Direct current charging pile fault detection method and system

Abstract

A DC charging pile fault detection method comprises the following steps: a charging pile data acquisition step; a load charging abnormity analysis step; a charging mode judgment step; and judging the credibility of the charging pile. A DC charging pile fault detection system comprises a charging pile data acquisition module used for acquiring real-time charging data of a load connected to a charging pile; the load charging abnormity analysis module is used for calling historical charging data of a load according to the type of the load accessed into the charging pile, and respectively calculating the difference values between the load current value and the load voltage value in the real-time charging data and the load current mean value and the load voltage mean value in the historical charging data to obtain a current difference value and a voltage difference value; the current difference value and the voltage difference value are compared with a preset threshold value, and when the current difference value and the voltage difference value are larger than the preset threshold value, a charging abnormity instruction is output; the charging mode judgment module judges the charging mode of the charging pile through a charging mode judgment model according to the load type and the real-time charging data; and the charging pile trust degree judgment module is used for constructing a trust degree prediction model, calculating a trust value through the trust degree prediction model according to the predicted value and the measured value of the working parameter of the charging pile, and outputting an abnormal condition according to a comparison result of the trust value and a preset trust threshold value.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of charging, in particular to a direct current charging pile fault detection method and system. BACKGROUND

[0002] With the popularity of electric vehicles, direct current charging piles are increasingly widely used. However, voltage or current may suddenly change during charging, which may be caused by charging pile failure or vehicle problems. Therefore, it is particularly important to develop a direct current charging pile fault detection method that can accurately determine the source of the fault.

[0003] Currently, the design idea of a direct current charging pile fault detection method is as follows: first, analyze the vehicle (i.e. load) connected to the charging and obtain the current charging data. Second, compare the current charging data with the historical charging data of the load, and determine that there is an anomaly when the difference exceeds the set threshold. Next, a charging mode prediction model is constructed, which can predict the current charging mode according to the load type, charging data and other related parameters. Charging modes include normal charging, protection charging and fast charging, and different modes will affect the load's own parameters. Finally, a trust degree prediction model is constructed to output a trust value representing the degree of trust in the charging pile, so as to determine whether the anomaly is caused by the charging pile or the load. This method has some limitations in actual application. First, for the first time connected load, there is a lack of accurate historical charging data, which may affect the accuracy of the judgment. Second, the accuracy of the charging mode prediction model directly affects the subsequent anomaly judgment, but the existing model may not fully consider various influencing factors. In addition, the parameter selection and weight distribution of the trust degree prediction model may also affect the reliability of the judgment result.

[0004] Another important aspect is that existing fault detection methods mainly focus on electrical parameters, while ignoring the influence of environmental factors on the charging process. For example, environmental factors such as humidity and smoke may cause charging pile failure, but existing methods cannot effectively monitor these factors.

[0005] Therefore, in order to solve the above problems, the present application proposes a direct current charging pile fault detection method and system. SUMMARY

[0006] In view of the deficiencies in the prior art, the purpose of the present application is to provide a direct current charging pile fault detection method and system.

[0007] To achieve the above-mentioned purpose, the present application provides the following technical solutions: A direct current charging pile fault detection method, comprising the following steps: A charging pile data acquisition step, acquiring real-time charging data of a load connected to the charging pile; The load charging abnormality analysis step calls historical charging data of the load according to the type of the load connected to the charging pile, respectively calculates the difference between the load current value and the load voltage value in the real-time charging data and the load current average and the load voltage average in the historical charging data to obtain a current difference value and a voltage difference value, compares the current difference value, the voltage difference value and the size of the preset threshold value, and outputs a charging abnormality instruction when the current difference value and the voltage difference value are greater than the preset threshold value. The charging mode judgment step judges the charging mode of the charging pile according to the load type and the real-time charging data through a charging mode judgment model. The charging pile trust degree judgment step includes constructing a trust degree prediction model, calculating a trust value through the trust degree prediction model according to the predicted value and the measured value of the charging pile working parameter, and outputting an abnormal condition according to the comparison result of the trust value and the preset trust threshold.

[0008] As a further improvement of the application, the historical charging data acquisition includes that when the vehicle is connected to the charging pile, the charging pile identifies the load type through the load resistance value, the load initial voltage response characteristic and the power factor angle difference, when the load type is a known type, the load current average and the load voltage average in the historical charging process of the load type are directly called as the historical charging data, when the load type is an unknown type, the closest known load type is matched according to the load resistance value combined with the real-time charging data, and the historical charging data of the known load type is weighted to obtain a charging data as the historical charging data of the current load according to the real-time charging data of the current load.

[0009] As a further improvement of the application, the charging mode judgment step includes judging the charging mode of the current load when the charging abnormality instruction is received, the charging mode includes a stable charging mode, a protection charging mode and a fast charging mode, when the current load is in the stable charging mode, the real-time charging data is in the stable stage, at this time, the load current value and the load voltage value remain unchanged, when the current load is in the protection charging mode, the real-time charging data is lower than the load voltage value and the load current value when the load is in the stable charging mode, and there is an amplitude mutation, when the current load is in the fast charging mode, the real-time charging data is higher than the load voltage value and the load current value when the load is in the stable charging mode, at this time, the power stability value of the load is reduced due to the temperature influence.

[0010] As a further improvement of the application, the charging pile trust degree judgment step includes calculating the predicted value of the charging pile working parameter through the charging mode and the real-time charging data of the charging pile respectively, and calculating the trust value after the predicted value and the actually measured charging pile working parameter measured value are weighted.

[0011] As a further improvement of the application, the predicted value calculation is configured with: ; Wherein, P is a prediction value, used for trust evaluation; is a charging mode weight adjustment function, M is a charging mode discriminant value, according to the amplitude of the charging mode, V t is a current load voltage measurement value, V avg is the average value of the voltage in the historical charging data, T is the current ambient temperature value, T ref is a preset standard ambient temperature, I t is a current load current measurement value, I avg is the average value of the current in the historical charging data, is a power stability value filtering function, △P is the difference between the real-time power and the stable power, μ p is the mean value of the historical power stability value, σ p is the standard deviation of the historical power stability value, t is the current time point, and T is the length of the historical time period for calculation.

[0012] As a further improvement of the application, the charging pile trust degree judgment further comprises setting a first trust threshold and a second trust threshold, when the trust value calculated by the trust degree prediction model is higher than the first trust threshold, the output judgment instruction is that the charging pile is normal; when the trust value is lower than the first trust threshold and higher than the second trust threshold, the historical charging data of the current load is weighted to obtain new historical charging data according to the trust value; when the trust value is lower than the second trust threshold, an abnormal charging pile instruction is output.

[0013] As a further improvement of the application, the trust value calculation is configured with: ; Wherein, Tr is the trust value, indicating the trust degree of the charging pile, the higher the value, the less likely the charging pile is abnormal, P(t) represents the prediction value at time t, and W(t) represents the measured value at time t, represents the weight of the prediction value, represents the weight of the actual value.

[0014] As a further improvement of the application, a humidity sensor and a smoke sensor are further installed inside the charging pile to monitor the humidity and smoke concentration of the charging pile environment in real time, and when the humidity or smoke concentration of the charging pile environment is higher than the preset alarm value, an environment abnormal alarm instruction is output.

[0015] A direct current charging pile fault detection system, comprising: A charging pile data acquisition module acquires real-time charging data of a load connected to the charging pile; The load charging abnormality analysis module calls historical charging data of the load according to the type of the load connected to the charging pile, respectively calculates the difference between the load current value and the load voltage value in the real-time charging data and the load current mean value and the load voltage mean value in the historical charging data to obtain a current difference value and a voltage difference value, compares the current difference value, the voltage difference value and a preset threshold value, and outputs a charging abnormality instruction when the current difference value and the voltage difference value are greater than the preset threshold value. The charging mode judgment module judges the charging mode of the charging pile according to the load type and the real-time charging data through a charging mode judgment model. The charging pile trustworthiness judgment module constructs a trustworthiness prediction model, calculates a trustworthiness value through the trustworthiness prediction model according to the predicted value and the measured value of the charging pile working parameters, and outputs an abnormality according to the comparison result of the trustworthiness value and a preset trustworthiness threshold.

[0016] As a further improvement of the application, the direct current charging pile fault detection system is further provided with a temperature sensor and a humidity sensor, which can monitor the humidity and smoke concentration of the charging pile environment in real time, and output an environment abnormality alarm instruction when the humidity or smoke concentration of the charging pile environment is higher than a preset alarm value.

[0017] The beneficial effects of the application are: BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 The method flowchart of the application is shown in the figure; DETAILED DESCRIPTION

[0019] The application will be further described in detail below in combination with the drawings and examples. Identical parts are denoted by the same reference numerals. It should be noted that the words "front", "back", "left", "right", "up" and "down" used in the following description refer to the directions in the drawings, and the words "bottom surface" and "top surface", "inner" and "outer" refer to the directions towards or away from the geometric center of a particular part.

[0020] In the current technical field, there is a need to detect faults during the charging process of a direct current charging pile for a vehicle. The existing technology mainly relies on simple current and voltage monitoring means, which cannot accurately distinguish between charging pile faults and vehicle faults, resulting in low fault troubleshooting efficiency. Especially during the charging process, when the voltage or current suddenly changes, the existing technology cannot effectively determine the source of the fault, affecting the safety and reliability of the charging.

[0021] To solve the above problems, the application provides a direct current charging pile fault detection method. As shown in the figure, Figure 1 The method comprises the following steps: Real-time charging data of the load connected to the charging pile is collected. Through the acquisition of real-time data, basic data support is provided for subsequent abnormality analysis and mode judgment.

[0022] According to the load type of the access charging pile, the historical charging data of the load is called. The difference between the load current value and the load voltage value in the real-time charging data and the load current mean value and the load voltage mean value in the historical charging data is calculated respectively to obtain the current difference value and the voltage difference value. The size of the current difference value, the voltage difference value and the preset threshold value is compared, and when the current difference value, the voltage difference value is greater than the preset threshold value, the charging abnormal instruction is output. In this way, the abnormal situation in the charging process can be found in time.

[0023] According to the load type and the real-time charging data, the charging mode of the charging pile is judged through the charging mode judgment model. The judgment of the charging mode is helpful to further analyze the abnormal source, and the charging mode includes ordinary charging, protection charging and fast charging, etc. Different charging modes correspond to different charging behavior characteristics.

[0024] A trust degree prediction model is constructed, and the trust value is calculated through the trust degree prediction model according to the predicted value and the measured value of the charging pile working parameter. The trust value represents the trust degree of the charging pile, and the higher the trust value, the smaller the possibility of charging pile abnormality. The abnormal situation is output through the comparison result of the trust value and the preset trust threshold. The introduction of the trust degree prediction model can more accurately judge the abnormal source, whether it is a charging pile fault or a vehicle itself fault.

[0025] In the specific implementation process, the load charging abnormality analysis step detects the abnormality by comparing the difference between the real-time data and the historical data, the charging mode judgment step determines the current charging mode through the judgment model, and the charging pile trust degree judgment step calculates the trust value through the trust degree prediction model and judges the abnormal situation according to the trust value. These technical features cooperate with each other to effectively detect whether there is a fault in the charging process of the charging pile for the vehicle.

[0026] For example, when the load is connected to the charging pile, first, the real-time charging data of the load is collected. Then the historical charging data of the load is called, and the difference between the load current value and the load voltage value in the real-time charging data and the load current mean value and the load voltage mean value in the historical charging data is calculated respectively to obtain the current difference value and the voltage difference value. The size of the current difference value, the voltage difference value and the preset threshold value is compared, and when the current difference value, the voltage difference value is greater than the preset threshold value, the charging abnormal instruction is output. Next, according to the load type and the real-time charging data, the charging mode of the charging pile is judged through the charging mode judgment model. Finally, the trust value is calculated through the trust degree prediction model, and the abnormal situation is output according to the comparison result of the trust value and the preset trust threshold.

[0027] Through the above steps, the problem of detecting faults in the charging process of the charging pile for the vehicle can be effectively solved, and the safety and reliability of the charging process are improved.

[0028] Further, the application also proposes that the historical charging data acquisition includes, when the vehicle accesses the charging pile, the charging pile identifies the load type through the load resistance value, the load initial voltage response characteristic and the power factor angle difference, when the load type is a known type, directly calling the load current average and the load voltage average in the historical charging process of the load type as the historical charging data; when the load type is an unknown type, matching the closest known load type according to the load resistance value combined with the real-time charging data, and obtaining a charging data as the historical charging data of the current load by weighting the historical charging data of the known load type according to the real-time charging data of the current load.

[0029] When the vehicle accesses the charging pile, the load type is identified through the load resistance value, the load initial voltage response characteristic and the power factor angle difference. The role of these technical features is to accurately identify the load type, so as to ensure that the appropriate historical charging data is called. If the load type is known, the system directly calls the historical charging data of the load type. If the load type is unknown, the closest known load type is matched according to the load resistance value and the real-time charging data, and the historical charging data thereof is weighted to generate the historical charging data of the current load. In this way, by identifying the load type and obtaining the corresponding historical charging data, accurate charging abnormality analysis and judgment can be performed.

[0030] The load resistance value, the load initial voltage response characteristic and the power factor angle difference are key parameters for identifying the load type. The load resistance value can be calculated by measuring the current and voltage of the load at the instant of access; the load initial voltage response characteristic refers to the voltage change of the load at the instant of access; and the power factor angle difference is determined by the phase difference between the current and voltage of the load. Through comprehensive analysis of these parameters, the type of the load can be accurately identified.

[0031] When the identified load type is a known type, the historical charging data of the type is directly called, which includes the load current average and the load voltage average. These historical data can be used as a reference for comparison and analysis of real-time charging data.

[0032] When the identified load type is an unknown type, the closest known load type is matched through the load resistance value and the real-time charging data. Specifically, the matching can be performed by calculating the similarity of the load resistance value with the resistance value of the known load type. At the same time, the closest known load type is further determined in combination with the real-time charging data. Then, according to the real-time charging data of the current load, the historical charging data of the known load type is weighted to obtain a new charging data as the historical charging data of the current load.

[0033] The application can quickly and accurately obtain historical charging data when the vehicle accesses the charging pile by identifying the load type and calling the corresponding historical charging data. This not only improves the working efficiency of the charging pile, but also can timely discover charging abnormal conditions by comparing real-time charging data and historical charging data, ensuring the safety and stability of the charging process. Compared with the prior art, the method of the application is more accurate in load identification and data calling, can better adapt to different types of loads, and has high practical value.

[0034] Further, the application also proposes that when the charging abnormal instruction is received, the charging mode of the current load is judged, including stable charging mode, protection charging mode and fast charging mode. When the current load is in stable charging mode, the real-time charging data is in stable stage, at this time the load current value and the load voltage value remain unchanged; when the current load is in protection charging mode, the real-time charging data is lower than the load voltage value and the load current value when the load is in stable charging, and there is amplitude mutation; when the current load is in fast charging mode, the real-time charging data is higher than the load voltage value and the load current value when the load is in stable charging, at this time the power stable value of the load is reduced due to temperature influence.

[0035] The charging mode judgment step plays an important role in solving the problem of how to judge the charging mode of the current load when the charging abnormal instruction is received. By judging the charging mode of the current load, the cause of the charging abnormality can be further analyzed. In stable charging mode, the load current value and the load voltage value remain unchanged, indicating that the charging process is normal; in protection charging mode, the real-time charging data is lower than the load voltage value and the load current value when the load is in stable charging, and there is amplitude mutation, indicating that the charging process may be abnormal; in fast charging mode, the real-time charging data is higher than the load voltage value and the load current value when the load is in stable charging, and the power stable value is reduced due to temperature influence, indicating that the charging speed is accelerated but may cause temperature rise. Through these judgments, the causes of charging pile failure and load failure can be effectively distinguished.

[0036] Specifically, the charging mode of the current load is realized by analyzing the real-time charging data. For example, when the load current value and the load voltage value of the real-time charging data remain unchanged, it can be judged that the current load is in stable charging mode; when the real-time charging data is lower than the load voltage value and the load current value when the load is in stable charging, and there is amplitude mutation, it can be judged that the current load is in protection charging mode; when the real-time charging data is higher than the load voltage value and the load current value when the load is in stable charging, and the power stable value of the load is reduced due to temperature influence, it can be judged that the current load is in fast charging mode. Through these judgment methods, the charging mode of the current load can be accurately identified, thereby providing a basis for further fault analysis.

[0037] Therefore, the charging mode judgment step can effectively judge the charging mode of the current load when receiving the charging abnormal instruction, and further analyze the cause of the charging abnormality. This not only improves the accuracy of fault detection, but also quickly distinguishes between charging pile faults and load faults, so that appropriate measures can be taken for processing. This method has significant advantages in the prior art and can significantly improve the fault detection efficiency and accuracy of the charging pile.

[0038] Further, the charging pile trust degree judgment step includes calculating a predicted value of the charging pile working parameter through the charging mode and real-time charging data of the charging pile respectively, and calculating the trust value after weight configuration of the predicted value and the actually measured charging pile working parameter measured value.

[0039] The technical scheme of the present application calculates the predicted value of the charging pile working parameter through the charging mode and real-time charging data of the charging pile, and finally obtains the trust value after weight configuration of the predicted value and the actually measured charging pile working parameter measured value. The trust value is used to judge whether the charging pile is abnormal, and the higher the trust value, the less likely the charging pile is abnormal.

[0040] Specifically, in the charging pile trust degree judgment step, first, the predicted value of the charging pile working parameter is calculated through the charging mode and real-time charging data. Then, the predicted value and the actually measured charging pile working parameter measured value are weight configured to calculate the trust value. The trust value is a quantitative evaluation of whether the charging pile is abnormal, and the higher the trust value, the more normal the working state of the charging pile.

[0041] The predicted value calculation configuration includes: ; Wherein, P is the predicted value, used for trust degree evaluation; is a charging mode weight adjustment function, M is a charging mode discrimination value, according to the amplitude of the charging mode, V t is the current load voltage measurement value, V avg is the average voltage in the historical charging data, T is the current environmental temperature value, T ref is the preset standard environmental temperature, I t is the current load current measurement value, I avg is the average current in the historical charging data, is a power stability value filtering function, △P is the difference between the real-time power and the stable power, μ p is the average value of the historical power stability value, σ p is the standard deviation of the historical power stability value, t is the current time point, and T is the length of the historical time period for calculation.

[0042] The calculation of the prediction value includes multiple parameters and functions corresponding to the charging mode, load voltage, ambient temperature, load current, and power stability value, etc. Through the calculation of these parameters and functions, a comprehensive prediction value is obtained. This prediction value is used for trust assessment to help determine whether the charging pile is abnormal. Through the calculation of the above prediction value, multiple influencing factors can be considered comprehensively, making the trust assessment more accurate, and thus improving the reliability and accuracy of fault detection.

[0043] Further, the calculation process of the prediction value involves the use of multiple parameters and functions. The charging mode weight adjustment function is used to adjust the amplitude of the prediction value according to different charging modes. The difference between the measured value of the load voltage and the load current and their historical mean reflects the degree of deviation of the current load state from the historical state. The change of the ambient temperature affects the calculation of the prediction value through the temperature adjustment function. The power stability value filtering function is used to process the difference between the real-time power and the stable power, combined with the mean and standard deviation of the historical power stability value, to further enhance the accuracy of the prediction value.

[0044] Thus, by comprehensively considering multiple factors such as charging mode, load voltage, ambient temperature, load current, and power stability value, the calculation of the prediction value can more accurately reflect the working state of the charging pile. Compared with the prior art, the prediction value calculation method of the present application improves the accuracy of trust assessment, thereby enhancing the reliability and accuracy of charging pile fault detection.

[0045] Through the above technical solutions, the present application can effectively judge the working state of the charging pile and timely discover abnormal conditions of the charging pile, improving the safety and reliability of the charging pile. Compared with the prior art, the present application has the advantage that by combining the charging mode and real-time charging data, the working parameters of the charging pile can be more accurately predicted, thereby improving the accuracy and reliability of the trust value. Thus, it can better determine whether the charging pile is abnormal, ensuring the safety of the charging process.

[0046] Further, the present application also proposes that the trust degree judgment of the charging pile further includes setting a first trust threshold and a second trust threshold, when the trust value calculated by the trust degree prediction model is higher than the first trust threshold, outputting a judgment instruction that the charging pile is normal; when the trust value is lower than the first trust threshold and higher than the second trust threshold, the historical charging data of the current load is weighted to obtain new historical charging data according to the trust value; when the trust value is lower than the second trust threshold, outputting an abnormal instruction of the charging pile.

[0047] The application improves the accuracy of the judgment by setting the first trust threshold and the second trust threshold. The setting of the first trust threshold and the second trust threshold enables the judgment results of no anomaly of the charging pile, weighted processing of the historical charging data, and output of the charging pile anomaly instruction to be output respectively when the trust value is in different intervals. In solving the technical problem of how to distinguish the charging pile anomaly and the load anomaly, the technical feature of the charging pile trust degree judgment enables the trust degree prediction model to output different judgment results according to different intervals of the trust value, thereby improving the accuracy of the judgment.

[0048] Further, the first trust threshold and the second trust threshold can be adjusted according to actual application conditions. For example, a reasonable threshold range can be determined through statistical analysis of historical data. The trust degree prediction model can use a machine learning algorithm to gradually improve the prediction accuracy of the model through training on a large amount of historical data. In the case where the trust value is lower than the first trust threshold but higher than the second trust threshold, the historical charging data of the current load is weighted and processed, which can dynamically update the historical data and improve the accuracy of subsequent judgments.

[0049] The application sets different trust thresholds, so that the trust degree prediction model can output different judgment results in different trust value intervals, avoiding the misjudgment problem that may be caused by a single threshold. Thus, the accuracy of distinguishing the charging pile anomaly and the load anomaly is improved, and the safety and reliability of the charging process are improved.

[0050] Further, the trust value calculation is configured to: ; Wherein Tr is the trust value, representing the trust degree of the charging pile, and the higher the value, the less likely the charging pile is abnormal, P(t) represents the predicted value at time t, and W(t) represents the measured value at time t, represents the weight of the predicted value, represents the weight of the actual value.

[0051] The application evaluates the trust degree of the charging pile through trust value calculation. The calculation formula of the trust value is Tr = α *P(t) + β * W(t), where Tr represents the trust value, P(t) is the predicted value, W(t) is the measured value, and α and β are the weights of the predicted value and the measured value, respectively. This trust value is used to represent the trust degree of the charging pile, and the higher the value, the less likely the charging pile is abnormal. Through the above technical features, the application solves the problem of how to accurately evaluate the trust degree of the charging pile. When calculating the trust value, the predicted value and the measured value are considered comprehensively, and the weight adjustment is used to improve the accuracy of the evaluation, thereby effectively judging whether the charging pile is abnormal.

[0052] The calculation of the trust value can be achieved in various ways. For example, the predicted value P(t) can be calculated based on historical data and the current charging mode, and the measured value W(t) can be directly obtained from the real-time data of the charging pile. The weight α of the predicted value and the weight β of the measured value can be adjusted according to the specific application scenario to ensure the accuracy and reliability of the calculation result of the trust value. Further, the weights of the predicted value and the measured value can be dynamically adjusted according to different charging modes and environmental conditions to adapt to different use scenarios.

[0053] By introducing the calculation of the trust value, the application effectively improves the accuracy of the trust degree evaluation of the charging pile. Compared with the prior art, the application can more accurately determine whether the charging pile has abnormal conditions, thereby improving the reliability of the charging pile and the user experience.

[0054] Further, the application also proposes to install a humidity sensor and a smoke sensor inside the charging pile to monitor the humidity and smoke concentration of the charging pile environment in real time. When the humidity or smoke concentration of the charging pile environment is higher than the preset alarm value, an environmental abnormality alarm instruction is output.

[0055] By installing a humidity sensor and a smoke sensor inside the charging pile, the environmental humidity and smoke concentration of the charging pile can be monitored in real time. When the environmental humidity or smoke concentration is detected to exceed the preset alarm value, the system outputs an environmental abnormality alarm instruction. This scheme increases the environmental monitoring function to ensure that the alarm can be issued in time when the environment around the charging pile is abnormal, thereby improving the safety and reliability of the charging pile.

[0056] The humidity sensor and the smoke sensor can use high-sensitivity sensors commonly available in the market. These sensors can quickly respond to changes in environmental humidity and smoke concentration in a short time. The humidity sensor can use a capacitive humidity sensor, which has high precision and stability and can work in a wide range of humidity. The smoke sensor can use a photoelectric smoke sensor, which detects the scattering or blocking of light by smoke particles to sense the smoke concentration. The output signal of the sensor can be converted into a digital signal by an analog-to-digital converter and input into the control system of the charging pile for processing.

[0057] Further, the control system can monitor and compare the output signal of the sensor in real time according to the preset alarm value. When the humidity or smoke concentration exceeds the preset alarm value, the control system triggers the alarm mechanism, such as an audible and visual alarm, to remind the maintenance personnel to check and handle the abnormal situation in time. As a preferred embodiment, the control system can also send the alarm information to the remote monitoring center through the network for remote monitoring and management.

[0058] Therefore, the application can monitor the environmental humidity and smoke concentration in real time and send an alarm signal in time in abnormal conditions by installing a humidity sensor and a smoke sensor inside the charging pile. Compared with the prior art, the application increases the environmental monitoring function, improves the safety and reliability of the charging pile, and effectively solves the problem that the charging pile cannot alarm in time when the environmental humidity or smoke concentration is abnormal.

[0059] Further, the application also provides a direct-current charging pile fault detection system, comprising: a charging pile data acquisition module, which acquires real-time charging data of a load connected to the charging pile; a load charging abnormality analysis module, which calls historical charging data of the load according to the type of the load connected to the charging pile, respectively calculates the difference between the load current value and the load voltage value in the real-time charging data and the load current mean value and the load voltage mean value in the historical charging data to obtain a current difference value and a voltage difference value, compares the current difference value and the voltage difference value with a preset threshold value, and outputs a charging abnormality instruction when the current difference value and the voltage difference value are greater than the preset threshold value; a charging mode judgment module, which judges the charging mode of the charging pile according to the load type and the real-time charging data through a charging mode judgment model; a charging pile trustworthiness judgment module, which constructs a trustworthiness prediction model, calculates a trustworthiness value through the trustworthiness prediction model according to the predicted value and the measured value of the working parameters of the charging pile, and outputs an abnormal condition according to the comparison result of the trustworthiness value and a preset trustworthiness threshold value.

[0060] The technical scheme solves the problems of data processing and abnormality identification in the fault detection of the direct-current charging pile through four modules of data acquisition, abnormality analysis, charging mode judgment and trustworthiness evaluation. Through the comparison between real-time data and historical data, combined with the judgment of the charging mode and the evaluation of the trustworthiness, the abnormal conditions of the charging pile and the load can be effectively detected and judged, and the safety and reliability of the charging process are ensured.

[0061] The charging pile data acquisition module is the basis of the whole system, which is responsible for acquiring the real-time charging data of the load connected to the charging pile, ensuring that the subsequent analysis has accurate real-time data as a basis. The load charging abnormality analysis module calculates the difference between the real-time charging data and the historical data by calling the historical charging data of the load, and compares it with the preset threshold value to judge whether there is an abnormal condition. The charging mode judgment module identifies the current charging mode through the charging mode judgment model according to the load type and the real-time charging data, so as to make more accurate abnormality judgment. The charging pile trustworthiness judgment module calculates the trustworthiness value according to the predicted value and the measured value of the working parameters through the construction of the trustworthiness prediction model, and outputs the abnormal condition to further confirm the reliability of the charging pile.

[0062] The innovation of the system lies in the accurate detection and judgment of charging pile faults through multi-dimensional data analysis and model prediction. Compared with the prior art, the application not only can timely find charging abnormalities, but also can further confirm the source of the abnormality through charging mode and trust degree evaluation, thereby improving the accuracy and reliability of fault detection.

[0063] Specifically, the charging pile data acquisition module can use high-precision current and voltage sensors to ensure the accuracy of data acquisition. The load charging abnormality analysis module can use big data analysis technology to call historical charging data for difference calculation and set reasonable preset thresholds through machine learning algorithms. The charging mode judgment module can use neural network or decision tree model to judge the charging mode based on load type and real-time data. The charging pile trust degree judgment module can use Bayesian network or fuzzy logic algorithm to build a trust degree prediction model, calculate the trust value and output the abnormal situation.

[0064] Further, the application also proposes that the direct current charging pile fault detection system is also configured with temperature sensors and humidity sensors to monitor the humidity and smoke concentration of the charging pile environment in real time. When the humidity or smoke concentration of the charging pile environment is higher than the preset alarm value, an environmental abnormality alarm instruction is output.

[0065] The technical scheme includes adding temperature sensors and humidity sensors in the direct current charging pile fault detection system to monitor the humidity and smoke concentration of the charging pile environment in real time. When the environmental humidity or smoke concentration is detected to be higher than the preset alarm value, the system outputs an environmental abnormality alarm instruction. These technical features can timely discover and alarm environmental abnormality by monitoring the environmental parameters of the charging pile in real time, thereby improving the safety and reliability of the charging pile.

[0066] The temperature sensors and humidity sensors can be implemented in various ways, for example, the temperature sensors can use thermocouples, thermistors, etc., and the humidity sensors can use capacitive humidity sensors, impedance humidity sensors, etc. These sensors can be installed inside or outside the charging pile to monitor environmental parameters in real time. The data of the sensors can be transmitted to the monitoring system through wireless or wired means, and the system can preset the alarm value. When the environmental parameter exceeds the alarm value, the system will automatically trigger an alarm.

[0067] Specifically, the temperature sensors and humidity sensors can be installed at key positions of the charging pile, such as battery compartment, charging interface, etc., to more accurately monitor the environmental conditions. The data of the sensors can be transmitted to the central control system in real time, and the central control system can make judgments according to the preset alarm value. When the humidity or smoke concentration is detected to be abnormal, the system will send an alarm signal to remind users or maintenance personnel to handle it in time.

[0068] The application can monitor the humidity and smoke concentration of the charging pile environment in real time by adding temperature sensors and humidity sensors in the direct current charging pile fault detection system, and timely alarm when the environmental parameters are abnormal, thereby improving the safety and reliability of the charging pile. Compared with the prior art, the application provides a more comprehensive environmental monitoring and alarm mechanism, which can more effectively prevent charging pile failures caused by environmental factors and ensure the safety of the charging process.

[0069] The basic features, principles and advantages of the application are shown and described above. It should be pointed out that the application is not limited by the above-mentioned embodiments, which are only part of the embodiments, and several improvements and supplements made without departing from the spirit and scope of the application are considered to be within the protection scope of the application.

Claims

1. A method for detecting faults of a direct current charging pile, characterized in that, The method comprises the following steps: a charging pile data collection step, collecting real-time charging data of a load connected to a charging pile; a load charging anomaly analysis step, calling historical charging data of the load according to the type of the load connected to the charging pile, respectively calculating the difference between the load current value and the load voltage value in the real-time charging data and the load current average value and the load voltage average value in the historical charging data to obtain a current difference value and a voltage difference value, and comparing the current difference value and the voltage difference value with a preset threshold value, when the current difference value and the voltage difference value are greater than the preset threshold value, outputting a charging anomaly instruction; a charging mode judgment step, judging the charging mode of the charging pile according to the load type and the real-time charging data through a charging mode judgment model; a charging pile trustworthiness judgment step, constructing a trustworthiness prediction model, calculating a trust value through the trustworthiness prediction model according to the predicted value and the measured value of the charging pile working parameters, and outputting an abnormal situation according to the comparison result of the trust value and the preset trust threshold value.

2. The DC charging pile fault detection method according to claim 1, characterized in that, The historical charging data acquisition comprises that when a vehicle is connected to a charging pile, the charging pile identifies the load type through the load resistance value, the load initial voltage response characteristic and the power factor angle difference, when the load type is a known type, the load current average value and the load voltage average value in the historical charging process of the load type are directly called as the historical charging data; when the load type is an unknown type, the closest known load type is matched according to the load resistance value combined with the real-time charging data, and the historical charging data of the known load type is weighted processed according to the real-time charging data of the current load to obtain a charging data as the historical charging data of the current load.

3. The DC charging pile fault detection method according to claim 1, characterized in that, The charging mode judgment step comprises that when the charging anomaly instruction is received, the charging mode of the current load is judged, the charging mode comprises a stable charging mode, a protection charging mode and a fast charging mode; when the current load is in the stable charging mode, the real-time charging data is in a stable stage, at this time, the load current value and the load voltage value remain unchanged; when the current load is in the protection charging mode, the real-time charging data is lower than the load voltage value and the load current value when the load is in the stable charging mode, and there is an amplitude mutation; when the current load is in the fast charging mode, the real-time charging data is higher than the load voltage value and the load current value when the load is in the stable charging mode, at this time, the power stability value of the load is reduced due to the temperature influence.

4. The DC charging pile fault detection method according to claim 1, characterized in that, The charging pile trustworthiness judgment step comprises that the predicted value of the charging pile working parameters is calculated through the charging mode and the real-time charging data of the charging pile respectively, and the trust value is calculated after the predicted value is weighted configured with the actually measured charging pile working parameter measured value.

5. The DC charging pile fault detection method according to claim 4, characterized in that, The predicted value calculation configuration comprises: ； Wherein, P is the prediction value, used for trust evaluation; is the charging mode weight adjustment function, M is the charging mode discriminant value, according to the amplitude of the charging mode, V t is the current load voltage measurement value, V avg is the average value of voltage in historical charging data, T is the current ambient temperature value, T ref is the preset standard ambient temperature, I t is the current load current measurement value, I avg is the average value of current in historical charging data, is the power stability value filtering function, △P is the difference between real-time power and stable power, μ p is the mean value of historical power stability value, σ p is the standard deviation of historical power stability value, t is the current time point, T is the length of historical time period for calculation.

6. The DC charging pile fault detection method according to claim 1, characterized in that, The charging pile trustworthiness judgment further comprises that a first trust threshold value and a second trust threshold value are set, when the trust value calculated through the trustworthiness prediction model is higher than the first trust threshold value, the judgment instruction output is that the charging pile is normal; when the trust value is lower than the first trust threshold value and higher than the second trust threshold value, the historical charging data of the current load is weighted processed to obtain new historical charging data according to the trust value; when the trust value is lower than the second trust threshold value, the charging pile anomaly instruction is output.

7. The DC charging pile fault detection method according to claim 1, characterized in that, The trust value calculation configuration comprises: ； Wherein, Tr is the trust value, indicating the trust degree of the charging pile, the higher the value, the smaller the possibility of abnormal charging pile, P(t) represents the prediction value at t moment, W(t) represents the measured value at t moment, represents the weight of the prediction value, represents the weight of the actual value.

8. The DC charging pile fault detection method according to claim 1, characterized in that, Further comprising, installing humidity sensor and smoke sensor inside the charging pile, monitoring the humidity and smoke concentration of the charging pile environment in real time, outputting environment abnormal alarm instruction when the humidity or smoke concentration of the charging pile environment is higher than the preset alarm value.

9. A direct current charging pile fault detection system, characterized in that, Comprise: The charging pile data acquisition module acquires the real-time charging data of the load connected to the charging pile; The load charging abnormality analysis module calls the historical charging data of the load according to the type of the load connected to the charging pile, respectively calculates the difference between the load current value and the load voltage value in the real-time charging data and the load current average value and the load voltage average value in the historical charging data to obtain the current difference value and the voltage difference value, compares the current difference value, the voltage difference value and the preset threshold value, and outputs the charging abnormality instruction when the current difference value and the voltage difference value are greater than the preset threshold value; The charging mode judgment module judges the charging mode of the charging pile according to the load type and the real-time charging data through the charging mode judgment model; The charging pile trust degree judgment module constructs a trust degree prediction model, calculates the trust value through the trust degree prediction model according to the predicted value and the measured value of the charging pile working parameter, and outputs the abnormal situation according to the comparison result of the trust value and the preset trust threshold.

10. The DC charging pile fault detection system of claim 9, wherein, The direct current charging pile fault detection system is also provided with temperature sensor and humidity sensor, which monitors the humidity and smoke concentration of the charging pile environment in real time, and outputs environment abnormal alarm instruction when the humidity or smoke concentration of the charging pile environment is higher than the preset alarm value.

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