power ratio is 0.7. Based on the magnitude of the power ratio, the system determines the power occupancy factor: when the power ratio is below 0.4, the power occupancy factor is 0.2-0.4; when the power ratio is between 0.4 and 0.7, the power occupancy factor is 0.4-0.7; and when the power ratio is above 0.7, the power occupancy factor is 0.7-0.9. In the above example, a power ratio of 0.7 corresponds to a power occupancy factor of 0.7.

[0085] S44 generates the mutual interference coefficient based on the power occupancy factor, and the power occupancy factor and the mutual interference coefficient are positively correlated.

[0086] The system generates a cross-interference coefficient based on the power occupancy factor, and the two are positively correlated. Specifically, when the power occupancy factor is in the range of 0.2-0.4, the cross-interference coefficient is 0.95-1.0, indicating relatively low cross-interference; when the power occupancy factor is in the range of 0.4-0.7, the cross-interference coefficient is 0.85-0.95, indicating moderate cross-interference; and when the power occupancy factor is in the range of 0.7-0.9, the cross-interference coefficient is 0.7-0.85, indicating significant cross-interference. In the example above, a power occupancy factor of 0.7 might correspond to a cross-interference coefficient of 0.85.

[0087] S105, adjust the second remaining usage time according to the mutual interference coefficient to generate the target remaining usage time.

[0088] In this embodiment, since mutual interference between charging piles can lead to accelerated aging of the equipment, the second remaining usage time needs to be finally adjusted based on the mutual interference coefficient. This adjustment reflects the actual impact of parallel operation of multiple charging piles on the equipment's lifespan and helps to obtain more accurate lifespan prediction results.

[0089] Specifically, the first step is to determine the corresponding attenuation duration based on the mutual interference coefficient. Attenuation duration refers to the lifespan loss caused by mutual interference, and its magnitude corresponds directly to the mutual interference coefficient. By consulting a pre-established attenuation duration lookup table, the attenuation duration corresponding to different mutual interference coefficients can be determined. For example, when the mutual interference coefficient is 0.85, the corresponding annual attenuation duration might be 1.2 months. The lookup table is established based on statistical analysis of a large amount of actual operating data, fully considering the impact of different levels of mutual interference on the lifespan of charging piles.

[0090] In the decay duration comparison table, the relationship between the mutual interference coefficient and the decay duration can be divided into the following ranges: Level 1: When the mutual interference coefficient is between 0.95 and 1.0, it indicates slight mutual interference, with an annual decay duration of 0.5-0.8 months. This usually occurs in scenarios where charging pile utilization is low or peak-shifting usage is effective. Level 2: When the mutual interference coefficient is between 0.85 and 0.95, it indicates moderate mutual interference, with an annual decay duration of 0.8-1.2 months. This is common in daily operations. Level 3: When the mutual interference coefficient is between 0.7 and 0.85, it indicates significant mutual interference, with an annual decay duration of 1.2-2.0 months. This usually occurs in scenarios where charging stations are frequently used and under heavy load. Level 4: When the mutual interference coefficient is between 0.5 and 0.7, it indicates severe mutual interference, with an annual decay duration of 2.0-3.0 months. This may occur in scenarios where distribution transformers operate under high load for extended periods. Level 5: When the mutual interference coefficient is below 0.5, it indicates extremely severe mutual interference, with an annual attenuation period of 3.0-4.0 months. This situation suggests that the charging station may have insufficient design capacity or operational management issues, requiring timely system optimization or expansion.

[0091] In practical applications, to make the calculation of attenuation duration more accurate, a linear interpolation method is used to determine the specific attenuation duration value within each interval. For example, when the mutual interference coefficient is 0.9, it is located at the midpoint of the second-level interval (0.85-0.95), and its corresponding annual attenuation duration can be taken as the midpoint of this interval (0.8-1.2 months), which is 1.0 month. This refined interval division and interpolation calculation method can more accurately reflect the lifespan loss of charging piles under different degrees of mutual interference.

[0092] Meanwhile, considering extreme usage scenarios, when the mutual interference coefficient is close to 0 (e.g., 0-0.1), the system will trigger an alarm mechanism to prompt the operator to conduct emergency checks and handle the situation. In this case, the conventional calculation of the attenuation duration will no longer be performed, but special operation and maintenance measures will be required.

[0093] After determining the attenuation duration, subtract the attenuation duration from the second remaining usage duration obtained in S103 to get the final target remaining usage duration. For example, if the second remaining usage duration is 65.02 months, the mutual interference coefficient is 0.85, the corresponding annual attenuation duration is 1.2 months, and the used duration is 36 months, then the total attenuation duration is 3.6 months (1.2 months / year × 3 years). Therefore, the target remaining usage duration is 61.42 months (65.02 - 3.6).

[0094] Based on the above embodiments, as an optional implementation, in S105, adjusting the second remaining usage time according to the mutual interference coefficient to generate the target remaining usage time specifically includes S51-S52:

[0095] S51, determine the attenuation time of the corresponding mutual interference coefficient.

[0096] The system determines the attenuation duration corresponding to the current mutual interference coefficient by consulting a preset attenuation duration lookup table. The attenuation duration lookup table details the annual attenuation duration for different mutual interference coefficient ranges: when the mutual interference coefficient is between 0.95 and 1.0, the annual attenuation duration is 0.5-0.8 months, indicating a slight mutual interference impact; when the mutual interference coefficient is between 0.85 and 0.95, the annual attenuation duration is 0.8-1.2 months, indicating a moderate mutual interference impact; when the mutual interference coefficient is between 0.7 and 0.85, the annual attenuation duration is 1.2-2.0 months, indicating a significant mutual interference impact; when the mutual interference coefficient is between 0.5 and 0.7, the annual attenuation duration is 2.0-3.0 months, indicating a severe mutual interference impact; and when the mutual interference coefficient is below 0.5, the annual attenuation duration is 3.0-4.0 months, indicating an extremely severe mutual interference impact. For example, when the mutual interference coefficient is 0.85, the annual attenuation duration obtained from the lookup table is 1.2 months. To obtain the total degradation time, the annual degradation time needs to be multiplied by the number of years the charging station has been used. Assuming the charging station has been used for 36 months (3 years), the total degradation time is 3.6 months (1.2 months / year × 3 years).

[0097] S52, subtract the decay time from the second remaining usage time to obtain the target remaining usage time.

[0098] The final target remaining usage time is obtained by subtracting the calculated degradation time from the second remaining usage time. For example, if the second remaining usage time is 65.02 months and the total degradation time is 3.6 months, then the target remaining usage time is 61.42 months (65.02 - 3.6). This final result comprehensively considers the usage intensity of the charging pile, environmental impact, and mutual interference effects, and can accurately reflect the actual remaining lifespan of the charging pile.

[0099] Based on the above method, this application also discloses a full lifecycle monitoring system for charging facilities, such as... Figure 2 As shown, Figure 2 This is a schematic diagram of the structure of a full life-cycle monitoring system for charging facilities provided in an embodiment of this application. The system includes: a determination module, a first adjustment module, a second adjustment module, a calculation module, and a third adjustment module; wherein,

[0100] The system comprises the following modules: a determination module, used to determine the remaining usage time of a charging pile based on its standard service life and the amount of time it has been used; a first adjustment module, used to acquire usage data of the charging pile within its used time, generate a correction coefficient based on the usage data, and adjust the remaining usage time according to the correction coefficient to generate a first remaining usage time; a second adjustment module, used to acquire environmental parameters of the charging pile's environment within its used time, generate an environmental adjustment coefficient based on the environmental parameters, and adjust the first remaining usage time according to the environmental adjustment coefficient to generate a second remaining usage time; a calculation module, used to calculate the mutual interference coefficient based on the operating data of other charging piles within their used time; other charging piles are those connected to the same distribution transformer as the charging pile; and a third adjustment module, used to adjust the second remaining usage time according to the mutual interference coefficient to generate a target remaining usage time.

[0101] It should be noted that the system provided in the above embodiments is only illustrated by the division of the above functional modules. In actual applications, the above functions can be assigned to different functional modules as needed, that is, the internal structure of the device can be divided into different functional modules to complete all or part of the functions described above. In addition, the system and method embodiments provided in the above embodiments belong to the same concept, and the specific implementation process can be found in the method embodiments, which will not be repeated here.

[0102] Please see Figure 3 This is a schematic diagram of the structure of an electronic device provided in an embodiment of this application. Figure 3 As shown, the electronic device 1000 may include: at least one processor 1001, at least one network interface 1004, a user interface 1003, a memory 1005, and at least one communication bus 1002.

[0103] The communication bus 1002 is used to realize the connection and communication between these components.

[0104] The user interface 1003 may include a display screen and a camera. Optionally, the user interface 1003 may also include a standard wired interface and a wireless interface.

[0105] The network interface 1004 may optionally include a standard wired interface or a wireless interface (such as a Wi-Fi interface).

[0106] The processor 1001 may include one or more processing cores. The processor 1001 connects to various parts of the server using various interfaces and lines, and performs various server functions and processes data by running or executing instructions, programs, code sets, or instruction sets stored in the memory 1005, and by calling data stored in the memory 1005. Optionally, the processor 1001 may be implemented using at least one hardware form of Digital Signal Processing (DSP), Field-Programmable Gate Array (FPGA), or Programmable Logic Array (PLA). The processor 1001 may integrate one or a combination of several of the following: Central Processing Unit (CPU), Graphics Processing Unit (GPU), and modem. The CPU primarily handles the operating system, user interface, and applications; the GPU is responsible for rendering and drawing the content required for display; and the modem handles wireless communication. It is understood that the modem may also not be integrated into the processor 1001 and may be implemented as a separate chip.

[0107] The memory 1005 may include random access memory (RAM) or read-only memory. Optionally, the memory 1005 may include a non-transitory computer-readable storage medium. The memory 1005 can be used to store instructions, programs, code, code sets, or instruction sets. The memory 1005 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as touch function, sound playback function, image playback function, etc.), instructions for implementing the above-described method embodiments, etc.; the data storage area may store data involved in the above-described method embodiments, etc. Optionally, the memory 1005 may also be at least one storage device located remotely from the aforementioned processor 1001. Figure 3 As shown, the memory 1005, which serves as a computer storage medium, may include an operating system, a network communication module, a user interface module, and an application program for a method of monitoring the entire lifecycle of a charging facility.

[0108] exist Figure 3In the electronic device 1000 shown, the user interface 1003 is mainly used to provide an input interface for the user and to obtain the user input data; while the processor 1001 can be used to call an application stored in the memory 1005 for a full life cycle monitoring method of a charging facility. When executed by one or more processors, the electronic device performs one or more of the methods described in the above embodiments.

[0109] An electronic device readable storage medium stores instructions that, when executed by one or more processors, cause the electronic device to perform one or more of the methods described in the above embodiments.

[0110] It should be noted that, for the sake of simplicity, the foregoing method embodiments are all described as a series of actions. However, those skilled in the art should understand that this application is not limited to the described order of actions, as some steps may be performed in other orders or simultaneously according to this application. Furthermore, those skilled in the art should also understand that the embodiments described in the specification are preferred embodiments, and the actions and modules involved are not necessarily essential to this application.

[0111] In the above embodiments, the descriptions of each embodiment have different focuses. For parts not described in detail in a certain embodiment, please refer to the relevant descriptions in other embodiments.

[0112] In the several embodiments provided in this application, it should be understood that the disclosed apparatus can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative; for instance, the division of units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the displayed or discussed mutual couplings, direct couplings, or communication connections may be through some service interfaces; indirect couplings or communication connections between devices or units may be electrical or other forms.

[0113] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0114] Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit.

[0115] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage device (CMD). Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a memory and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned memory includes various media capable of storing program code, such as USB flash drives, portable hard drives, magnetic disks, or optical disks.

[0116] The foregoing description is merely an exemplary embodiment of this disclosure and should not be construed as limiting the scope of this disclosure. Any equivalent changes and modifications made in accordance with the teachings of this disclosure shall still fall within the scope of this disclosure. Other embodiments of this disclosure will be readily apparent to those skilled in the art upon consideration of the specification and practice of the disclosure herein. This application is intended to cover any variations, uses, or adaptations of this disclosure that follow the general principles of this disclosure and include common knowledge or customary techniques in the art not described herein. The specification and embodiments are to be considered exemplary only, and the scope and spirit of this disclosure are defined by the claims.

Claims

1. A method for monitoring the entire lifecycle of charging facilities, characterized in that, The method includes: Based on the standard service life of the charging pile, the remaining service life of the charging pile is determined according to the usage time of the charging pile. The usage data of the charging pile within the specified usage time is obtained, and a correction coefficient is generated based on the usage data. The usage data includes the number of charging attempts and the average charging amount per charge. Generating the correction coefficient based on the usage data includes: calculating a first difference between the number of charging attempts and the standard number of charging attempts, and generating a first correction coefficient based on the first difference; calculating a second difference between the average charging amount and the rated charging capacity, and generating a second correction coefficient based on the second difference; and weighted summing the first correction coefficient and the second correction coefficient to generate a correction coefficient. The remaining usage time is adjusted according to the correction coefficient to generate a first remaining usage time; The process involves obtaining environmental parameters of the charging pile's environment within the used time period, and generating an environmental adjustment coefficient based on these parameters. This includes: determining, based on the environmental parameters, the first duration for which the temperature of the environment where the charging pile is located exceeds a first preset temperature, and the second duration for which it is below a second preset temperature, where the first preset temperature is greater than the second preset temperature; determining a temperature influence coefficient for the charging pile based on the sum of the first and second durations; determining, based on the environmental parameters, the third duration for which the humidity of the environment where the charging pile is located exceeds a third preset humidity, and the fourth duration for which it is below a fourth preset humidity, where the third preset humidity is greater than the fourth preset humidity; determining a humidity influence coefficient for the charging pile based on the sum of the third and fourth durations; and determining the environmental influence level of the charging pile from a preset database based on the magnitudes of the temperature and humidity influence coefficients, and generating an environmental adjustment coefficient based on the influence level. Based on the environmental adjustment coefficient, the first remaining usage time is adjusted to generate a second remaining usage time; Based on the operating data of other charging piles within the used time, a mutual interference coefficient is calculated; this includes: obtaining a first charging time of the other charging piles within the used time and a second charging time of the charging pile within the used time; calculating the overlap time of the first charging time and the second charging time, the overlap time including: the time period during which multiple charging piles charge simultaneously; obtaining the power ratio of the total charging power of the other charging piles to the rated power of the distribution transformer within the overlap time, and determining a power occupancy coefficient based on the power ratio; generating a mutual interference coefficient based on the power occupancy coefficient, the power occupancy coefficient being positively correlated with the mutual interference coefficient; the other charging piles being charging piles connected to the same distribution transformer as the charging pile; and adjusting the second remaining usage time based on the mutual interference coefficient to generate a target remaining usage time.

2. The method for monitoring the entire lifecycle of charging facilities according to claim 1, characterized in that, The step of adjusting the remaining usage time according to the correction coefficient to generate a first remaining usage time includes: performing an arithmetic multiplication of the correction coefficient and the remaining usage time to generate a first remaining usage time.

3. The method for monitoring the entire lifecycle of charging facilities according to claim 1, characterized in that, The step of adjusting the first remaining usage time according to the environmental adjustment coefficient to generate a second remaining usage time includes: multiplying the environmental adjustment coefficient by the first remaining usage time arithmetically to generate a second remaining usage time.

4. The method for monitoring the entire lifecycle of charging facilities according to claim 1, characterized in that, The step of adjusting the second remaining usage time according to the mutual interference coefficient to generate a target remaining usage time includes: determining the attenuation time corresponding to the mutual interference coefficient; and subtracting the attenuation time from the second remaining usage time to obtain the target remaining usage time.

5. A full lifecycle monitoring system for charging facilities, characterized in that, The system includes: a determining module, a first adjusting module, a second adjusting module, a calculating module, and a third adjusting module; wherein, the determining module is used to determine the remaining usage time of the charging pile based on its standard service life and the usage time already taken; the first adjusting module is used to acquire usage data of the charging pile within the usage time, and generate a correction coefficient based on the usage data, wherein the usage data includes the number of charging attempts and the average charging amount per charge, and generating the correction coefficient based on the usage data includes: calculating a first difference between the number of charging attempts and the standard number of charging attempts, generating a first correction coefficient based on the first difference; and calculating a second difference between the average charging amount and the rated charging capacity. The value is used to generate a second correction coefficient based on the second difference; the first correction coefficient and the second correction coefficient are weighted and summed to generate a correction coefficient; the remaining usage time is adjusted according to the correction coefficient to generate a first remaining usage time; the second adjustment module is used to obtain environmental parameters of the environment where the charging pile is located within the usage time, and generate an environmental adjustment coefficient according to the environmental parameters, including: determining, according to the environmental parameters, a first duration when the temperature of the environment where the charging pile is located exceeds a first preset temperature and a second duration when it is lower than a second preset temperature within the usage time, wherein the first preset temperature is greater than the second preset temperature; and determining the charging pile's... Temperature influence coefficient; based on the environmental parameters, determine the third duration for which the humidity of the environment where the charging pile is located exceeds a third preset humidity and the fourth duration for which the humidity is lower than a fourth preset humidity within the used time, wherein the third preset humidity is greater than the fourth preset humidity; determine the humidity influence coefficient of the charging pile based on the sum of the third duration and the fourth duration; determine the influence level of the environment on the charging pile from a preset database based on the magnitude of the temperature influence coefficient and the humidity influence coefficient, and generate an environmental adjustment coefficient based on the influence level; adjust the first remaining usage time based on the environmental adjustment coefficient to generate a second remaining usage time; the calculation module is used to determine the influence level of other charging piles within the used time. The system uses operational data to calculate a mutual interference coefficient. This includes: obtaining the first charging duration of the other charging piles within the used time period, and the second charging duration of the charging pile within the used time period; calculating the overlap duration of the first and second charging durations, where the overlap duration includes the time period during which multiple charging piles charge simultaneously; obtaining the power ratio of the total charging power of the other charging piles to the rated power of the distribution transformer within the overlap duration, and determining a power occupancy coefficient based on the power ratio; generating a mutual interference coefficient based on the power occupancy coefficient, where the power occupancy coefficient is positively correlated with the mutual interference coefficient; the other charging piles are those connected to the same distribution transformer as the charging pile.The third adjustment module is used to adjust the second remaining usage time according to the mutual interference coefficient to generate a target remaining usage time.

6. An electronic device, characterized in that, The device includes a processor, a memory, a user interface, and a network interface. The memory is used to store instructions, the user interface and the network interface are used to communicate with other devices, and the processor is used to execute the instructions stored in the memory to cause the electronic device to perform the method as described in any one of claims 1-4.

7. A computer-readable storage medium, characterized in that, The computer program is stored that can be loaded by a processor and executed as described in any one of claims 1-4.

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