A charging pile abnormal state diagnosis method and system based on vehicle-pile data interaction

Abstract

The present invention discloses a charging pile abnormal state diagnosis method and system based on vehicle-pile data interaction, using the charging pile related self data and environmental data as independent variables, and the power loss as the dependent variable to establish a fitting relationship; obtaining the charging pile historical operation data from the relevant charging pile operator unit, and establishing an evaluation system; using the CRITIC weighting method, combined with the dynamic health factor to calculate the overall health status score of the charging pile; rating the charging pile health status according to the overall health status score of the charging pile, and establishing a relationship between the charging pile health status level and the corresponding power error, to obtain the charging pile power error interval of the health evaluation level; comparing the power measurement value in the vehicle-side BMS message, calculating the power measurement error is not within the corresponding interval, and then judging it as an abnormal charging pile. The present invention not only has accurate evaluation results, but also reduces the measurement time.

Description

Technical Field

[0001] The present invention relates to a method and system for diagnosing abnormal charging pile status based on vehicle-pile data interaction, and belongs to the technical field of power equipment monitoring. Background Art

[0002] At present, the number and frequency of use of charging piles are increasing rapidly. The calibration of new energy charging piles and the uncertainty assessment methods and analysis research of their metrological characteristics are imminent. Therefore, more and more metrological scientific research institutions have conducted exploratory research on the metrology of charging piles.

[0003] Chinese patent CN202211467297.3 discloses a remotely monitored DC charging pile metering monitoring system and method proposed by the applicant Jiangsu Institute of Metrology. The device can upload metering data to the cloud to achieve remote data interaction with the metering data center. The large amount of uploaded data can be used as a long-term tracking record of the charging pile, future prediction or research, and it is portable and economical. "Electric Power Automation Equipment", 2022.10, pages 70-76, Liu Wei et al. proposed an AMI data-driven electric vehicle charging facility metering operation error state assessment method. This method analyzes the topological structure of a typical DC charging station, combines the massive charging facility electricity consumption data provided by AMI, and uses big data analysis methods to achieve accurate assessment and abnormal monitoring of the metering operation error state of the operating charging facility. Compared with traditional metering methods, no additional hardware facilities are required, which is easy to promote. In addition, some scholars have conducted research and design from the algorithm level and deep learning level. Modern Electronic Technology, 2024.3.1, pp. 112-117, Chen et al. proposed a DC charging pile online metering error prediction method based on the improved GWO-GM(1,1) model. This method introduced the nonlinear mutation probability k to improve the Grey Wolf Algorithm, and integrated it with the grey theory, applied it to the GM(1,1) model, and iterated multiple times to find the optimal value, which improved the prediction accuracy of the model. Industrial Control Computer, 2024.4.25, pp. 87-88, Yu Qingquan et al. proposed a study on the relative error prediction of DC charging piles based on deep learning algorithms. The study used MAE and MSE as evaluation indicators and found that LightGBM had the best prediction effect compared with N-Linear and CNN models.

[0004] When diagnosing abnormal status of a charging pile, it is generally necessary to measure the operation data of the charging pile. Since a lot of measurement data is required, the measurement time is long and the labor cost is high. Summary of the invention

[0005] Purpose of the invention: In order to reduce data measurement in the process of determining whether the metering error of a charging pile is abnormal, and to reasonably allocate human resources for charging pile maintenance, the present invention provides a charging pile abnormal state diagnosis method based on vehicle-pile data interaction.

[0006] Technical solution: To achieve the above purpose, the technical solution adopted by the present invention is:

[0007] A method for diagnosing abnormal status of charging piles based on vehicle-pile data interaction, firstly, establish a database to obtain the fitting relationship between charging piles with different rated powers and power loss under the influence of factors such as service life and operating environment; then, by analyzing and processing the key power data, working environment data and the number of failures of each major component of the DC charging pile, the power loss of each charging pile is calculated, and a health status evaluation system is established according to various indicator parameters and dynamic health factors, and the health status score of the charging pile at a certain moment is calculated, and the health status is rated according to the score, and an error model is established according to a certain number of health status ratings and power loss, and combined with the power loss data in the established database, the health status level of the charging pile with unknown measured operation data is obtained; finally, the error is judged whether it is abnormal according to the health status level and the vehicle-side BMS data, and specific maintenance arrangements are given. Specifically, the following steps are included:

[0008] Step 1: Collect charging data of DC charging piles under typical working conditions in advance, establish a database, use the charging pile-related data and environmental data as independent variables, and power loss as dependent variable to establish a fitting relationship.

[0009] Step 2: Obtain the historical operation data of the charging pile from the relevant charging pile operator, including the charging pile metering unit record information and working environment data, as well as the number of failures of each major component and the most recent repair time of the failed component. In addition, it is necessary to measure the input power and output power on site and subtract them to obtain the power loss error of the charging pile.

[0010] Step 3, calculate the input current error, input voltage error, and output current error based on the electric energy data calculated according to the information recorded by the charging pile metering unit, and establish an evaluation system based on the service life of the charging gun, the number of charging gun failures, and the number of fan failures.

[0011] Step 4: Based on the evaluation system, use the CRITIC weighting method and the dynamic health factor to calculate the overall health status score of the charging pile.

[0012] Step 5: Rating the health status of the charging pile according to the overall health status score of the charging pile by using the relationship between the health status score of the charging pile and the corresponding level to obtain the health status level of the charging pile.

[0013] Step 6: Establish a relationship between the health status level of the charging pile and the corresponding power error. Take the confidence interval with a confidence level of 95% as the power error interval of the charging pile at the health evaluation level.

[0014] Step 7: Compare the energy measurement value in the vehicle-side BMS message, and if the energy measurement error is not within the corresponding range, it is judged as an abnormal charging pile.

[0015] Preferably, the calculation method of the health status score of the charging pile in step 4 is as follows:

[0016] Step 4.1, perform positive or negative processing on each indicator, and calculate the health index of the indicator at each moment in the group. If the data exceeds the limit value of the indicator, the health index is 0, and if it is exactly equal to the standard value of the indicator, the health index is 1.

[0017] Step 4.2, use the critic weight method to calculate the weight of each indicator.

[0018] Step 4.3, introduce the dynamic health factors of each group, calculate the comprehensive weight, and calculate the overall health status score of the charging pile.

[0019] Preferred: The formula of dynamic health factor is as follows:

[0020] ;

[0021] in, represents the dynamic health factor of k groups of components at time t, For charging piles The health index at all times, To take the charging pile out of the factory or just after maintenance, When the charging pile is scrapped The health index of the component. T is the component life. is the component load correction factor, is the component environment correction factor.

[0022] Optimum: The calculation formula for the overall health status score of the charging pile is:

[0023] ;

[0024] in, Score the overall health status of the charging pile. is the dynamic health factor of k groups of components at time t, is the weight obtained by the critic weight method, is the health index of indicator i at time t, is the specific value of index i at time t.

[0025] Preferably: the fitting relationship in step 1 is:

[0026] ;

[0027] in, is the average power loss of the charging pile, , is the fitting coefficient, They are the rated power of the charging pile, the proportion of the remaining service life of the charging pile, the average temperature of the area where the charging pile operates, and the annual temperature difference in the area where the charging pile operates.

[0028] Preferably, the relationship between the charging pile health status score and the corresponding level is: the charging pile health status score [0,20] is level 4. The charging pile health status score [20,40] is level 3. The charging pile health status score [40,60] is level 2. The charging pile health status score [60,80] is level 1. The charging pile health status score [80,100] is level 0.

[0029] Preferably, the evaluation system structure is established in step 3 as follows:

[0030] The evaluation indicators are divided into four groups. The first group is called charging pile electrical indicators, which include input current error , Input voltage error , output current error , output voltage error , voltage regulation accuracy , steady flow accuracy , Overall efficiency , Charging power factor The second group is called charging gun indicators, which include the average operating temperature of the charging gun , Charging gun service life , Charging gun failure times The third group is called the charging pile working environment indicators, which include the average humidity of the charging pile. , average operating temperature of charging pile The fourth group is called other failure indicators, which include the number of fan failures. , arrester failure times , card reader failure times .

[0031] Preferably, the electric energy error calculation formula in step 6 is as follows:

[0032] ;

[0033] in: is the energy error, For input electrical energy, To output electrical energy.

[0034] Another object of the present invention is to provide a charging pile abnormal state diagnosis system based on vehicle-pile data interaction, which is used to implement the charging pile abnormal state diagnosis method based on vehicle-pile data interaction, including a collection unit, a fitting relationship unit, a charging pile historical data processing unit, an evaluation system unit, a health status scoring unit, a charging pile health status level unit, a charging pile power error interval unit, and an abnormal charging pile judgment unit, wherein:

[0035] The acquisition unit is used to collect charging data of DC charging piles under typical working conditions and establish a database.

[0036] The fitting relationship unit is used to establish a fitting relationship based on the charging pile-related self data and environmental data as independent variables and the power loss as the dependent variable.

[0037] The charging pile historical data processing unit is used to obtain the charging pile historical operation data from the relevant charging pile operator, including the charging pile metering unit record information and working environment data, as well as the number of failures of each major component and the most recent repair time of the failed component. In addition, it is necessary to measure the input power and output power on site, subtract them, and use them as the power loss error of the charging pile.

[0038] The evaluation system unit is used to calculate the input current error, input voltage error, and output current error based on the electric energy data calculated by the charging pile metering unit recording information, and establish an evaluation system in combination with the service life of the charging gun, the number of charging gun failures, and the number of fan failures.

[0039] The health status scoring unit is used to calculate the overall health status score of the charging pile according to the evaluation system, using the CRITIC weighting method and combining the dynamic health factors.

[0040] The charging pile health status grade unit is used to rate the health status of the charging pile according to the overall health status score of the charging pile through the relationship between the charging pile health status score and the corresponding grade, so as to obtain the health status grade of the charging pile.

[0041] The charging pile power error interval unit is used to establish a relationship between the charging pile health status level and the corresponding power error, and take the confidence interval with a confidence level of 95% as the charging pile power error interval of the health evaluation level.

[0042] The abnormal charging pile judgment unit is used to compare the electric energy measurement value in the vehicle-side BMS message, and if the calculated electric energy measurement error is not within the corresponding interval, it is judged as an abnormal charging pile.

[0043] Another object of the present invention is to provide a computer system, comprising a memory and a processor, wherein the memory is used to store a computer program / instruction, and the processor is used to execute the computer program / instruction to implement the charging pile abnormal state diagnosis method based on vehicle-pile data interaction.

[0044] Compared with the prior art, the present invention has the following beneficial effects:

[0045] 1. This method combines the main working data and performance parameters that affect the health status of DC charging piles as evaluation indicators, conducts a comprehensive evaluation, takes into account specific and comprehensive aspects, and the evaluation results are more accurate.

[0046] 2. This method introduces a dynamic health factor and evaluates the health status of charging piles by group. It takes into account the status of the charging piles at the evaluation time and in the previous period of time. It is time-series, specific and comprehensive, and the evaluation results are more accurate.

[0047] 3. This method proposes to carry out sampling inspections of different degrees according to the different states of charging piles, rationalize personnel arrangements, and reduce manual maintenance costs.

[0048] 4. This method establishes a charging pile error database, and can estimate the loss and health status level of the charging pile without measuring the charging pile operation data, saving labor costs and reducing measurement time. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 Establish a process for error model based on charging pile health status evaluation;

[0050] Figure 2 In order to combine BMS message information to judge and repair abnormal charging piles. DETAILED DESCRIPTION

[0051] The present invention is further explained below in conjunction with the accompanying drawings and specific embodiments. It should be understood that these examples are only used to illustrate the present invention and are not used to limit the scope of the present invention. After reading the present invention, various equivalent forms of modifications to the present invention by those skilled in the art all fall within the scope defined by the claims attached to this application.

[0052] A method for diagnosing abnormal errors in electric energy metering of charging piles based on the interaction of vehicle and pile data. The method establishes a charging pile error database by pre-collecting data, and obtains the fitting relationship between the charging pile's own data, environmental data and power loss; establishes a charging pile health status evaluation system by analyzing the existing charging pile operation data; establishes a corresponding relationship between charging piles with unmeasured operation data and health status ratings in combination with the charging pile health status evaluation system; determines whether it is an abnormal charging pile by comparing the health status rating error range and BMS data, and proposes a corresponding maintenance strategy. The specific workflow is as follows: Figure 1 As shown, the following steps are included:

[0053] Step 1: Collect data in advance, establish a database, use the charging pile's own data and environmental data as independent variables, and the power loss as the dependent variable to establish a fitting relationship. The method is as follows:

[0054] The data that needs to be collected and stored in the database in advance are: the rated power of the charging pile, the remaining service life of the charging pile, the average temperature of the charging pile operation area, the annual temperature difference of the charging pile operation area, the average humidity of the charging pile operation area, and the average power loss of the charging pile; the annual temperature difference of the charging pile operation area refers to the difference between the highest monthly average temperature and the lowest monthly average temperature in the charging pile operation area in a year. The data is preprocessed and then stored in the database.

[0055] In another embodiment, the method for establishing the fitting relationship is as follows:

[0056] ;

[0057] ;

[0058] ;

[0059] Depend on:

[0060] ;

[0061] The solution is:

[0062] ;

[0063] Therefore, the fitting relationship is:

[0064] ;

[0065] in: is the fitting coefficient; They are the rated power of the charging pile, the remaining service life of the charging pile, the average temperature of the charging pile operation area, and the annual temperature difference of the charging pile operation area; is the average power loss of the charging pile.

[0066] Step 2: Collect the historical operation data of the charging pile on-site or through relevant units, including the recording information and working environment data of the charging pile metering unit, the number of failures of each major component and the most recent maintenance time of the failed component; in addition, it is necessary to measure the input power and output power, subtract them, and use them as the power loss error of the charging pile.

[0067] The formula for calculating the power loss error is as follows:

[0068] ;

[0069] in is the energy error, For input electrical energy, To output electrical energy.

[0070] Step 3: Calculate some evaluation indicators based on the electric energy data obtained from the information recorded by the charging pile metering unit, and establish an evaluation system in combination with the remaining indicator data.

[0071] The evaluation system structure is as follows:

[0072] The evaluation indicators are divided into four groups. The first group is called charging pile electrical indicators, which include input current error , Input voltage error , output current error , output voltage error , voltage regulation accuracy , steady flow accuracy , Overall efficiency , Charging power factor The second group is called charging gun indicators, which include the average operating temperature of the charging gun , Charging gun service life , Charging gun failure times The third group is called the charging pile working environment indicators, which include the average humidity of the charging pile. , average operating temperature of charging pile The fourth group is called other failure indicators, which include the number of fan failures. , arrester failure times , card reader failure times .

[0073] The calculation formula of relevant electrical indicators is as follows:

[0074] Input / output current error, formula is:

[0075] ;

[0076] Where: is the input / output current fluctuation limit value, It is the standard value of input / output current.

[0077] The input / output voltage error formula is:

[0078] ;

[0079] Where: is the input / output voltage fluctuation limit value, It is the standard value of input / output voltage.

[0080] The voltage / flow accuracy formula is:

[0081] ;

[0082] ;

[0083] Where: is the input / output voltage fluctuation limit value, It is the input / output voltage setting value. is the input / output current fluctuation limit value, It is the input / output current setting value.

[0084] The overall efficiency formula is:

[0085] ;

[0086] Where: is the output power.

[0087] The charging power factor formula is:

[0088] ;

[0089] Where: is the effective power, is reactive power.

[0090] Step 4: According to the evaluation system, use the critic weight method and the dynamic health factor to calculate the health status score of the charging pile at that moment.

[0091] Step 4.1, perform positive or negative processing on each indicator, and calculate the health index of the indicator at each moment in the group. If the data exceeds the limit value of the indicator, the health index is 0, and if it is exactly equal to the standard value of the indicator, the health index is 1.

[0092] The forward formula is: ;

[0093] The negative formula is:

[0094] ;

[0095] in is the value of the i-th indicator at time t, is the maximum value of the i-th index, The minimum value of the i-th indicator, is the processed data value.

[0096] The health index calculation formula is:

[0097] h i ( t ) = { x i ( t ) − x i m i n x i ( t ) ¯ − x i m i n , x i ( t ) ∈ [ x i m i n , x i ( t ) ¯ ] x i m a x − x i ( t ) x i m a x − x i ( t ) ¯ , x i ( t ) ∈ [ x i ( t ) ¯ , x i m a x ] ;

[0098] Where: is the health index of the ith indicator at time t, is the standard value of the i-th indicator at time t.

[0099] Step 4.2, use the critic weight method to calculate the weight of each indicator. The formula used is as follows:

[0100] The contrast strength is measured using the standard deviation, which is calculated as:

[0101] ;

[0102] The conflict calculation formula is:

[0103] ;

[0104] in is the correlation coefficient between indicator i and indicator j.

[0105] Furthermore, the information carrying capacity is: ;

[0106] The final weight of indicator i is: ;

[0107] Step 4.3, introduce the dynamic health factors of each group, calculate the comprehensive weight, and calculate the final overall health status score of the charging pile.

[0108] The formula for the dynamic health factor is as follows:

[0109] ;

[0110] in For charging piles The health index at all times, To take the charging pile out of the factory or just after repair; For charging piles Health index at all times; is the aging coefficient, and the calculation formula is:

[0111] ;

[0112] in is the health index of the charging pile at the time of scrapping; T is the life of the components; is the component load correction factor, is the component environment correction factor.

[0113] The formula of dynamic health factor is as follows:

[0114] ;

[0115] in, represents the dynamic health factor of k groups of components at time t, For charging piles The health index at all times, To take the charging pile out of the factory or just after maintenance, When the charging pile is scrapped The health index of; T is the life of the parts; is the component load correction factor, is the component environment correction factor.

[0116] The calculation formula for the overall health status score of the charging pile is:

[0117] ;

[0118] in is the dynamic health factor of k groups of components at time t, is the weight obtained by the critic weight method. is the health index of indicator i at time t, is the specific value of index i at time t.

[0119] Step 5: Rating the health status of the charging pile according to the final overall health status score of the charging pile.

[0120] Since the final scores of charging piles are all in the range of [0,1], they can be expanded 100 times and transferred to the range of [0,100]. The relationship between the health status score of the charging pile and the corresponding level is shown in Table 1. The health status score of the charging pile [0,20] is level 4; the health status score of the charging pile [20,40] is level 3; the health status score of the charging pile [40,60] is level 2; the health status score of the charging pile [60,80] is level 1; the health status score of the charging pile [80,100] is level 0.

[0121] Table 1 Relationship between charging pile health status score and corresponding level

[0122] Score grade [0,20） 4 [20,40） 3 [40,60） 2 [60,80） 1 [80,100] 0

[0123] Step 6: According to a certain amount of health evaluation level and the corresponding power loss value, establish the relationship between the two. Take the confidence interval with a confidence level of 95% as the charging pile power error interval of the health evaluation level.

[0124] According to the normal distribution of power loss, the mean value and standard deviation are obtained, and the two-sided confidence interval with a confidence level of 95% is calculated as the error range. The relationship model between the health status level of the charging pile and the power loss range is established.

[0125] Step 7: Determine the maintenance method. Figure 2 As shown in the figure, if the health evaluation level of the charging pile is greater than level 0 (excluding level 0), it is marked as a problematic charging pile, and personnel are arranged to conduct on-site inspection and repair; at the same time, if the electric energy measurement value in the vehicle-side BMS message is compared and the calculated electric energy measurement error is not within the corresponding range, it is judged to be an abnormal charging pile, and personnel are also arranged to conduct on-site inspection and repair.

[0126] In another embodiment, five data items are collected, including the rated power of the charging pile, the proportion of remaining service life, the average temperature of the operating area, and the annual temperature difference of the operating area. The charging pile health evaluation level of the charging pile is estimated through a pre-established database. If the level is 1, 25% of the charging piles are selected for manual maintenance; if the level is 2, 50% of the charging piles are selected for manual maintenance; if the level is 3, 75% of the charging piles are selected for maintenance; if the level is 4, all charging piles should be manually inspected.

[0127] In another embodiment, if the BMS message of the car at the time of charging can be obtained, the input power data in the BMS message is extracted and combined with the input power data of the charging pile to obtain the charging pile measurement error. , the formula is as follows:

[0128] ;

[0129] in Input power to the charging pile. It is the input power provided in the vehicle-side BMS message.

[0130] like is positive, and the maximum value of the energy loss interval of the charging pile at this health status level is , the minimum value is ,like Θ ∉ [ e m i n − e m a x − e m i n × 2 % ， e m a x + e m a x − e m i n × 2 % ] , marked as a problematic charging pile, manual maintenance should be arranged; otherwise, the charging pile is normal.

[0131] like If the value is negative, it is immediately marked as a problematic charging pile and manual maintenance should be arranged. After eliminating the fault of the metering module at the pile end, it is determined that electricity theft exists at the vehicle end.

[0132] In another embodiment, a charging pile abnormal state diagnosis system based on vehicle-pile data interaction is provided, which is used to implement the charging pile abnormal state diagnosis method based on vehicle-pile data interaction, including a collection unit, a fitting relationship unit, a charging pile historical data processing unit, an evaluation system unit, a health status scoring unit, a charging pile health status level unit, a charging pile power error interval unit, and an abnormal charging pile judgment unit, wherein:

[0133] The acquisition unit is used to collect charging data of DC charging piles under typical working conditions and establish a database.

[0134] The fitting relationship unit is used to establish a fitting relationship based on the charging pile-related self data and environmental data as independent variables and the power loss as the dependent variable.

[0135] The charging pile historical data processing unit is used to obtain the charging pile historical operation data from the relevant charging pile operator, including the charging pile metering unit record information and working environment data, as well as the number of failures of each major component and the most recent repair time of the failed component. In addition, it is necessary to measure the input power and output power on site, subtract them, and use them as the power loss error of the charging pile.

[0136] The evaluation system unit is used to calculate the input current error, input voltage error, and output current error based on the electric energy data calculated by the charging pile metering unit recording information, and establish an evaluation system in combination with the service life of the charging gun, the number of charging gun failures, and the number of fan failures.

[0137] The health status scoring unit is used to calculate the overall health status score of the charging pile according to the evaluation system, using the CRITIC weighting method and combining the dynamic health factors.

[0138] The charging pile health status grade unit is used to rate the health status of the charging pile according to the overall health status score of the charging pile through the relationship between the charging pile health status score and the corresponding grade, so as to obtain the health status grade of the charging pile.

[0139] The charging pile power error interval unit is used to establish a relationship between the charging pile health status level and the corresponding power error, and take the confidence interval with a confidence level of 95% as the charging pile power error interval of the health evaluation level.

[0140] The abnormal charging pile judgment unit is used to compare the electric energy measurement value in the vehicle-side BMS message, and if the calculated electric energy measurement error is not within the corresponding interval, it is judged as an abnormal charging pile.

[0141] In another embodiment, a computer system is provided, including a memory and a processor, wherein the memory is used to store a computer program / instruction, and the processor is used to execute the computer program / instruction to implement the charging pile abnormal state diagnosis method based on vehicle-pile data interaction.

[0142] In this embodiment, a charging pile health status evaluation system based on dynamic health factors is established. By measuring the rated power, environmental data and operating data of the DC charging pile of new energy vehicles in advance, the fitting relationship between the rated power, ambient temperature, life and electric energy error of the charging pile is calculated. The dynamic health factor is introduced in combination with the CRITIC weight method to evaluate the health of the charging pile, and a charging pile electric energy error database is established. For unknown charging piles, it can be determined whether it is an abnormal charging pile, whether manual inspection is required, and whether there is a possibility of vehicle-side electricity theft based on the environment and data of the charging pile, combined with the BMS message information on the vehicle side. The establishment of the database can estimate the health status evaluation and error of the charging pile, and can adapt to a variety of common working conditions, so as to achieve the effect of quickly finding the problem charging pile without measuring the operating data of the charging pile.

[0143] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A charging pile abnormal state diagnosis method based on vehicle-pile data interaction, characterized in that: The following steps are involved: Step 1: pre-collect the charging data of the DC charging pile under typical working conditions, establish a database, use the charging pile related data and environmental data as independent variables, and the power loss as the dependent variable to establish a fitting relationship; Step 2: Obtain the historical operation data of the charging pile from the relevant charging pile operator, including the charging pile metering unit record information and working environment data, as well as the number of failures of each major component and the most recent repair time of the failed component; In addition, it is necessary to measure the input power and output power on site and subtract them to obtain the power loss error of the charging pile; Step 3, calculate the input current error, input voltage error, and output current error based on the electric energy data calculated from the information recorded by the charging pile metering unit, and establish an evaluation system based on the service life of the charging gun, the number of charging gun failures, and the number of fan failures; The evaluation system structure is established as follows: the evaluation indicators are divided into four groups. The first group is called charging pile electrical indicators, which include input current error , Input voltage error , output current error , output voltage error , voltage regulation accuracy , steady flow accuracy , Overall efficiency , Charging power factor ; The second group is called charging gun indicators, which include the average operating temperature of the charging gun , Charging gun service life , Charging gun failure times The third group is called the charging pile working environment indicators, which include the average humidity of the charging pile. , average operating temperature of charging pile ; The fourth group is called other failure indicators, which include the number of fan failures. , arrester failure times , card reader failure times ; Step 4: Calculate the overall health status score of the charging pile based on the evaluation system using the CRITIC weighting method combined with the dynamic health factor; The calculation method of the health status score of the charging pile is as follows: Step 4.1, perform positive or negative processing on each indicator, and calculate the health index of the indicator at each moment in the group. If the data exceeds the limit value of the indicator, the health index is 0, and if it is exactly equal to the standard value of the indicator, the health index is 1; Step 4.2, use the CRITIC weight method to calculate the weight of each indicator; Step 4.3, introduce the dynamic health factors of each group, calculate the comprehensive weight, and calculate the overall health status score of the charging pile; The formula for the dynamic health factor is as follows: ； in, represents the dynamic health factor of k groups of components at time t, For charging piles The health index at all times, To take the charging pile out of the factory or just after maintenance, When the charging pile is scrapped The health index of; T is the life of the parts; is the component load correction factor, is the component environment correction factor; The calculation formula for the overall health status score of the charging pile is: ； in, Score the overall health status of the charging pile. is the dynamic health factor of k groups of components at time t, is the weight obtained by the CRITIC weight method, is the health index of indicator i at time t, is the specific value of index i at time t; Step 5, rating the health status of the charging pile according to the overall health status score of the charging pile by using the relationship between the health status score of the charging pile and the corresponding level to obtain the health status level of the charging pile; Step 6: Establish a relationship between the health status level of the charging pile and the corresponding power error; take the confidence interval of 95% confidence level as the power error interval of the charging pile of the health evaluation level; Step 7: Compare the energy measurement value in the vehicle-side BMS message, and if the energy measurement error is not within the corresponding range, it is judged as an abnormal charging pile.

2. The charging pile abnormal state diagnosis method based on vehicle-pile data interaction according to claim 1 is characterized by: The fitted relationship in step 1 is: ； in, is the average power loss of the charging pile, , is the fitting coefficient, They are the rated power of the charging pile, the proportion of the remaining service life of the charging pile, the average temperature of the area where the charging pile operates, and the annual temperature difference in the area where the charging pile operates.

3. The charging pile abnormal state diagnosis method based on vehicle-pile data interaction according to claim 2 is characterized by: The relationship between the charging pile health status score and the corresponding level is: the charging pile health status score [0,20] is level 4; the charging pile health status score [20,40] is level 3; the charging pile health status score [40,60] is level 2; the charging pile health status score [60,80] is level 1; the charging pile health status score [80,100] is level 0.

4. The charging pile abnormal state diagnosis method based on vehicle-pile data interaction according to claim 3 is characterized by: The formula for calculating the electric energy error in step 6 is as follows: in: is the energy error, For input electrical energy, To output electrical energy.

5. A charging pile abnormal state diagnosis system based on vehicle-pile data interaction, characterized by: The method for diagnosing abnormal state of a charging pile based on vehicle-pile data interaction according to any one of claims 1 to 4 comprises a collection unit, a fitting relationship unit, a charging pile historical data processing unit, an evaluation system unit, a health status scoring unit, a charging pile health status level unit, a charging pile power error interval unit, and an abnormal charging pile judgment unit, wherein: The acquisition unit is used to collect charging data of DC charging piles under typical working conditions and establish a database; The fitting relationship unit is used to establish a fitting relationship based on the charging pile related self data and environmental data as independent variables and the power loss as the dependent variable; The charging pile historical data processing unit is used to obtain the charging pile historical operation data from the relevant charging pile operator unit, including the charging pile metering unit record information and working environment data, as well as the number of failures of each major component and the most recent repair time of the failed component; in addition, it is also necessary to measure the input power and output power on site, subtract them, and use them as the power loss error of the charging pile; The evaluation system unit is used to calculate the input current error, input voltage error, and output current error based on the electric energy data calculated by the charging pile metering unit recording information, and establish an evaluation system in combination with the service life of the charging gun, the number of charging gun failures, and the number of fan failures; The health status scoring unit is used to calculate the overall health status score of the charging pile according to the evaluation system, using the CRITIC weighting method and combining the dynamic health factors; The charging pile health status grade unit is used to grade the health status of the charging pile according to the overall health status score of the charging pile through the relationship between the health status score of the charging pile and the corresponding grade, so as to obtain the health status grade of the charging pile; The charging pile power error interval unit is used to establish a relationship between the charging pile health status level and the corresponding power error according to the two; taking the confidence interval with a confidence level of 95% as the charging pile power error interval of the health evaluation level; The abnormal charging pile judgment unit is used to compare the electric energy measurement value in the vehicle-side BMS message, and if the calculated electric energy measurement error is not within the corresponding interval, it is judged as an abnormal charging pile.

6. A computer system, characterized in that: It includes a memory and a processor, the memory is used to store computer programs / instructions; the processor is used to execute the computer programs / instructions to implement the charging pile abnormal state diagnosis method based on vehicle-pile data interaction as described in any one of claims 1-4.

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