High-reliability charging pile redundancy control system

Abstract

The invention discloses a high-reliability charging pile redundancy control system, and relates to the technical field of charging pile redundancy control. According to the high-reliability charging pile redundancy control system, running state data of a charging gun, a contactor, a communication module and the like are collected and preprocessed in real time through the multi-source data acquisition subsystem, and the running state data are compared and analyzed with reference data through the fault trend preliminary diagnosis subsystem, so that the fault trend is recognized in advance; a support vector machine model of the fault diagnosis subsystem is used to accurately identify a fault mode, and finally the redundancy control strategy generation subsystem matches an optimal strategy according to a historical state vector and a reward value to realize early warning, accurate diagnosis and dynamic redundancy control of a fault. The reliability, the fault handling capacity and the operation efficiency of a charging pile system are improved, the charging interruption risk and the operation and maintenance cost caused by faults are reduced, and the problems that a traditional charging pile cannot be charged due to the faults of a single control board, fault diagnosis is lagged, and a redundancy strategy is rigid are solved.

Description

Technical Field

[0001] The present invention relates to the technical field of redundant control of charging piles, and specifically to a highly reliable redundant control system for charging piles. Background Art

[0002] At present, all dual-gun DC charging integrated machines on the market adopt a control strategy of single-gun single control and power sharing. Once a problem occurs in one control board, the charging gun on that path will malfunction and charging cannot be carried out. Although the charging pile can report the fault status in time, the repair of the charging pile still takes several days, which will not only have a certain impact on the user's charging experience, but also affect the income of the charging station.

[0003] Chinese Patent with Publication No. CN117774760B discloses a redundant control system for a charging gun of a charging pile, belonging to the technical field of charging piles. The technical problem to be solved is that charging cannot be carried out due to a control board failure in the case of single-gun single control. It includes a dual-channel control board, namely a status acquisition board and a charging control board; the status acquisition board is configured with a gun line status acquisition interface, a CAN interface and a processor MCU, where the processor MCU serves as the status acquisition MCU; the charging control board is configured with a processor MCU, a BMS communication interface, an inter-board communication interface, a charging module communication interface and a charging module control line interface; the charging control MCU is used to control the charging process based on the gun line status and the vehicle BMS status stored in its on-board FLASH.

[0004] However, traditional charging piles have problems such as inability to charge due to a single control board failure, lag in fault diagnosis, and rigidity in the redundant strategy. Summary of the Invention

[0005] In view of the deficiencies of the prior art, the present invention provides a highly reliable redundant control system for charging piles, which solves the problems of inability to charge due to a single control board failure, lag in fault diagnosis, and rigidity in the redundant strategy of traditional charging piles.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: A redundant control system for a high-reliability charging pile, including a multi-source data acquisition subsystem for the charging pile, a preliminary fault trend diagnosis subsystem, a fault diagnosis subsystem, and a redundant control strategy generation subsystem, where: The multi-source data acquisition subsystem for the charging pile is used to acquire multi-source operating state data of the charging pile and perform preprocessing to obtain processed multi-source operating state data of the charging pile; The preliminary fault trend diagnosis subsystem is used to perform real-time diagnosis on the processed multi-source operating state data of the charging pile acquired by the multi-source data acquisition subsystem for the charging pile to determine whether there is a trend of the charging pile to fail, and obtain a preliminary diagnosis result; The fault diagnosis subsystem is used to perform fault mode recognition based on a fault diagnosis model when the preliminary diagnosis result indicates that the charging pile has a trend of failing; The redundant control strategy generation subsystem is used to determine a redundant control strategy according to the processed multi-source operating state data of the charging pile after fault mode recognition.

[0007] Further, the processed multi-source operating state data of the charging pile includes the operating characteristics A1 of the charging gun, the operating characteristics B1 of the contactor, and the operating characteristics C1 of the communication module, where: The operating characteristics A1 of the charging gun include the gun head temperature, the cable temperature, the interface temperature, and the current fluctuation amplitude; The operating characteristics B1 of the contactor include the contact resistance and the vibration signal amplitude; The operating characteristics C1 of the communication module include the signal strength, the packet loss rate, and the response delay.

[0008] Further, the multi-source data acquisition subsystem for the charging pile includes a charging gun monitoring module, a contactor monitoring module, a communication module monitoring module, and a data preprocessing module, where: The charging gun monitoring module is used to perform real-time monitoring on the operating state of the charging gun to obtain the initial operating state data of the charging gun; The contactor monitoring module is used to perform real-time monitoring on the operating state of the contactor to obtain the initial operating state data of the contactor; The communication module monitoring module is used to perform real-time monitoring on the operating state of the communication module to obtain the initial operating state data of the communication module; The data preprocessing module is used to receive the initial operating state data of the charging gun, the initial operating state data of the contactor, and the initial operating state data of the communication module, and perform standardization processing to obtain the processed multi-source operating state data of the charging pile.

[0009] Furthermore, the process of obtaining the preliminary diagnosis result on whether there is a tendency for the charging pile to malfunction is as follows: Determine the multi-source operating state reference data of the charging pile, including the operating reference feature A2 of the charging gun, the operating reference feature B2 of the contactor, and the operating reference feature C2 of the communication module; Perform a similarity analysis on the processed multi-source operating state data of the charging pile and the multi-source operating state reference data of the charging pile to determine the abnormal operation evaluation index Gzx of the charging pile; If the abnormal operation evaluation index Gzx of the charging pile is greater than the charging pile operation abnormal evaluation threshold obtained from the database, the preliminary diagnosis result is that there is no tendency for the charging pile to malfunction; If the abnormal operation evaluation index Gzx of the charging pile is not greater than the charging pile operation abnormal evaluation threshold obtained from the database, the preliminary diagnosis result is that there is a tendency for the charging pile to malfunction.

[0010] Furthermore, the calculation formula for the abnormal operation evaluation index Gzx of the charging pile is:

[0011] Gzx = α1 * σ(A1, A2) + α2 * σ(B1, B2) + α3 * σ(C1, C2);

[0012] Where α1, α2, and α3 are all weighting factors, and σ(·) is the cosine similarity function.

[0013] Furthermore, the process of determining the multi-source operating state reference data of the charging pile is as follows: Obtain the corresponding multi-source operating state calibration data of the charging pile from the database based on the charging pile type; Obtain the historical working environment data of the charging pile, including the total usage duration St, the ambient temperature fluctuation range Sw, the ambient humidity fluctuation amplitude Sh, and the monthly average working overload rate Sf; Obtain the matching data - correction factor mapping data set stored in the database, where the matching data includes the total usage duration matching value Ct, the ambient temperature fluctuation range matching value Cw, the ambient humidity fluctuation range matching value Ch, and the monthly average working overload rate matching value Cf, and the correction factors include the operating reference feature correction factor of the charging gun, the operating reference feature correction factor of the contactor, and the operating reference feature correction factor of the communication module; Determine the correction factors based on the historical working environment data of the charging pile and the matching data - correction factor mapping data set, and correct the multi-source operating state calibration data of the charging pile based on the correction factors to obtain the multi-source operating state reference data of the charging pile.

[0014] Furthermore, the process of determining the correction factors based on the historical working environment data of the charging pile and the matching data - correction factor mapping data set is as follows: Compare the historical working environment data of the charging pile with each matching data in the matching data - correction factor mapping data set one by one to obtain the comparison value Bd:

[0015]

[0016] Determine the matching data corresponding to the minimum comparison value to obtain the corresponding correction coefficient.

[0017] Furthermore, the process of fault mode recognition based on the fault diagnosis model is as follows: Obtain the charging pile fault characteristics, including charging gun fault characteristics, contactor fault characteristics, and communication module fault characteristics, where: The charging gun fault characteristics include temperature gradient, current fluctuation variance, and plugging and unplugging force change rate; The contactor fault characteristics include contact resistance increment, action delay time, and arc energy accumulation; The communication module fault characteristics include signal strength attenuation rate, packet loss rate fluctuation coefficient, and communication success rate with mainstream vehicle models; Standardize the charging pile fault characteristics to obtain the standardized charging pile fault characteristics; Input the standardized charging pile fault characteristics into the trained support vector machine model to obtain the fault mode.

[0018] Furthermore, the process of determining the redundancy control strategy according to the processed multi-source operating state data of the charging pile is as follows: Concatenate the processed multi-source operating state data of the charging pile and the standardized charging pile fault characteristics to obtain the charging pile state vector; Obtain the historical charging pile state vector dataset obtained from the database; Determine the historical charging pile state vector most similar to the charging pile state vector from the historical charging pile state vector dataset based on the cosine similarity function; Obtain the redundancy control strategy set corresponding to the most similar historical charging pile state vector from the database, and each redundancy control strategy in the redundancy control strategy set corresponds to a reward value; Select the redundancy control strategy with the largest reward value for redundancy control and update the charging pile state vector; Perform fault trend analysis based on the updated charging pile state vector and update the reward value at the same time. If there is a fault trend, re-select the redundancy control strategy until there is no fault trend.

[0019] Furthermore, the update process of the reward value is as follows: Obtain the updated processed multi-source operating state data of the charging pile in the updated charging pile state vector; Process the updated processed multi-source operating state data of the charging pile by the fault trend preliminary diagnosis subsystem to obtain the updated charging pile operation abnormality evaluation index; Calculate the difference between the updated charging pile operation abnormality evaluation index and the charging pile operation abnormality evaluation index before update to obtain the evaluation value deviation; Obtain the corresponding reward additional value corresponding to the evaluation value deviation from the database through the query table; Add the reward value before update and the reward additional value to obtain the updated reward value.

[0020] The present invention has the following beneficial effects:

[0021] The high-reliability redundant control system for charging piles collects the operation status data of charging guns, contactors, communication modules, etc. in real time through the multi-source data acquisition subsystem and preprocesses it. Through comparison and analysis with the reference data by the preliminary fault trend diagnosis subsystem, the fault trend is identified in advance. Then, with the support of the support vector machine model of the fault diagnosis subsystem, the fault mode is accurately identified. Finally, the redundant control strategy generation subsystem matches the optimal strategy according to the historical state vector and the reward value, realizing the early warning, accurate diagnosis and dynamic redundant control of faults, improving the reliability, fault response ability and operation efficiency of the charging pile system, reducing the risk of charging interruption and operation and maintenance costs caused by faults, and solving the problems of inability to charge due to single control board failure, lagging fault diagnosis and rigid redundant strategy in traditional charging piles.

[0022] Of course, it is not necessary for any product implementing the present invention to achieve all the above advantages simultaneously. Brief Description of the Drawings

[0023] Figure 1 It is a flowchart of the high-reliability redundant control system for charging piles of the present invention. Detailed Embodiment

[0024] Please refer to Figure 1 , an embodiment of the present invention provides a technical solution: a high-reliability redundant control system for charging piles, including a charging pile multi-source data acquisition subsystem, a preliminary fault trend diagnosis subsystem, a fault diagnosis subsystem and a redundant control strategy generation subsystem, wherein: the charging pile multi-source data acquisition subsystem is used to acquire the multi-source operation status data of the charging pile and preprocess it to obtain the processed multi-source operation status data of the charging pile.

[0025] The processed multi-source operation status data of the charging pile includes the charging gun operation feature A1, the contactor operation feature B1 and the communication module operation feature C1, wherein: the charging gun operation feature A1 includes the gun head temperature, the cable temperature, the interface temperature and the current fluctuation amplitude; the contactor operation feature B1 includes the contact resistance and the vibration signal amplitude; the communication module operation feature C1 includes the signal strength, the packet loss rate and the response delay.

[0026] The multi-source data acquisition subsystem of the charging pile includes a charging gun monitoring module, a contactor monitoring module, a communication module monitoring module, and a data preprocessing module. Among them: The charging gun monitoring module is used to monitor the running state of the charging gun in real time to obtain the initial running state data of the charging gun; The contactor monitoring module is used to monitor the running state of the contactor in real time to obtain the initial running state data of the contactor; By using the charging gun monitoring module, the contactor monitoring module, and the communication module monitoring module, key running characteristic data such as the temperature and current fluctuation of the charging gun, the contact resistance and vibration signal of the contactor, and the signal strength and packet loss rate of the communication module can be obtained in real time, realizing the comprehensive monitoring of the state of the core components of the charging pile and avoiding the missed judgment of faults caused by incomplete data collection.

[0027] The communication module monitoring module is used to monitor the running state of the communication module in real time to obtain the initial running state data of the communication module; The data preprocessing module is used to receive the initial running state data of the charging gun, the initial running state data of the contactor, and the initial running state data of the communication module, and perform standardization processing to obtain the processed multi-source running state data of the charging pile. The data preprocessing module performs standardization processing on various types of initial data, which can eliminate the dimensional differences of data from different sensors, ensure the accuracy of subsequent fault trend diagnosis and fault mode recognition, lay a data foundation for the system to detect component abnormal trends in advance and accurately locate the fault type, and then improve the reliability of the charging pile running state assessment, reduce the misjudgment risk caused by data errors, and provide a scientific basis for the dynamic generation of redundant control strategies.

[0028] The preliminary fault trend diagnosis subsystem is used to perform real-time diagnosis on the processed multi-source running state data of the charging pile obtained by the multi-source data acquisition subsystem of the charging pile to determine whether there is a trend of the charging pile to fail and obtain a preliminary diagnosis result.

[0029] The process of determining whether there is a trend of the charging pile to fail and obtaining a preliminary diagnosis result is as follows: Determine the multi-source running state reference data of the charging pile, including the charging gun running reference characteristic A2, the contactor running reference characteristic B2, and the communication module running reference characteristic C2; Perform similarity analysis on the processed multi-source running state data of the charging pile and the multi-source running state reference data of the charging pile to determine the charging pile running abnormal evaluation index Gzx; If the charging pile running abnormal evaluation index Gzx is greater than the charging pile running abnormal evaluation threshold obtained from the database, the preliminary diagnosis result is that there is no trend of the charging pile to fail; If the charging pile running abnormal evaluation index Gzx is not greater than the charging pile running abnormal evaluation threshold obtained from the database, the preliminary diagnosis result is that the charging pile has a trend of failing.

[0030] By comparing the evaluation index with the threshold, it is possible to quickly determine whether there is a fault trend in the charging pile. When the index is not greater than the threshold, a warning is issued in a timely manner, changing the passive mode of traditional after-the-fact maintenance, achieving early detection of faults, winning time for subsequent accurate fault diagnosis and the generation of redundancy control strategies, and effectively reducing the fault incidence rate and downtime losses.

[0031] The calculation formula for the abnormal operation evaluation index Gzx of the charging pile is:

[0032] Gzx = α1 * σ(A1, A2) + α2 * σ(B1, B2) + α3 * σ(C1, C2);

[0033] Where α1, α2, and α3 are all weight factors, and σ(·) is the cosine similarity function.

[0034] The cosine similarity function is used to calculate the similarity between the processed data and the reference data, generating the abnormal operation evaluation index of the charging pile, and transforming the abstract fault trend into a quantifiable numerical indicator. This index differentiates the importance differences of the charging gun, contactor, and communication module through weight factors, realizes the comprehensive evaluation of multi-source data, and ensures the comprehensiveness of abnormal judgment.

[0035] The process of determining the reference data for the multi-source operating state of the charging pile is as follows: Obtain the corresponding reference data for the multi-source operating state of the charging pile from the database based on the charging pile type; Obtain the historical working environment data of the charging pile, including the total usage duration St, the fluctuation range Sw of the ambient temperature, the fluctuation amplitude Sh of the ambient humidity, and the average monthly number of times Sf of working overload; Obtain the matching data - correction factor mapping data set stored in the database, where the matching data includes the matching value Ct of the total usage duration, the matching value Cw of the ambient temperature fluctuation range, the matching value Ch of the ambient humidity fluctuation range, and the matching value Cf of the average monthly number of times of working overload, and the correction factors include the correction factor for the reference characteristics of the charging gun operation, the correction factor for the reference characteristics of the contactor operation, and the correction factor for the reference characteristics of the communication module operation; Determine the correction factors based on the historical working environment data of the charging pile and the matching data - correction factor mapping data set, and correct the reference data for the multi-source operating state of the charging pile based on the correction factors to obtain the reference data for the multi-source operating state of the charging pile.

[0036] By determining the reference data for the multi-source operating state of the charging pile and correcting the reference data in combination with the charging pile type and historical working environment (usage duration, temperature and humidity fluctuations, overload rate, etc.), the reference data is made more in line with the actual operating conditions of the charging pile, avoiding evaluation deviations caused by static references, and solving the problem of benchmark unification in different usage scenarios.

[0037] Determine the correction factor based on the historical working environment data of the charging pile and the matching data - correction factor mapping dataset. The process is as follows: Compare each piece of matching data in the historical working environment data of the charging pile and the matching data - correction factor mapping dataset one by one to obtain the comparison value Bd ：

[0038]

[0039] Determine the matching data corresponding to the smallest comparison value to obtain the corresponding correction factor.

[0040] By means of the matching data - correction factor mapping dataset, the historical working environment data is converted into specific correction factors, realizing the quantitative processing of the influence of environmental factors on the reference data. The mechanism of determining the correction factor based on the smallest comparison value ensures a high degree of matching between the reference data and the actual historical working conditions of the charging pile, making the abnormal evaluation index obtained through similarity analysis more capable of reflecting the true fault trend in the follow-up, avoiding the abnormal evaluation deviation caused by the "one-size-fits-all" of the reference data, providing a more reliable judgment basis for early fault warning, and thus enhancing the reliability and fault prevention ability of the charging pile system.

[0041] The fault diagnosis subsystem is used to identify the fault mode based on the fault diagnosis model when the preliminary diagnosis result indicates a trend of the charging pile having a fault.

[0042] Obtain the charging pile fault characteristics, including the charging gun fault characteristics, contactor fault characteristics, and communication module fault characteristics. Among them: The charging gun fault characteristics include the temperature gradient, current fluctuation variance, and plugging and unplugging force change rate; The contactor fault characteristics include the contact resistance increment, action delay time, and arc energy accumulation; The communication module fault characteristics include the signal strength attenuation rate, packet loss rate fluctuation coefficient, and communication success rate with mainstream vehicle models; Extract core fault characteristics such as the temperature gradient, contact resistance increment, and signal strength attenuation rate for the charging gun, contactor, and communication module respectively, covering the key indicators of typical fault modes such as component aging, poor contact, and communication anomalies, avoiding the missed judgment of faults caused by a single characteristic, and realizing the multi-dimensional characterization of faults.

[0043] Perform standardization processing on the charging pile fault characteristics to obtain the standardized charging pile fault characteristics; Performing standardization processing on the fault characteristics eliminates the influence of different characteristic dimensions, enables heterogeneous data such as temperature, current, and signal strength to be comparable, ensures that the SVM model can accurately learn the internal laws of the fault mode, and improves the adaptability of the model to different charging piles and different operating scenarios.

[0044] The standardized fault features of the charging pile are input into the trained support vector machine model to obtain the fault mode. The trained SVM model is used to classify the standardized features, and its non-linear mapping ability can effectively handle the complex correlations between fault features (such as the coupling relationship between temperature gradient and current fluctuation), realizing the accurate identification of specific fault modes such as poor contact of the charging gun, adhesion of the contactor, and incompatibility of communication protocols. Compared with traditional rule matching, it has stronger robustness and generalization ability, providing an accurate basis for the type of fault for the generation of subsequent redundancy control strategies, thereby improving the pertinence and efficiency of charging pile fault handling.

[0045] In the training stage, the support vector machine model adopts the RBF kernel function, and the optimal parameters are determined through grid search. The range of C (penalty coefficient) is [0.1, 1, 10, 100], and the range of γ (kernel function width) is [0.01, 0.1, 1, 10].

[0046] The redundancy control strategy generation subsystem is used to determine the redundancy control strategy according to the processed multi-source operating state data of the charging pile after the fault mode is recognized.

[0047] The processed multi-source operating state data of the charging pile and the standardized fault features of the charging pile are concatenated to obtain the charging pile state vector; the historical charging pile state vector dataset obtained from the database is acquired; the historical charging pile state vector most similar to the charging pile state vector is determined from the historical charging pile state vector dataset based on the cosine similarity function; the redundancy control strategy set corresponding to the most similar historical charging pile state vector is obtained from the database, and each redundancy control strategy in the redundancy control strategy set corresponds to a reward value; the redundancy control strategy with the largest reward value is selected for redundancy control, and the charging pile state vector is updated; based on the updated charging pile state vector, the fault trend analysis is carried out and the reward value is updated simultaneously. If there is a fault trend, the redundancy control strategy is reselected until there is no fault trend.

[0048] The processed operating data and fault features are concatenated into a state vector, and the historical optimal strategy is matched through cosine similarity, realizing the efficient reuse of past fault handling experience. Each redundancy control strategy corresponds to a reward value, and the reward is dynamically updated through the evaluation value deviation, forming a closed-loop optimization mechanism of "strategy execution - effect evaluation - reward update", enabling the system to automatically screen high-value strategies and gradually eliminate low-efficiency strategies.

[0049] The process of updating the reward value is as follows: Obtain the updated processed multi-source operating status data of the charging pile in the updated charging pile status vector; Process the updated processed multi-source operating status data of the charging pile by the fault trend preliminary diagnosis subsystem to obtain the updated abnormal operation evaluation index of the charging pile; Calculate the difference between the updated abnormal operation evaluation index of the charging pile and the abnormal operation evaluation index of the charging pile before the update to obtain the evaluation value deviation; Obtain the corresponding reward additional value corresponding to the evaluation value deviation from the database through the query table; Add the reward value before the update and the reward additional value to obtain the updated reward value.

[0050] Updating the charging pile status vector and circularly evaluating the fault trend can ensure the effectiveness of the strategy in complex scenarios. If there is still a fault trend after the first execution of the strategy, the system will re-match the strategy until the fault is eliminated, avoiding the processing ineffectiveness caused by static strategies. The update of the reward value is based on the quantitative deviation of the abnormal evaluation index, avoiding the limitations of subjective rule design. By associating the evaluation deviation with the reward additional value through the database query table, the strategy effect can be quantified and traced.

[0051] An electronic device includes: a processor; and a memory in which computer program instructions are stored, and when the computer program instructions are run by the processor, the processor is caused to execute the highly reliable charging pile redundancy control system as described above.

[0052] A computer-readable storage medium is used to store a program, and when the program is executed by a processor, the highly reliable charging pile redundancy control system as described above is implemented.

[0053] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present invention can take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0054] The present invention is described with reference to the flowcharts and / or block diagrams of systems, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowcharts and / or block diagrams, and the combination of processes and / or blocks in the flowcharts and / or block diagrams, can be realized by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for realizing the process Figure 1one process or multiple processes and / or blocks Figure 1 means for the functions specified in one block or multiple blocks.

[0055] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured article including an instruction means, and the instruction means implements the processes Figure 1 one process or multiple processes and / or blocks Figure 1 the functions specified in one block or multiple blocks.

[0056] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to produce a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0057] Although the preferred embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the present invention.

[0058] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalent technologies, the present invention also intends to include these modifications and variations.

Claims

1. A redundant control system for a charging pile with high reliability, characterized in that, It includes a multi-source data acquisition subsystem for charging piles, a preliminary fault trend diagnosis subsystem, a fault diagnosis subsystem, and a redundant control strategy generation subsystem, where: The multi-source data acquisition subsystem for charging piles is used to acquire multi-source operation status data of charging piles and perform preprocessing to obtain processed multi-source operation status data of charging piles; The preliminary fault trend diagnosis subsystem is used to perform real-time diagnosis on the processed multi-source operation status data of charging piles acquired by the multi-source data acquisition subsystem for charging piles to determine whether there is a trend of faults occurring in the charging piles and obtain a preliminary diagnosis result; The fault diagnosis subsystem is used to perform fault mode recognition based on a fault diagnosis model when the preliminary diagnosis result indicates that there is a trend of faults occurring in the charging piles; The redundant control strategy generation subsystem is used to determine a redundant control strategy according to the processed multi-source operation status data of charging piles after fault mode recognition.

2. The redundant control system of a high-reliability charging pile according to claim 1, characterized in that, The processed multi-source operation status data of charging piles includes the operation characteristics A1 of the charging gun, the operation characteristics B1 of the contactor, and the operation characteristics C1 of the communication module, where: The operation characteristics A1 of the charging gun include the gun head temperature, the cable temperature, the interface temperature, and the current fluctuation amplitude; The operation characteristics B1 of the contactor include the contact resistance and the vibration signal amplitude; The operation characteristics C1 of the communication module include the signal strength, the packet loss rate, and the response delay.

3. The redundant control system of a high-reliability charging pile according to claim 2, characterized in that, The multi-source data acquisition subsystem for charging piles includes a charging gun monitoring module, a contactor monitoring module, a communication module monitoring module, and a data preprocessing module, where: The charging gun monitoring module is used to perform real-time monitoring on the operation status of the charging gun to obtain the initial operation status data of the charging gun; The contactor monitoring module is used to perform real-time monitoring on the operation status of the contactor to obtain the initial operation status data of the contactor; The communication module monitoring module is used to perform real-time monitoring on the operation status of the communication module to obtain the initial operation status data of the communication module; The data preprocessing module is used to receive the initial operation status data of the charging gun, the initial operation status data of the contactor, and the initial operation status data of the communication module, and perform normalization processing to obtain the processed multi-source operation status data of charging piles.

4. The redundant control system of a high-reliability charging pile according to claim 3, characterized in that The process of determining whether there is a trend of faults occurring in the charging piles and obtaining a preliminary diagnosis result is as follows: Determine the multi-source operation status reference data of the charging piles, including the operation reference characteristics A2 of the charging gun, the operation reference characteristics B2 of the contactor, and the operation reference characteristics C2 of the communication module; Perform similarity analysis on the processed multi-source operation status data of the charging piles and the multi-source operation status reference data of the charging piles to determine the charging pile operation anomaly evaluation index Gzx; If the charging pile operation anomaly evaluation index Gzx is greater than the charging pile operation anomaly evaluation threshold obtained from the database, the preliminary diagnosis result is that there is no trend of faults occurring in the charging piles; If the charging pile operation anomaly evaluation index Gzx is not greater than the charging pile operation anomaly evaluation threshold obtained from the database, the preliminary diagnosis result is that there is a trend of faults occurring in the charging piles.

5. The redundant control system for a high-reliability charging pile according to claim 4, wherein, The calculation formula for the charging pile operation anomaly evaluation index Gzx is: Gzx = α1 * σ(A1, A2) + α2 * σ(B1, B2) + α3 * σ(C1, C2); Where, α1, α2, and α3 are all weight factors, and σ(·) is the cosine similarity function.

6. The redundant control system of a high-reliability charging pile according to claim 4, characterized in that, The process of determining the reference data for the multi-source operating state of the charging pile is as follows: Obtain the corresponding reference data for the multi-source operating state of the charging pile from the database based on the charging pile type; Obtain the historical working environment data of the charging pile, including the total usage duration St, the amplitude of environmental temperature fluctuation Sw, the amplitude of environmental humidity fluctuation Sh, and the average number of monthly working overload rate times Sf; Obtain the matching data - correction factor mapping data set stored in the database. The matching data includes the matching value Ct of the total usage duration, the matching value Cw of the amplitude of environmental temperature fluctuation, the matching value Ch of the amplitude of environmental humidity fluctuation, and the matching value Cf of the average number of monthly working overload rate times. The correction factors include the correction factor for the reference characteristics of the charging gun operation, the correction factor for the reference characteristics of the contactor operation, and the correction factor for the reference characteristics of the communication module operation; Determine the correction factors based on the historical working environment data of the charging pile and the matching data - correction factor mapping data set, and correct the reference data for the multi-source operating state of the charging pile based on the correction factors to obtain the reference data for the multi-source operating state of the charging pile.

7. A redundant control system for a high-reliability charging pile according to claim 6, characterized in that, The process of determining the correction factors based on the historical working environment data of the charging pile and the matching data - correction factor mapping data set is as follows: Compare the historical working environment data of the charging pile with each matching data in the matching data - correction coefficient mapping dataset one by one to obtain the comparison value Bd ： Determine the matching data corresponding to the minimum comparison value to obtain the corresponding correction factor.

8. A redundant control system for a high-reliability charging pile according to claim 3, characterized in that, The process of performing fault mode recognition based on the fault diagnosis model is as follows: Obtain the fault characteristics of the charging pile, including the fault characteristics of the charging gun, the fault characteristics of the contactor, and the fault characteristics of the communication module, where: The fault characteristics of the charging gun include the temperature gradient, the variance of current fluctuation, and the change rate of plugging and unplugging force; The fault characteristics of the contactor include the increment of contact resistance, the action delay time, and the accumulation of arc energy; The fault characteristics of the communication module include the signal strength attenuation rate, the packet loss rate fluctuation coefficient, and the communication success rate with mainstream vehicle models; Perform standardization processing on the fault characteristics of the charging pile to obtain the standardized fault characteristics of the charging pile; Input the standardized fault characteristics of the charging pile into the trained support vector machine model to obtain the fault mode.

9. A redundant control system for a high-reliability charging pile according to claim 8, characterized in that, The process of determining the redundancy control strategy based on the processed multi-source operating state data of the charging pile is as follows: Concatenate the processed multi-source operating state data of the charging pile and the standardized fault characteristics of the charging pile to obtain the charging pile state vector; Obtain the historical charging pile state vector data set obtained from the database; Determine the historical charging pile state vector most similar to the charging pile state vector from the historical charging pile state vector data set based on the cosine similarity function; Obtain the redundancy control strategy set corresponding to the most similar historical charging pile state vector from the database. Each redundancy control strategy in the redundancy control strategy set corresponds to a reward value; Select the redundancy control strategy with the largest reward value for redundancy control and update the charging pile state vector; Perform fault trend analysis based on the updated charging pile state vector and update the reward value at the same time. If there is a fault trend, re-select the redundancy control strategy until there is no fault trend.

10. A highly reliable redundant control system for a charging pile according to claim 9, characterized in that, The update process of the reward value is: Obtain the updated processed multi-source operating state data in the updated charging pile state vector; The preliminary diagnosis subsystem based on the fault trend processes the multi-source operation status data of the charging pile after update and processing, and obtains the abnormal operation evaluation index of the updated charging pile; Calculate the difference between the abnormal operation evaluation index of the updated charging pile and the abnormal operation evaluation index of the charging pile before update to obtain the evaluation value deviation; Obtain the corresponding reward additional value corresponding to the evaluation value deviation from the database through the query table; Add the reward value before update and the reward additional value to obtain the updated reward value.

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