Intelligent charging pile system with fault judgment function

Abstract

The invention discloses an intelligent charging pile system with a fault judgment function, and relates to the field of fault judgment, and the intelligent charging pile system comprises a standby state analysis module, a charging state analysis module, a charging fault analysis module and a charging fault processing module. The system judges the charging adaptation level of each charging power of each charging pile, analyzes the charging state data, judges whether a fault exists or not, calls a charging fault analysis module to carry out detailed diagnosis if the fault is found, and finally analyzes the state data of each part of the target charging device. According to the method, the fault type of the target charging device is judged, so that a corresponding fault processing scheme is adopted, the fault of the charging pile can be found and processed in time, the safe operation efficiency of the charging facility can be effectively improved, and the problems of energy waste and environmental pollution caused by the fault are reduced.

Description

Technical Field

[0001] The present invention relates to the field of fault diagnosis, and in particular to an intelligent charging pile system with fault diagnosis capability. Background Art

[0002] As the number of electric vehicles is growing rapidly and the demand for charging becomes increasingly significant, efficiently, safely, and reliably meeting the charging needs of electric vehicles has become a critical task that needs to be solved urgently. Maintaining the normal operation of equipment through manual inspections will consume a lot of time and manpower. Therefore, there is a need for an intelligent charging pile system that can achieve real-time monitoring of the status of charging facilities, automatic diagnosis and processing of faults, and intelligent optimization management.

[0003] Prior art, such as the invention patent application with announcement number CN112937352A, discloses an artificial intelligence-based centralized charging station power supply system operation monitoring and management system, which includes a charging station charging pile statistical marking module, a charging pile charging display parameter acquisition module, a charging pile automatic power-off detection module, a charging pile charging environment parameter acquisition module, a power supply database, a charging pile charging efficiency statistics module, a parameter processing and analysis module, a management cloud platform and an online display terminal. The present invention performs a normal charging display data detection on each charging pile in the charging station, and screens out charging piles that display faults and charging piles that display normal. Then, charging display parameter acquisition, charging environment parameter acquisition and charging efficiency statistics are performed on the charging piles that display normal, so as to statistically calculate the comprehensive charging quality coefficient corresponding to the charging piles that display normal, thereby greatly expanding the range of operation monitoring indicators of the charging station power supply system, improving the reliability of the monitoring results, and effectively improving the monitoring and management level.

[0004] The above scheme has at least the following shortcomings: the above scheme focuses on judging whether there is a fault in the charging pile in the standby and charging states and issuing early warning prompts, but when the early warning terminal issues a fault prompt, there is no corresponding response strategy suggestion, and the system does not give any guiding opinions. As a result, after receiving the fault prompt, the system is still unable to take specific measures to solve the fault and cannot perform fault repairs in time. It only issues an early warning and cannot guarantee the customer's charging needs, which increases the customer's charging time and reduces customer satisfaction. At the same time, it can only rely on manual experience to provide inspection and maintenance assistance, which increases the time and labor costs of fault resolution. Summary of the Invention

[0005] In view of the above-mentioned technical deficiencies, the purpose of the present invention is to provide an intelligent charging pile system with fault diagnosis.

[0006] In order to solve the above technical problems, the present invention adopts the following technical solutions: The present invention provides an intelligent charging pile system with fault judgment, including the following modules: a standby state analysis module, which is used to collect the standby state data and historical usage data of each charging pile in the charging station, analyze the standby state data and historical usage data of each charging pile in the charging station, obtain the standard state data of each charging pile in the charging station, and then use the standby charging model to determine the charging adaptation level of each charging power of each charging pile.

[0007] The charging status analysis module is used to set the charging mode of the target charging device based on the standard status data of the target charging pile and the historical charging records of the target vehicle in the database. When the target charging device is charging, the charging status data of the target charging pile is collected. Based on the charging fault judgment model, the charging status data of the target charging pile is analyzed to determine whether a fault occurs. When a fault occurs, the charging fault analysis module is used.

[0008] The charging fault analysis module is used to collect status data of each component of the target charging device, analyze the status data of each component of the target charging device, obtain fault data of each component of the target charging device, and then determine the fault type of the target charging device based on the local fault judgment model.

[0009] The charging fault processing module is used to set a fault processing plan according to the fault type of the target charging device.

[0010] Preferably, the status data of each component of the target charging device is analyzed, and the specific analysis process is as follows: the status data of each component of the target charging device includes the power fluctuation rate, power mutation curvature and the number of power mutation points of each component of the target charging device, and the status data of each component of the target charging device including the power fluctuation rate, power mutation curvature and the number of power mutation points of each component of the target charging device are input into the local fault judgment model to obtain the output results of each component of the target charging device, and the values ​​of the output results include 0 and 1.

[0011] If the output result of a component of the target charging device is 0, it indicates that the component is normal. If the output result of a component of the target charging device is 1, it indicates that the component of the target charging device has a fault. The component is recorded as a faulty component, and the faulty components of the target charging device are obtained. A three-dimensional model of the target charging device is established to obtain the coordinates of the faulty components of the target charging device. The coordinates of the faulty components of the target charging device are vectorized to obtain a vector set of target charging device faults. The vector set of target charging device faults is respectively calculated for similarity with the vector set of charging pile faults, the vector set of charging gun faults, and the vector set of charging port faults in the database to obtain the target charging device charging pile fault similarity, charging gun fault similarity, and charging port fault similarity. The fault type with the highest similarity is selected as the fault type of the target charging device.

[0012] Preferably, the fault handling plan is set up, and the specific setting process is as follows: if the fault type is a charging pile fault, the power collected by the target charging device each time is obtained from the database, and the power that appears the most times is recorded as the target usage power of the target charging device, and the charging adaptation level of the target usage power of each unused charging pile is obtained from the charging adaptation level of each charging power of each unused charging pile, and the unused charging piles with the highest charging adaptation level of the target usage power are selected as the charging piles to be replaced, and the target vehicle is moved to the charging pile to be replaced for charging, and the staff is prompted to repair the target charging pile.

[0013] If the fault type is a charging gun failure, the target charging gun is unplugged by the robot, the camera is used to capture the image of the charging gun plug, the stain point is obtained through image recognition technology, and the robot is used to clean it. After cleaning, it is reinserted into the target vehicle. If the stain point cannot be obtained through image recognition technology, or the charging still fails when it is reinserted into the target vehicle after cleaning, it indicates that there is an electrical failure in the charging gun and it is replaced by the robot.

[0014] If the fault type is a charging port failure, charging will be stopped and the user will be prompted to perform repairs.

[0015] The beneficial effects of the present invention are: 1. The present invention determines the charging adaptation level of each charging power of each charging pile by analyzing the standby status data and historical usage data of each charging pile in the charging station, and then analyzes its charging status data to determine whether there is a fault. If a fault is found, the charging fault analysis module will be called for detailed diagnosis. Finally, the system will also analyze the status data of each component of the target charging device to determine the fault type of the target charging device, so as to adopt corresponding fault handling solutions, which can timely discover and handle charging pile faults, effectively improve the safe operation efficiency of charging facilities, and reduce energy waste and environmental pollution caused by faults.

[0016] 2. The present invention analyzes the fault in detail at the component level, which helps to accurately locate the specific location where the fault occurs, rather than just staying at the level of whether the entire charging device is faulty. It provides more accurate information for subsequent fault handling. By setting up fault handling plans for different parts, while improving the speed of fault handling, it can also reduce the errors and safety risks that may be caused by manual operation, improve the efficiency and reliability of the entire fault handling process, enable timely fault handling, reduce the increased charging time of the car due to charging failure, ensure customer needs, and improve customer satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the following briefly introduces the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0018] Figure 1 This is a schematic diagram of the system module connection of the present invention. DETAILED DESCRIPTION

[0019] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making creative efforts are within the scope of protection of the present invention.

[0020] according to Figure 1 As shown, the present invention provides an intelligent charging pile system with fault judgment, including the following modules: a standby state analysis module, a charging state analysis module, a charging fault analysis module, a charging fault processing module and a database.

[0021] The charging state analysis module is connected to the standby state analysis module, the charging fault analysis module and the database respectively, and the charging fault processing module is connected to the charging fault analysis module.

[0022] The standby state analysis module is used to collect the standby state data and historical usage data of each charging pile in the charging station, analyze the standby state data and historical usage data of each charging pile in the charging station, obtain the standard state data of each charging pile in the charging station, and then use the standby charging model to determine the charging adaptation level of each charging power of each charging pile.

[0023] In a specific embodiment, the standby status data and historical usage data of each charging pile in the charging station are collected, and the specific collection process is as follows: the standby status data of each charging pile in the charging station includes the average standby temperature, standby temperature fluctuation index, average standby time and standby time fluctuation index of each charging pile. The standby temperature collected each time of each charging pile is collected by a temperature sensor, and the average standby temperature of each charging pile is calculated by the average value. The standby temperature fluctuation index of each charging pile is calculated by the fluctuation rate. The video of each charging pile is collected by a camera, and the standby time of each charging pile is obtained from the video of each charging pile by machine vision. The average standby time of each charging pile is calculated by the average value, and the standby time fluctuation index of each charging pile is calculated by the fluctuation rate.

[0024] The historical usage data of each charging pile at the charging station includes the interruption rate of each charging power of each charging pile, the maximum number of single interruptions, the charging fluctuation rate and the charging fluctuation index. The charging power of the charging piles during charging is collected by sensors, and the number of occurrences of each power for each charging of each charging pile is counted. The power with the highest number of occurrences is recorded as the charging power for each charging, thereby obtaining the power of each charging power for each charging pile for each charging. When the charging power is less than a preset value, it indicates that charging is interrupted. The number of interruptions for each charging power of each charging pile is counted, the maximum number of single interruptions and the total number of interruptions for each charging power of each charging pile are counted, and the total number of interruptions for each charging power of each charging pile is divided by the total number of collections to obtain the interruption rate of each charging power of each charging pile. At the same time, the fluctuation rate of each power for each charging power of each charging pile is calculated to obtain the fluctuation rate of each charging power of each charging pile for each charging. The average value is calculated to obtain the charging fluctuation rate of each charging power of each charging pile, and the fluctuation rate is calculated to obtain the charging fluctuation index of each charging power of each charging pile.

[0025] It should be noted that the volatility calculation process is the difference between the average value and the minimum value, divided by the difference between the maximum value and the minimum value. For example, the standby temperature fluctuation index calculation formula is: the difference between the average and the lowest standby temperature of each charging pile, divided by the difference between the highest standby temperature and the lowest standby temperature. For example, the volatility of each charge is calculated as: the difference between the average power and the minimum power of each charging power of each charging pile, divided by the difference between the corresponding maximum power and minimum power.

[0026] In a specific embodiment, the standby state data and historical usage data of each charging pile of the charging station are analyzed. The specific analysis process is as follows: the standby average temperature, standby temperature fluctuation index, standby average time and standby time fluctuation index of each charging pile are input into the standby stability index calculation formula The standby stability index E″ of the charging pile No. a is obtained ab , a is the number of each charging pile, the value of a is a positive integer, T′ a , T″ a , R′ a and R″ a are the average standby temperature, standby temperature fluctuation index, average standby time and standby time fluctuation index of charging pile No. a, respectively. T′, T″, R′ and R″ are the preset standard standby temperature, standard standby temperature fluctuation index, standard standby time and standard standby time fluctuation index, respectively. σ1 and σ2 are the weight factors of standby temperature and standby time, respectively. σ1>0, σ2>0, σ1+σ2=1.

[0027] It should be noted that the standard parameter T′ is the threshold value of the normal standby temperature of the charging pile. When the average standby temperature of a charging pile is greater than T′, it indicates that the charging pile is overheated during standby, and the safety hazard is high and needs maintenance. It is set by the staff. For example, T′ is 39. The setting process of the standard parameters T″, R′ and R″ is the same as the setting process of the standard parameter T′. For example, T″ is 0.32, R′ is 0.36 and R″ is 0.72. The setting process of the weight factors σ1 and σ2 is related to the utilization rate of the charging pile. The higher the utilization rate of the charging pile, the larger σ2, and the smaller the utilization rate of the charging pile, the larger σ1. The specific values ​​are set by the staff.

[0028] Input the interruption rate, maximum number of single interruptions, charging fluctuation rate and charging fluctuation index of each charging pile into the charging quality index calculation formula The quality index E′ of the b-type charging power of the a-th charging pile is obtained ab， b is the number of each type of charging power, and the value of b is a positive integer. ab , P″ ab , Q′ ab and Q″ ab are the interruption rate, maximum number of single interruptions, charging volatility and charging volatility index of the b-type charging power of charging pile No. a, respectively. P′, P″, Q′ and Q″ are the preset standard interruption rate, standard maximum number of single interruptions, standard charging volatility and standard charging volatility index, respectively. θ1 and θ2 are the weight factors of the number of interruptions and the weight factor of the charging volatility, respectively. θ1>0, θ2>0, θ1+θ2=1. The standby stability index of each charging pile and the quality index of each charging power are recorded as standard state data.

[0029] It should be noted that the setting process of the standard parameters P′, P″, Q′ and Q″ is the same as the setting process of the standard parameter T′, for example, P′ is 5, P″ is 6, Q′ is 0.65 and Q″ is 0.72, and the setting process of the weight factors θ1 and θ2 is the same as the setting process of the weight factor σ1, for example, θ1 is 0.3 and θ2 is 0.7.

[0030] In a specific embodiment, the charging adaptability level of each charging power of each charging pile is determined, and the specific determination process is as follows: if the quality index of a certain charging power of a certain charging pile is greater than a preset charging power index, it indicates that the charging power of the charging pile is an effective charging power, thereby obtaining the effective charging power of each charging pile.

[0031] At the same time, the difference of the quality indexes corresponding to the adjacent charging powers of each charging pile is calculated to obtain the quality index fluctuation of each charging pile. The difference between the maximum quality index fluctuation of each charging pile and the minimum quality index fluctuation is divided by the sum of the maximum quality index fluctuation and the minimum quality index fluctuation to obtain the quality fluctuation index of each charging pile. The quality fluctuation index of each charging pile is averaged to obtain the quality fluctuation index of the charging station. The interval range corresponding to the quality fluctuation index of the charging station in the database is recorded as the associated interval range. The effective charging powers within the associated interval range of each charging power of each charging pile are summarized to obtain the associated effective charging powers of each charging power of each charging pile.

[0032] The standby stability index of each charging pile and the quality index of each associated effective charging power of each charging power are input into the standby charging model to obtain the output results of each charging power of each charging pile. The output value r is the charging adaptation level, r=1, 2...u, u>2, and u is the maximum charging adaptation level.

[0033] In a specific embodiment, the standby charging model expression is:

[0034]

[0035] Among them, A ab is the output result of the b-type charging power of the charging pile No. a, e is a natural constant, E′ abc is the quality index of the cth category associated effective charging power of the bth category charging power of the charging pile No. a, c is the number of each category of associated effective charging power, the value of c is a positive integer, E′ and E″ are the preset standard quality index and standard standby stability index respectively, ε1 and ε2 are the preset weight factors of the quality index and the standby stability index respectively, ε1>0, ε2>0, ε1+ε2=1, N1, N r-1 、N r and N u-1 They are respectively the preset first charging adaptation index, r-1th charging adaptation index, rth charging adaptation index and u-1th charging adaptation index.

[0036] It should be noted that the standard parameters E′ and E″ are the quality index threshold and standby stability index threshold of a normal charging pile, respectively. When the quality index of a charging pile is less than the quality index threshold, it indicates that the quality of the charging pile is too low and requires maintenance and repair. When the standby stability index of a charging pile is less than the standby stability index threshold, it indicates that the use effect of the charging pile is poor and the charging pile needs to be inspected regularly. The specific values ​​are set by the staff. The weight factors ε1 and ε2 are related to the demand for charging piles. The higher the demand for charging piles, the larger ε1, and the lower the demand for charging piles, the larger ε2. The specific values ​​of ε1 and ε2 are set by the staff.

[0037] The charging status analysis module is used to set the charging mode of the target charging device based on the standard status data of the target charging pile and the historical charging records of the target vehicle in the database. When the target charging device is charging, the charging status data of the target charging pile is collected. Based on the charging fault judgment model, the charging status data of the target charging pile is analyzed to determine whether a fault occurs. When a fault occurs, the charging fault analysis module is used.

[0038] It should be noted that the target charging device includes a target vehicle, a target charging pile and a target charging gun.

[0039] In a specific embodiment, the charging mode of the target charging device is set as follows: the historical charging record of the target vehicle is the charging time of each historical power of the target vehicle, the historical power with the longest charging time is selected as the target power of the target vehicle, and then the charging adaptation level of each charging power within the associated interval of the target power of the target vehicle is obtained, and the charging power with the highest charging adaptation level is selected as the charging power of the target vehicle, so as to set the charging mode of the target charging device.

[0040] In a specific embodiment, the charging status data of the target charging pile is collected, and the specific collection process is as follows: the charging status data of the target charging pile includes the charging temperature fluctuation index, charging current fluctuation index, charging voltage fluctuation index and power sudden change number of the target charging pile, and the charging temperature, charging current and charging voltage collected at each time of the target charging pile are collected by temperature sensors, current sensors and voltage sensors, and the charging temperature fluctuation index, charging current fluctuation index and charging voltage fluctuation index of the target charging pile are obtained by fluctuation rate calculation, and the power collected at each time is obtained by power calculation formula. If the power difference between two adjacent collections is greater than the preset power difference, it indicates that a power sudden change occurs in the two adjacent collections, which is recorded as one power sudden change number, and the power sudden change number of the target charging pile is obtained by statistics.

[0041] It should be noted that the preset power difference is set by the staff and is the power difference threshold for normal power fluctuations. When the power difference exceeds the preset power difference, it indicates that the power fluctuation is abnormal.

[0042] In a specific embodiment, the charging status data of the target charging pile is analyzed, and the specific analysis process is as follows: the charging temperature fluctuation index, charging current fluctuation index, charging voltage fluctuation index and number of power sudden changes of the target charging pile are input into the charging fault judgment model to obtain the output result, and the output result value includes 0 and 1.

[0043] If the output result is 1, it indicates that the target charging pile is faulty.

[0044] In a specific embodiment, the charging fault judgment model expression is:

[0045]

[0046] Wherein, β is the output result, G, F, H and f are the charging temperature fluctuation index, charging current fluctuation index, charging voltage fluctuation index and number of power sudden changes of the target charging pile, respectively; G′, F′, H′ and f′ are the preset standard charging temperature fluctuation index, standard charging current fluctuation index, standard charging voltage fluctuation index and standard number of power sudden changes, respectively; φ1, φ2, φ3 and φ4 are the preset weight factors of the charging temperature fluctuation index, charging current fluctuation index, charging voltage fluctuation index and power sudden change number, respectively; φ1>0, φ2>0, φ3>0, φ4>0, φ1+φ2+φ3+φ4=1, and M is the preset standard charging fault assessment index.

[0047] It should be noted that the setting process of the standard parameters G′, F′, H′, f′ and M is the same as that of the standard parameter E′, for example, G′ is 0.32, F′ is 0.43, H′ is 0.57, f′ is 0.26 and M is 0.71. The setting process of the weight factors φ1, φ2, φ3 and φ4 is the same as that of the weight factor ε1, for example, φ1 is 0.2, φ2 is 0.25, φ3 is 0.25 and φ4 is 0.2.

[0048] The charging fault analysis module is used to collect status data of each component of the target charging device, analyze the status data of each component of the target charging device, obtain fault data of each component of the target charging device, and then determine the fault type of the target charging device based on the local fault judgment model.

[0049] In a specific embodiment, the state data of each component of the target charging device is collected, and the specific collection process is as follows: the state data of each component of the target charging device includes the power fluctuation rate, power mutation curvature and the number of power mutation points of each component of the target charging device, the power of each component of the target charging device at each time point is collected by a sensor, the power of each component of the target charging device at each time point is converted, and a power change curve graph over time is established, and the curvature of each power mutation point of each component of the target charging device is obtained from the image through image recognition technology, and the number of power mutation points of each component of the target charging device is obtained by statistics, the power fluctuation rate of each component of the target charging device is obtained by fluctuation calculation, and the power mutation curvature of each component of the target charging device is obtained by average value calculation.

[0050] In a specific embodiment, the status data of each component of the target charging device is analyzed, and the specific analysis process is as follows: the status data of each component of the target charging device, including the power fluctuation rate, power mutation curvature and the number of power mutation points of each component of the target charging device, are input into the part fault judgment model to obtain the output results of each component of the target charging device, and the output results have numerical values ​​including 0 and 1.

[0051] If the output result of a component of the target charging device is 0, it indicates that the component is normal. If the output result of a component of the target charging device is 1, it indicates that the component of the target charging device has a fault. The component is recorded as a faulty component, and the faulty components of the target charging device are obtained. A three-dimensional model of the target charging device is established to obtain the coordinates of the faulty components of the target charging device. The coordinates of the faulty components of the target charging device are vectorized to obtain a vector set of target charging device faults. The vector set of target charging device faults is respectively calculated for similarity with the vector set of charging pile faults, the vector set of charging gun faults, and the vector set of charging port faults in the database to obtain the target charging device charging pile fault similarity, charging gun fault similarity, and charging port fault similarity. The fault type with the highest similarity is selected as the fault type of the target charging device.

[0052] In a specific embodiment, the position fault judgment model expression is: Among them, γ d is the output result of the dth component of the target charging device, d is the number of each component, and the value of d is a positive integer. d , K d and t dare the power fluctuation rate, power mutation curvature and number of power mutation points of component No. d, respectively; L′, K′ and t′ are the preset standard power fluctuation rate, standard power mutation curvature and number of standard power mutation points, respectively; η1 and η2 are the preset weight factors of power mutation curvature and power fluctuation rate, respectively; η1>0, η2>0, η1+η2=1, and D is the preset standard.

[0053] It should be noted that the setting process of the standard parameters L′, K′, t′ and D is the same as the setting process of the standard parameter E′, for example, L′ is 0.65, K′ is 0.93, t′ is 0.82 and D is 0.63, and the setting process of the weight factors η1 and η2 is the same as the setting process of the weight factor ε1, for example, η1 is 0.4 and η2 is 0.6.

[0054] The charging fault processing module is used to set a fault processing plan according to the fault type of the target charging device.

[0055] In a specific embodiment, the fault handling plan is set up, and the specific setting process is as follows: if the fault type is a charging pile fault, the power collected by the target charging device each time is obtained from the database, and the power that appears the most times is recorded as the target usage power of the target charging device, and the charging adaptation level of the target usage power of each unused charging pile is obtained from the charging adaptation level of each charging power of each unused charging pile, and the unused charging piles with the highest charging adaptation level of the target usage power are selected as the charging piles to be replaced, and the target vehicle is moved to the charging pile to be replaced for charging, and the staff is prompted to repair the target charging pile.

[0056] If the fault type is a charging gun failure, the target charging gun is unplugged by the robot, the camera is used to capture the image of the charging gun plug, the stain point is obtained through image recognition technology, and the robot is used to clean it. After cleaning, it is reinserted into the target vehicle. If the stain point cannot be obtained through image recognition technology, or the charging still fails when it is reinserted into the target vehicle after cleaning, it indicates that there is an electrical failure in the charging gun and it is replaced by the robot.

[0057] If the fault type is a charging port failure, charging will be stopped and the user will be prompted to perform repairs.

[0058] It should be noted that the target vehicle is moved through a mobile platform. When the vehicle moves, a movement request notification is sent to the customer. If the customer agrees to move, the target vehicle is moved. After the move, the target vehicle location is sent to the customer. If the customer does not agree to move, only the power supply is stopped.

[0059] The database is used to store the historical charging records of each vehicle, the interval range corresponding to the quality fluctuation index of each charging station, the vector set of charging pile failures, the vector set of charging gun failures, the vector set of charging port failures, and the power collected by each charging device.

[0060] The above content is merely an example and explanation of the concept of the present invention. Those skilled in the art may make various modifications or additions to the described specific embodiments or replace them in a similar manner. As long as they do not deviate from the concept of the invention or exceed the scope defined in this specification, they should all fall within the scope of protection of the present invention.

Claims

1. An intelligent charging pile system with fault diagnosis, characterized in that: Includes the following modules: The standby state analysis module is used to collect the standby state data and historical usage data of each charging pile at the charging station, analyze the standby state data and historical usage data of each charging pile at the charging station, obtain the standard state data of each charging pile at the charging station, and then use the standby charging model to determine the charging adaptation level of each charging power of each charging pile; The charging status analysis module is used to set the charging mode of the target charging device based on the standard status data of the target charging pile and the historical charging records of the target vehicle in the database. When the target charging device is charging, the charging status data of the target charging pile is collected and analyzed based on the charging fault judgment model to determine whether a fault has occurred. If a fault occurs, the charging fault analysis module is used; A charging fault analysis module is used to collect status data of various components of the target charging device, analyze the status data of various components of the target charging device, obtain fault data of various components of the target charging device, and then determine the fault type of the target charging device based on the local fault judgment model; The charging fault processing module is used to set a fault processing plan according to the fault type of the target charging device.

2. The intelligent charging pile system with fault diagnosis according to claim 1, characterized in that: The standby state data and historical usage data of each charging pile at the charging station are analyzed. The specific analysis process is as follows: The standby status data of each charging pile at the charging station include the average standby temperature, standby temperature fluctuation index, average standby time and standby time fluctuation index of each charging pile. The average standby temperature, standby temperature fluctuation index, average standby time and standby time fluctuation index of each charging pile are input into the standby stability index calculation formula to obtain the standby stability index of each charging pile. The historical usage data of each charging pile at the charging station include the interruption rate of each charging power of each charging pile, the maximum number of single interruptions, the charging fluctuation rate and the charging fluctuation index. The interruption rate, the maximum number of single interruptions, the charging fluctuation rate and the charging fluctuation index of each charging power of each charging pile are input into the charging quality index calculation formula to obtain the quality index of each charging power of each charging pile. The standby stability index of each charging pile and the quality index of each charging power are recorded as standard status data.

3. The intelligent charging pile system with fault diagnosis according to claim 2, characterized in that: The specific judgment process of judging the charging adaptability level of each charging power of each charging pile is as follows: If the quality index of a certain charging power of a charging pile is greater than the preset charging power index, it indicates that the charging power of the charging pile is the effective charging power, thereby obtaining the effective charging power of each charging pile; At the same time, the quality indexes corresponding to the adjacent charging powers of each charging pile are calculated by difference calculation to obtain the fluctuation amount of each quality index of each charging pile. The difference between the maximum quality index fluctuation amount and the minimum quality index fluctuation amount of each charging pile is divided by the sum of the maximum quality index fluctuation amount and the minimum quality index fluctuation amount to obtain the quality fluctuation index of each charging pile. The quality fluctuation index of each charging pile is averaged to obtain the quality fluctuation index of the charging station. The interval range corresponding to the quality fluctuation index of the charging station in the database is recorded as the associated interval range. The effective charging powers within the associated interval range of each charging power of each charging pile are summarized to obtain the associated effective charging powers of each charging power of each charging pile. The standby stability index of each charging pile and the quality index of each associated effective charging power of each charging power are input into the standby charging model to obtain the output results of each charging power of each charging pile. The output value r is the charging adaptation level, r=1, 2...u, u>2, and u is the maximum charging adaptation level.

4. The intelligent charging pile system with fault diagnosis according to claim 3, characterized in that: The standby charging model expression is: Among them, A ab is the output result of the b-th type of charging power of the a-th charging pile, a is the number of each charging pile, the value of a is a positive integer, b is the number of each type of charging power, the value of b is a positive integer, e is a natural constant, E′ abc is the quality index of the cth type of associated effective charging power of the bth type of charging power of the ath charging pile, c is the number of each type of associated effective charging power, and the value of c is a positive integer. E′ a ′ is the standby stability index of the charging pile No. a, E′ and E″ are the preset standard quality index and standard standby stability index respectively, ε1 and ε2 are the preset weight factors of the quality index and the standby stability index respectively, ε1>0, ε2>0, ε1+ε2=1, N1, N r-1 、N r and N u-1 They are respectively the preset first charging adaptation index, r-1th charging adaptation index, rth charging adaptation index and u-1th charging adaptation index.

5. The intelligent charging pile system with fault diagnosis according to claim 3, characterized in that: The charging status data of the target charging pile is analyzed, and the specific analysis process is as follows: The charging status data of the target charging pile includes a charging temperature fluctuation index, a charging current fluctuation index, a charging voltage fluctuation index, and a number of power sudden changes of the target charging pile. The charging temperature fluctuation index, the charging current fluctuation index, the charging voltage fluctuation index, and the number of power sudden changes of the target charging pile are input into the charging fault judgment model to obtain an output result. The output result has a value of 0 or 1. If the output result is 1, it indicates that the target charging pile is faulty.

6. The intelligent charging pile system with fault diagnosis according to claim 5, characterized in that: The charging fault judgment model expression is: Wherein, β is the output result, G, F, H and f are the charging temperature fluctuation index, charging current fluctuation index, charging voltage fluctuation index and number of power sudden changes of the target charging pile, respectively; G′, F′, H′ and f′ are the preset standard charging temperature fluctuation index, standard charging current fluctuation index, standard charging voltage fluctuation index and standard number of power sudden changes, respectively; φ1, φ2, φ3 and φ4 are the preset weight factors of the charging temperature fluctuation index, charging current fluctuation index, charging voltage fluctuation index and power sudden change number, respectively; φ1>0, φ2>0, φ3>0, φ4>0, φ1+φ2+φ3+φ4=1, and M is the preset standard charging fault assessment index.

7. The intelligent charging pile system with fault diagnosis according to claim 1, characterized in that: The state data of each component of the target charging device is analyzed, and the specific analysis process is as follows: The status data of each component of the target charging device includes a power fluctuation rate, a power mutation curvature, and a number of power mutation points of each component of the target charging device. The status data of each component of the target charging device, including the power fluctuation rate, power mutation curvature, and the number of power mutation points of each component of the target charging device, are input into the part fault judgment model to obtain an output result of each component of the target charging device. The output result has a value of 0 or 1. If the output result of a component of the target charging device is 0, it indicates that the component is normal. If the output result of a component of the target charging device is 1, it indicates that the component of the target charging device has a fault. The component is recorded as a faulty component, and the faulty components of the target charging device are obtained. A three-dimensional model of the target charging device is established to obtain the coordinates of the faulty components of the target charging device. The coordinates of the faulty components of the target charging device are vectorized to obtain a vector set of target charging device faults. The vector set of target charging device faults is respectively calculated for similarity with the vector set of charging pile faults, the vector set of charging gun faults, and the vector set of charging port faults in the database to obtain the target charging device charging pile fault similarity, charging gun fault similarity, and charging port fault similarity. The fault type with the highest similarity is selected as the fault type of the target charging device.

8. The intelligent charging pile system with fault diagnosis according to claim 7, characterized in that: The model expression for the position fault judgment is: Wherein, γd is the output result of the dth component of the target charging device, d is the number of each component, and the value of d is a positive integer. d , K d and t d are the power fluctuation rate, power mutation curvature and number of power mutation points of component No. d, respectively; L′, K′ and t′ are the preset standard power fluctuation rate, standard power mutation curvature and number of standard power mutation points, respectively; η1 and η2 are the preset weight factors of power mutation curvature and power fluctuation rate, respectively; η1>0, η2>0, η1+η2=1, and D is the preset standard.

9. The intelligent charging pile system with fault diagnosis according to claim 8, characterized in that: The specific setting process of setting the fault handling solution is as follows: If the fault type is a charging pile fault, the target charging device's power is obtained from the database. The power with the highest number of occurrences is recorded as the target usage power of the target charging device. The charging adaptation level of the target usage power of each unused charging pile is obtained from the charging adaptation level of each charging power of each unused charging pile. The unused charging pile with the highest charging adaptation level of the target usage power is selected as the charging pile to be replaced. The target vehicle is moved to the charging pile to be replaced for charging, and the staff is prompted to repair the target charging pile. If the fault is a charging gun failure, the robot will unplug the target charging gun, capture an image of the charging gun plug using a camera, identify the stain point using image recognition technology, and then clean it using the robot. After cleaning, the charging gun will be reinserted into the target vehicle. If the stain point cannot be identified using image recognition technology, or if the charging gun still fails after cleaning and reinsertion, it indicates an electrical fault and the robot will replace it. If the fault type is a charging port failure, charging will be stopped and the user will be prompted to perform repairs.

10. The intelligent charging pile system with fault diagnosis according to claim 1 further includes a database for storing the historical charging records of each vehicle, the interval range corresponding to the quality fluctuation index of each charging station, the vector set of charging pile failures, the vector set of charging gun failures, the vector set of charging port failures and the power collected by each charging device at each time.

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