Method and system for testing starting time sequence of charging pile through voltage simulator, program product and storage medium

Abstract

The invention provides a method and system for testing the starting time sequence of a charging pile through a voltage simulator, a program product and a storage medium, and relates to the technical field of charging piles. Firstly, a voltage curve determined according to complex voltage fluctuation conditions in an actual use scene is obtained, the voltage curve covers fluctuation of various amplitudes, frequencies and duration time, and therefore working parameters set subsequently can be in accordance with actual changes. Then working parameters are input into the voltage simulator, the voltage simulator outputs voltage signals changing according to the curve, and compared with the situation that a fixed voltage power supply can only provide limited fixed voltage levels, the method can simulate abundant and changeable actual voltage fluctuation. Therefore, the collected data obtained by monitoring the starting time sequence of the charging pile can reflect the performance of the charging pile in a real complex voltage environment, the problem that the test result lacks representativeness and comprehensiveness is avoided, the test result has higher reference value, and the starting characteristic of the charging pile can be accurately evaluated.

Description

Technical Field

[0001] The present application relates to the technical field of charging piles, and in particular to a method, system, program product and storage medium for testing the startup timing of a charging pile through a voltage simulator. Background Art

[0002] Electric vehicles have gradually become mainstream transportation tools due to their environmental protection and high efficiency, and the importance of charging pile facilities closely related to them has also become increasingly prominent. Charging pile startup timing test technology is the key to controlling whether the charging pile can start normally and safely in various complex environments. By accurately detecting key indicators such as the time parameters of each stage of the startup process, it can lay a solid foundation for the subsequent stable use of the charging pile.

[0003] At present, in the key technical field of charging pile startup timing test, on the one hand, some companies will use fixed voltage power supply to carry out testing work. During operation, based on the general classification of common voltage conditions in the past, several relatively fixed voltage levels are selected, such as setting common civilian standard voltage levels, several slightly higher or slightly lower typical voltage values, and connecting these fixed voltages to the charging pile in turn. Then, various conventional measuring instruments, such as voltmeters, ammeters, power meters, etc., are used to record the corresponding changes in key parameters such as voltage, current, power, etc. during the startup process of the charging pile, so as to analyze and determine whether its startup timing meets the requirements.

[0004] However, these related test methods have exposed many problems in practical applications. As for the use of fixed voltage power supply, since the voltage level it can provide is fixed and limited, in real life, the power grid environment where the charging pile is located is complex and changeable, and voltage fluctuations are constantly occurring due to many factors. For example, the difference in peak and valley power consumption in different periods of time, the start and stop of surrounding large-scale power-consuming equipment, etc. will cause dynamic changes in voltage, and the fixed voltage power supply cannot simulate these ever-changing actual voltage fluctuations. This means that the results obtained based on its test can only reflect the performance of the charging pile under those fixed voltages, and cannot fully reflect the starting characteristics of the charging pile in a real complex voltage environment, resulting in the lack of sufficient representativeness and comprehensiveness of the test results. Summary of the invention

[0005] The present application provides a method, system, program product and storage medium for testing the startup timing of a charging pile through a voltage simulator, which is used to improve the richness of voltage fluctuations. The collected data obtained by monitoring the startup timing of the charging pile can reflect its performance in a real complex voltage environment, avoiding the problem of lack of representativeness and comprehensiveness of the test results.

[0006] In the first aspect, the present application provides a method for testing the startup timing of a charging pile through a voltage simulator, including: obtaining a voltage curve, the voltage curve is determined according to the voltage fluctuation conditions occurring in the simulated actual usage scenario, and the voltage curve includes voltage fluctuation conditions of various amplitudes, frequencies, and durations; setting working parameters according to the voltage curve; inputting working parameters into the voltage simulator; causing the voltage simulator to send a simulated voltage signal to the connected charging pile, and the voltage signal changes according to the voltage curve; monitoring the startup timing of the charging pile to obtain collected data; judging whether there is an abnormality in the collected data according to judgment rules; the judgment rules include whether the electrical parameters reach the set threshold for normal operation and whether the startup timing is within a reasonable time range.

[0007] By adopting the above technical solution, we first obtain a voltage curve determined according to the complex voltage fluctuations in the actual use scenario, which covers fluctuations of various amplitudes, frequencies and durations, so that the subsequent working parameters can fit the actual changes. Then, we input the working parameters into the voltage simulator, and let it output a voltage signal that changes according to this curve. Compared with the situation where a fixed voltage power supply can only provide a limited fixed voltage level, this method can simulate rich and varied actual voltage fluctuations. In this way, the collected data obtained by monitoring the startup timing of the charging pile can reflect its performance in a real complex voltage environment, avoid the problem of lack of representativeness and comprehensiveness of the test results, make the test results more valuable for reference, and accurately evaluate the startup characteristics of the charging pile.

[0008] In combination with some embodiments of the first aspect, in some embodiments, the step of monitoring the startup timing of the charging pile and obtaining collected data specifically includes: inputting the collected data collected within a time period greater than a preset time threshold into a prediction model to obtain predicted values ​​and corresponding confidence intervals at multiple sampling times in the future; based on the predicted values ​​and confidence intervals, using a fuzzy logic algorithm to determine whether the sampling rate needs to be adjusted; adjusting the sampling time according to the sampling rate; and adjusting the amount of collected data obtained and the corresponding acquisition time according to the sampling time and the sampling rate.

[0009] By adopting the above technical solution, when monitoring the startup sequence of the charging pile to obtain collected data, a prediction model combined with a fuzzy logic algorithm is introduced to determine and adjust the sampling rate. When encountering a rapidly changing voltage fluctuation moment and the existing sampling frequency is insufficient, the prediction model is used to estimate the future sampling moment situation, and then the fuzzy logic algorithm is used to flexibly adjust the sampling rate based on the predicted value and confidence interval, and then adjust the sampling time and the acquisition amount and acquisition time of the collected data, effectively avoiding the omission of key data points, ensuring that the relevant information on the impact of voltage fluctuations on the charging pile startup can be fully obtained, and improving the accuracy and comprehensiveness of the charging pile startup performance evaluation.

[0010] In conjunction with some embodiments of the first aspect, in some embodiments, the step of using a fuzzy logic algorithm to determine whether the sampling rate needs to be adjusted according to the predicted value and the confidence interval specifically includes: In the formula, is the sampling rate adjustment degree, For rules, For rules The total rule activation strength, Typical values ​​corresponding to different degrees of adjustment of sampling rate requirements, To adjust the sampling rate accordingly, To adjust the threshold, , when it is greater than 0, the sampling rate needs to be adjusted. The degree of sampling rate adjustment is ,exist , when it is not greater than 0, there is no need to adjust the sampling rate; In the formula, For rules The total rule activation strength, is the result of the first rule, is the result of the second rule, As a result of the third rule; , , as a parameter.

[0011] By adopting the above technical solution, along with The change shows a nonlinear trend. When it approaches 0, Close to 1, the value of the nonlinear adjustment term is close to ,when Increase, for example, when When it increases to 1, Close to 0.368, the value of the adjustment item changes significantly, which in turn affects its influence in the overall weighted calculation. In terms of the adjustment effect on the rule weight, by combining the nonlinear adjustment item with as well as , respectively, so that different rules are based on the size of their activation strength in the final defuzzification calculation process The weights are adjusted nonlinearly.

[0012] In combination with some embodiments of the first aspect, in some embodiments, the first rule is that when the confidence interval is in the first interval, the change in the predicted value is divided by the first adjustment amount; the second rule is that when the confidence interval is in the second interval, the change in the predicted value is divided by the second adjustment amount; the third rule is that when the confidence interval is in the third interval, the change in the predicted value is divided by the third adjustment amount; the first interval is greater than the second interval, which is greater than the third interval; the first adjustment amount is greater than the second adjustment amount, which is greater than the third adjustment amount.

[0013] By adopting the above technical solution, the first rule, the second rule and the third rule play a role according to different intervals of the confidence interval and the corresponding adjustment amount. When the confidence interval is in the larger first interval, it corresponds to a larger first adjustment amount, which means that when the data reliability is relatively low (the confidence interval is large), it is more sensitive to the change of the predicted value, and it is necessary to adjust the sampling rate more actively to ensure that the possible key data changes can be captured in time to avoid missing important information due to slightly low data reliability. As the confidence interval gradually decreases to the second interval, the adjustment amount becomes the second adjustment amount, which is smaller than the first adjustment amount. At this time, due to the improvement of data reliability, although the sampling rate still needs to be adjusted according to the change of the predicted value, the adjustment range can be appropriately slowed down, which reflects the differentiated processing of data with different reliability, which not only ensures timely response to data changes, but also avoids excessive adjustment. When the confidence interval is in the smallest third interval, it corresponds to a smaller third adjustment amount. This is because when the data reliability is high, the change of the predicted value is more valuable for reference, and only a small adjustment of the sampling rate is required to meet the accuracy requirements of data collection, while also reducing unnecessary calculations and resource consumption. At various data reliability levels, the sampling rate can be adjusted in the most appropriate way to accurately collect data reflecting the startup status of the charging pile.

[0014] In combination with some embodiments of the first aspect, in some embodiments, the step of setting working parameters according to the voltage curve specifically includes: partitioning the voltage curve according to the minimum voltage amplitude step, minimum frequency adjustment step and time step that can be adjusted by the voltage simulator, and screening out the target area that is less than the minimum voltage amplitude step, minimum frequency adjustment step or time step; determining the loss amount according to the change in amplitude, frequency or duration in the target area and the corresponding minimum voltage amplitude step, minimum frequency adjustment step or time step; adjusting the amplitude, frequency and duration of subsequent areas of the target area according to the loss amount to reduce the sum of the loss amounts.

[0015] By adopting the above technical solution, the voltage curve is partitioned according to the minimum voltage amplitude step, minimum frequency adjustment step and time step of the voltage simulator, and the loss amount is determined after accurately finding the target area, and then the relevant parameters of the subsequent areas are adjusted accordingly to reduce the sum of the loss amount. In this way, the disadvantage that the simulator step size is limited to only approximate values ​​when converting working parameters is overcome, so that the simulated voltage signal can be closer to the expected signal of the original voltage curve, reducing the deviation between the two, and restoring the actual voltage fluctuation to the greatest extent, thereby improving the accuracy of the test, making the judgment of the charging pile startup status based on this test more reliable, and avoiding wrong judgments caused by parameter deviations.

[0016] In combination with some embodiments of the first aspect, in some embodiments, working parameters are set according to the voltage curve; working parameters are input into the voltage simulator; and the voltage simulator is made to send a simulated voltage signal to the connected charging pile, and the voltage signal changes according to the voltage curve. The steps specifically include: inputting the circuit structure of the charging pile into the analog circuit model, dividing the voltage curve into voltage segments, wherein the voltage segments correspond to amplitude, frequency and duration; creating corresponding voltage source modules according to the voltage segments; and arranging the circuit structure of the voltage source module in chronological order in the analog circuit model.

[0017] By adopting the above technical solution, the circuit structure of the charging pile is input into the simulation circuit model, which enables the software to build a virtual model that is highly consistent with the actual charging pile circuit, subdividing the voltage curve into voltage segments, each segment corresponds to a specific amplitude, frequency and duration, and creating corresponding voltage source modules based on these voltage segments. The software can accurately control the parameters of each module to ensure the accuracy and stability of the simulated voltage signal. Finally, in the simulation circuit model, the voltage source module is connected to the circuit structure in chronological order. The software can strictly perform the simulation process according to the actual time logic and circuit connection relationship, avoiding errors and uncertainties that may be caused by hardware connection problems in the actual simulator. Through this software simulation method, the working state of the charging pile under various voltage fluctuations can be simulated in a virtual environment with high fidelity, without the need to build a complex actual test environment, which greatly reduces the test cost and time cost.

[0018] In combination with some embodiments of the first aspect, in some embodiments, operating parameters are input into the voltage simulator; before the step of causing the voltage simulator to send a simulated voltage signal to the connected charging pile, and the voltage signal changes according to the voltage curve, the method also includes: obtaining load parameters, the load parameters are determined by the load appearing in the actual usage scenario simulated; adjusting the load simulator according to the load parameters so that the output load of the load simulator is the same as the load parameters; activating the connection channel between the load simulator and the charging pile.

[0019] By adopting the above technical solution, before sending the simulated voltage signal to the charging pile, the load parameters determined by the simulated actual scene load are first obtained, and the load simulator is adjusted accordingly and the connection channel between it and the charging pile is activated. This allows the charging pile to work in a simulated actual load environment while receiving the simulated voltage signal, avoiding the situation where only voltage simulation is considered and the load impact is ignored, making the entire test environment closer to the actual usage scenario.

[0020] In a second aspect, the present application provides a system for testing the startup timing of a charging pile through a voltage simulator, and the system for testing the startup timing of a charging pile through a voltage simulator includes: one or more processors and a memory; the memory is coupled to the one or more processors, and the memory is used to store computer program code, and the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the system for testing the startup timing of a charging pile through a voltage simulator to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, the present application provides a computer program product comprising instructions. When the computer program product is run on a charging pile startup timing test system through a voltage simulator, the charging pile startup timing test system is executed through a voltage simulator as described in the first aspect and any possible implementation method of the first aspect.

[0022] In a fourth aspect, the present application provides a computer-readable storage medium comprising instructions. When the instructions are executed on a charging pile startup timing test system through a voltage simulator, the charging pile startup timing test system is executed through a voltage simulator as described in the first aspect and any possible implementation method of the first aspect.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. First, obtain a voltage curve determined based on the complex voltage fluctuations in the actual usage scenario, which covers fluctuations of various amplitudes, frequencies and durations, so that the subsequent working parameters can fit the actual changes. Then input the working parameters to the voltage simulator to let it output a voltage signal that changes according to this curve. Compared with the situation where a fixed voltage power supply can only provide a limited fixed voltage level, this method can simulate rich and varied actual voltage fluctuations. In this way, the collected data obtained by monitoring the startup timing of the charging pile can reflect its performance in a real complex voltage environment, avoid the problem of lack of representativeness and comprehensiveness of the test results, make the test results more valuable for reference, and accurately evaluate the startup characteristics of the charging pile.

[0024] 2. When monitoring the startup sequence of charging piles to obtain collected data, introduce a prediction model combined with a fuzzy logic algorithm to determine and adjust the sampling rate. When encountering a rapidly changing voltage fluctuation moment and the existing sampling frequency is insufficient, the prediction model is used to estimate the future sampling moment, and then the fuzzy logic algorithm is used to flexibly adjust the sampling rate based on the predicted value and confidence interval, and then adjust the sampling time and the amount and time of collected data, effectively avoiding the omission of key data points, ensuring that the relevant information on the impact of voltage fluctuations on the startup of charging piles can be fully obtained, and improving the accuracy and comprehensiveness of the evaluation of the charging pile startup performance.

[0025] 3. Divide the voltage curve according to the minimum voltage amplitude step, minimum frequency adjustment step and time step of the voltage simulator, accurately find the target area and determine the loss, and then adjust the relevant parameters of the subsequent areas accordingly to reduce the sum of the losses. This overcomes the disadvantage that the simulator step size is limited to approximate values ​​when converting working parameters, allowing the simulated voltage signal to be closer to the expected signal of the original voltage curve, reducing the deviation between the two, and restoring the actual voltage fluctuation to the greatest extent, thereby improving the accuracy of the test, making the judgment of the charging pile startup status based on this test more reliable, and avoiding misjudgment due to parameter deviation. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a method for testing the startup timing of a charging pile by a voltage simulator in an embodiment of the present application; Figure 2 This is another flow chart of a method for testing the startup timing of a charging pile by a voltage simulator in an embodiment of the present application; Figure 3 This is another flow chart of a method for testing the startup timing of a charging pile by a voltage simulator in an embodiment of the present application; Figure 4 This is another flow chart of a method for testing the startup timing of a charging pile by a voltage simulator in an embodiment of the present application; Figure 5 It is an exemplary hardware structure diagram of a system for testing the startup timing of a charging pile through a voltage simulator in an embodiment of the present application. DETAILED DESCRIPTION

[0027] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to and includes any or all combinations of one or more listed items.

[0028] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0029] See also Figure 1 , Figure 1 It is a flow chart of a method for testing the startup timing of a charging pile by a voltage simulator in an embodiment of the present application; S101, obtaining a voltage curve, where the voltage curve is determined according to voltage fluctuations occurring in a simulated actual usage scenario, and the voltage curve includes voltage fluctuations of various amplitudes, frequencies, and durations; The voltage curve is a function curve that describes the change of voltage over time. It is a mathematical expression with time as the horizontal axis and voltage as the vertical axis, which is used to express the voltage amplitude at different time points. It covers the dynamic information of voltage, including voltage fluctuations of different amplitudes, frequencies and durations, and is the form of expression desired by the user.

[0030] S102, setting working parameters according to the voltage curve; The working parameters refer to a series of internal parameters that the voltage simulator needs to accurately simulate the voltage curve, which are used to represent the working status and performance indicators of the voltage simulator. These parameters are set according to the specific characteristics of the voltage curve, including but not limited to voltage amplitude, frequency, phase, duty cycle (for pulse signals), etc. They determine how the voltage simulator accurately outputs the required voltage signal to reproduce the voltage fluctuation described by the voltage curve.

[0031] In some embodiments, because the voltage simulator cannot directly process the voltage curve, it converts the curve information into a series of control parameters based on its own working principle and hardware performance. For example, if the voltage curve contains a voltage fluctuation with an amplitude of 300V and a frequency of 40Hz, then this information needs to be converted into acceptable working parameters for the voltage simulator, which may involve the scale of the simulator's voltage adjustment knob, the setting of the frequency adjustment module, etc., to ensure that the analog voltage signal it outputs can reproduce the voltage change represented by the voltage curve as accurately as possible. This process needs to fully consider the performance indicators of the voltage simulator, such as the adjustable minimum voltage amplitude step, the minimum frequency adjustment step, etc., to avoid situations where accurate simulation cannot be achieved due to the performance limitations of the simulator.

[0032] In some specific embodiments, the voltage curve is discretized and divided into multiple small time intervals. Based on the voltage amplitude, frequency and other information within each time interval, the parameter manual of the voltage simulator is searched to find the closest adjustable parameters. Then, based on the performance indicators of the voltage simulator, the voltage curve parameters that cannot be accurately matched are approximated. For example, when the required amplitude is between two adjustable gears, the appropriate gear is selected based on the principle of minimum error. Finally, these selected parameters are recorded and organized into an input format according to the parameter input requirements of the voltage simulator, which are not limited here.

[0033] In some embodiments, steps S106 to S108 may be performed before step S102, and step S103 may also be performed; S106, obtaining load parameters, where the load parameters are determined by the load occurring in the simulated actual usage scenario; Among them, the load parameters represent the quantitative description of the various electrical characteristics of the load connected to the charging pile, which refers to the physical quantities used to characterize the load in different states, including but not limited to the load resistance value (used to describe the load's resistance to current), inductance value (reflecting the load's ability to store magnetic field energy), capacitance value (reflecting the load's ability to store electric field energy), active power (indicating the actual power consumed by the load), reactive power (indicating the rate of energy exchange between the load and the power supply) and power factor (reflecting the load's efficiency in utilizing the power supply energy), etc.

[0034] In some embodiments, this step is usually performed during the test preparation stage of the charging pile, especially when considering simulating the actual working environment of the charging pile. The purpose is to accurately simulate the load conditions faced by the charging pile in real use, because different loads will have different effects on the performance of the charging pile, including the impact on its output voltage, current and power.

[0035] S107, adjusting the load simulator according to the load parameter so that the output load of the load simulator is the same as the load parameter; In some embodiments, after the required load parameters are determined, the load simulator needs to be adjusted so that it can accurately simulate the corresponding load conditions. This is to ensure that when testing the charging pile, the charging pile can be placed in a load environment similar to actual use, avoiding only considering voltage fluctuations and ignoring the impact of the load on the performance of the charging pile. For example, if the load parameters show that a load with high resistance and low power factor needs to be simulated, the load simulator needs to adjust its internal circuit or software parameters so that its output has such characteristics. This allows the charging pile to exhibit its actual working state under this load during the test, such as a drop in output voltage, a decrease in current, etc., thereby more comprehensively evaluating the performance of the charging pile under different load conditions.

[0036] S108: Activate the connection channel between the load simulator and the charging pile.

[0037] In some embodiments, after the load simulator has been adjusted according to the load parameters, it is necessary to activate the connection channel between it and the charging pile so that the entire test system forms a complete closed loop for subsequent testing. For example, in a laboratory test environment, the load simulator and the charging pile may be connected by cables and plugs. After adjusting the parameters of the load simulator, it is necessary to insert the cable plug into the output socket of the charging pile, or in a software simulation environment, it is necessary to turn on the connection switch in the software or enable the corresponding data link so that the two can effectively interact with each other in terms of energy and information, so that the charging pile can feel the simulated load conditions, and then observe its performance under the load, such as the stability of the output voltage, the magnitude of the current, and the power output capacity.

[0038] It can be seen that before sending the simulated voltage signal to the charging pile, the load parameters determined by simulating the actual scene load are obtained first, and the load simulator is adjusted accordingly and the connection channel between it and the charging pile is activated. This allows the charging pile to work in a simulated actual load environment while receiving the simulated voltage signal, avoiding the situation where only voltage simulation is considered and the load impact is ignored, making the entire test environment closer to the actual usage scenario.

[0039] S103, inputting working parameters into the voltage simulator; causing the voltage simulator to send a simulated voltage signal to the connected charging pile, and the voltage signal changes according to the voltage curve; Among them, the simulated voltage signal refers to the voltage output generated by the voltage simulator that is similar to the actual voltage fluctuation, which is used to simulate the voltage conditions in the actual scene. Its amplitude, frequency, duration and other characteristics are determined according to the working parameters and the voltage curve.

[0040] In some embodiments, after the setting of the working parameters is completed, the set working parameters are input into the voltage simulator, and the voltage simulator is started to generate a simulated voltage signal and send it to the connected charging pile. The purpose of this step is to allow the charging pile to operate in a simulated voltage environment, just as if it were in an actual grid voltage fluctuation environment. Through precise working parameter settings, the voltage simulator can output voltages of different amplitudes, frequencies, and durations at different times according to the voltage curve, so that the charging pile startup process is affected by the simulated voltage fluctuations, providing a complete voltage change environment for the charging pile startup, thereby testing the charging pile startup performance under different voltage conditions.

[0041] S104, monitoring the startup timing of the charging pile to obtain collected data; Among them, the startup sequence refers to the time sequence from the time the charging pile receives the startup command to the time when each key module and circuit inside it completes the corresponding actions and enters a stable operating state. It is used to represent the time sequence and time intervals during the startup process of the charging pile, including but not limited to the time points and durations of each stage from when the power is turned on to when the control circuit starts working, the power conversion circuit starts running, and the output voltage reaches a stable value.

[0042] In some embodiments, when the voltage simulator starts to send a simulated voltage signal to the charging pile, the charging pile startup process is monitored throughout by arranging sensors and measuring devices at different key positions of the charging pile, such as connecting voltage sensors and current sensors at the input and output ends, and installing temperature sensors on key power devices. The purpose is to obtain various performance data of the charging pile in a simulated voltage environment, which will provide a basis for subsequent evaluation and analysis.

[0043] S105. Determine whether the collected data is abnormal according to the judgment rules; the judgment rules include whether the electrical parameters reach the set threshold value for normal operation and whether the startup sequence is within a reasonable time range.

[0044] In some embodiments, the collected data is analyzed and evaluated through pre-set judgment rules to determine whether the startup process of the charging pile is normal. By comparing the collected data with the set threshold and time range, it can be determined whether the charging pile can start and operate normally under the simulated voltage environment. For example, if the collected input voltage exceeds the normal voltage range at a certain moment, or the time from startup to output voltage stabilization is too long, it may indicate that there is a problem with the charging pile. These judgment rules can be based on industry standards, manufacturer's design requirements or previous testing experience, and are intended to ensure that the charging pile can operate safely, reliably and efficiently in actual use.

[0045] It can be seen that first, a voltage curve is obtained based on the complex voltage fluctuations in the actual usage scenario, which covers fluctuations of various amplitudes, frequencies and durations, so that the subsequent working parameters can fit the actual changes. Then the working parameters are input to the voltage simulator to let it output a voltage signal that changes according to this curve. Compared with the situation where a fixed voltage power supply can only provide a limited fixed voltage level, this method can simulate rich and varied actual voltage fluctuations. In this way, the collected data obtained by monitoring the startup timing of the charging pile can reflect its performance in a real complex voltage environment, avoid the problem of lack of representativeness and comprehensiveness of the test results, make the test results more valuable for reference, and accurately evaluate the startup characteristics of the charging pile.

[0046] In actual use, when using a data acquisition device to collect data on voltage fluctuations during the startup of a charging pile, although the sampling rate of the device has been set to a level that meets general requirements, when encountering rapidly changing voltage fluctuations, especially during critical periods when the voltage rises or falls sharply, the existing sampling frequency is still not high enough. This will result in some important data points not being collected at these critical moments, resulting in data omissions. Since this information cannot be fully obtained, it will be difficult to accurately grasp the actual impact of voltage fluctuations on the startup of the charging pile, which may lead to inaccurate or incomplete evaluation of the charging pile startup performance.

[0047] See also Figure 2 , Figure 2 This is another flow chart of a method for testing the startup timing of a charging pile by a voltage simulator in an embodiment of the present application; Therefore, step S104 specifically includes: S201, inputting the collected data collected within a time period greater than a preset time threshold into a prediction model to obtain predicted values ​​at multiple future sampling moments and corresponding confidence intervals; Among them, the prediction model is a mathematical or statistical model used to represent a tool for predicting future data based on existing data. It can be a machine learning model trained based on historical data (such as a time series prediction model), or a theoretical model built based on physical principles. Its purpose is to predict the operating status of the charging pile in the future based on the existing collected data. The predicted value refers to the estimated value of the relevant electrical parameters of the charging pile at the future sampling moment based on the input collected data by the prediction model, which is used to represent the possible operating conditions of the charging pile at the future moment. The confidence interval refers to the possible range of the predicted value at a certain confidence level. It reflects the uncertainty of the prediction. A wider confidence interval means that the uncertainty of the prediction is greater, and a narrower confidence interval means that the prediction is more accurate.

[0048] In some embodiments, the data collection is performed after the charging pile has been started for a period of time. When the amount of data collected reaches a certain level (greater than the preset time threshold), this part of the data is input into the prediction model to predict the voltage, current and other parameters at multiple sampling moments in the future, and the corresponding confidence interval is given to provide a basis for the subsequent adjustment of the sampling strategy. This helps to discover possible abnormal situations in advance, such as predicting that there will be a large fluctuation in voltage at a certain moment in the future, and the reliability of this prediction can be judged by the confidence interval.

[0049] The training process of the prediction model is: First, extensive data collection on the startup process of charging piles in actual usage scenarios should be carried out. These scenarios should cover different environmental conditions, such as different seasons (summer, winter, etc., because temperature affects grid load and voltage fluctuations), different time periods (peak hours during the day, low hours at night), different load conditions (different numbers of electric vehicles connected to charging piles of different powers), and different geographical locations (commercial areas, residential areas, industrial areas, etc., because grid load characteristics vary in different areas).

[0050] Clean the collected raw data to remove obviously erroneous data points, which may come from sensor failure, communication errors or abnormal external interference. You can filter out abnormal values ​​by setting a reasonable data range. For example, for input voltage, if the data point exceeds the normal grid voltage range (such as exceeding ±20% of the rated voltage), it can be regarded as abnormal and removed.

[0051] At the same time, check the integrity of the data. For missing data points, interpolation methods (such as linear interpolation or cubic spline interpolation) can be used to supplement them to ensure the continuity of the data.

[0052] Useful features are extracted from the raw data. Time is taken as an important feature. Time can be converted into different forms, such as hours, minutes, seconds, or it can be expressed as a relative time relative to the start time, so that the model can better learn time series patterns.

[0053] Perform feature conversion on electrical parameters, for example, convert voltage and current data into amplitude, frequency, phase, etc., and calculate derivative features such as power factor, active power, reactive power, etc. These features can better describe the electrical state of the charging pile during the startup process.

[0054] It should be noted that among these data sequences, the earlier data are used as training data, and the later data are used as meaningful label data.

[0055] Use the ARIMA (Autoregressive Integrated Moving Average) model. The ARIMA model has advantages in processing time series data. It can consider the autoregressive (AR) part of the data, that is, the correlation between the current data point and the past data points, the moving average (MA) part, that is, considering the impact of past forecast errors on the current forecast, and the difference (I) part, which is used to eliminate the trend and seasonality of the data.

[0056] Then, by observing the autocorrelation function (ACF) and partial autocorrelation function (PACF) graphs, the range of the parameters p (autoregressive order), d (difference order), and q (moving average order) of the ARIMA model is preliminarily determined. Next, grid search (GridSearch) or other optimization algorithms (such as Bayesian optimization) are used to find the optimal (p, d, q) combination within the possible parameter range to minimize the prediction error of the model on the training set.

[0057] During the training process, the data of the training set is input into the ARIMA model. The model will estimate the parameters based on the set parameters and training data to minimize the prediction error (such as mean square error MSE).

[0058] S202, using a fuzzy logic algorithm to determine whether the sampling rate needs to be adjusted according to the predicted value and the confidence interval; Among them, the fuzzy logic algorithm is a computational method for processing fuzzy and uncertain information. It refers to converting the precise input values ​​(such as predicted values ​​and confidence intervals) into fuzzy sets, using fuzzy rules and reasoning mechanisms to quantify and process uncertainties, and finally obtain a fuzzy decision result. In this scenario, it is used to comprehensively judge whether the sampling rate needs to be adjusted based on the predicted values ​​and confidence intervals to adapt to possible voltage fluctuations and changes in the operating status of the charging pile in the future. The sampling rate refers to the frequency of data collection of the electrical parameters of the charging pile within a certain period of time. It is used to indicate the density of data collection. A higher sampling rate means more data points collected per unit time, which can reflect the operating status of the charging pile in more detail, but it will also bring more data volume and computing costs.

[0059] In some embodiments, after obtaining the predicted value and confidence interval, it is necessary to decide whether the current sampling rate needs to be adjusted based on this information. Because different prediction situations may require different sampling rates to ensure the integrity and validity of the data. For example, if it is predicted that the voltage of the charging pile will fluctuate frequently and violently in the future, and the confidence interval is large (indicating that the prediction is less reliable), it may be necessary to increase the sampling rate in order to more accurately capture these changes; and if the prediction results show that the future voltage is relatively stable and the confidence interval is small (indicating that the prediction is reliable), the sampling rate can be appropriately reduced to reduce the amount of data and computing resources. Consumption. Through the fuzzy logic algorithm, taking into account the size of the predicted value, the trend of change, and the width of the confidence interval, it is possible to make a more intelligent decision to adjust the sampling rate and avoid data loss or resource waste due to unreasonable sampling rates.

[0060] In some embodiments, the input variables of the fuzzy logic algorithm are first determined, and the predicted value and the width of the confidence interval are taken as input; then fuzzy rules are established, such as "if the predicted value changes little and the confidence interval is narrow, the sampling rate should be greatly increased" and "if the predicted value changes greatly and the confidence interval is wide, the sampling rate should be reduced", etc.; finally, the input variables are fuzzified, and through the fuzzy reasoning and defuzzification process, it is determined whether the sampling rate needs to be adjusted and the extent of the adjustment, which is not limited here.

[0061] In some embodiments, the function of step S202 is: In the formula, is the sampling rate adjustment degree, For rules, For rules The total rule activation strength, Typical values ​​corresponding to different degrees of adjustment of sampling rate requirements, To adjust the sampling rate accordingly, To adjust the threshold, , when it is greater than 0, the sampling rate needs to be adjusted. The degree of sampling rate adjustment is ,exist , when it is not greater than 0, there is no need to adjust the sampling rate; In the formula, For rules The total rule activation strength, is the result of the first rule, is the result of the second rule, As a result of the third rule; , , as a parameter.

[0062] visible, along with The change shows a nonlinear trend. When it approaches 0, Close to 1, the value of the nonlinear adjustment term is close to ,when Increase, for example, when When it increases to 1, Close to 0.368, the value of the adjustment item changes significantly, which in turn affects its influence in the overall weighted calculation. In terms of the adjustment effect on the rule weight, by combining the nonlinear adjustment item with as well as , respectively, so that different rules are based on the size of their activation strength in the final defuzzification calculation process The weights are adjusted nonlinearly.

[0063] Among them, the first rule is that when the confidence interval is in the first interval, the change in the predicted value is divided by the first adjustment amount; the second rule is that when the confidence interval is in the second interval, the change in the predicted value is divided by the second adjustment amount; the third rule is that when the confidence interval is in the third interval, the change in the predicted value is divided by the third adjustment amount; the first interval is greater than the second interval, greater than the third interval; the first adjustment amount is greater than the second adjustment amount, greater than the third adjustment amount.

[0064] It can be seen that the first rule, the second rule and the third rule work according to different intervals of the confidence interval and the corresponding adjustment amount. When the confidence interval is in the larger first interval, it corresponds to a larger first adjustment amount, which means that when the data reliability is relatively low (the confidence interval is large), it is more sensitive to the change of the predicted value, and it is necessary to adjust the sampling rate more actively to ensure that the possible key data changes can be captured in time to avoid missing important information due to slightly low data reliability. As the confidence interval gradually decreases to the second interval, the adjustment amount becomes the second adjustment amount, which is smaller than the first adjustment amount. At this time, due to the improvement of data reliability, although the sampling rate still needs to be adjusted according to the change of the predicted value, the adjustment range can be appropriately slowed down, which reflects the differentiated processing of data with different reliability, which not only ensures the timely response to data changes, but also avoids excessive adjustment. When the confidence interval is in the smallest third interval, it corresponds to a smaller third adjustment amount. This is because when the data reliability is high, the change of the predicted value is more valuable for reference, and only a small adjustment of the sampling rate is required to meet the accuracy requirements of data collection, while also reducing unnecessary calculations and resource consumption. At various data reliability levels, the sampling rate can be adjusted in the most appropriate way to accurately collect data reflecting the startup status of the charging pile.

[0065] S203, adjusting the sampling time according to the sampling rate; The sampling time refers to the time interval between two adjacent samples during the data collection process, and refers to the time length between two time points of collecting the electrical parameters of the charging pile. It is closely related to the sampling rate. The sampling time can be directly affected by adjusting the sampling rate. There is generally an inverse relationship between the two, that is, the higher the sampling rate, the shorter the sampling time, and vice versa.

[0066] In some embodiments, when it is determined that the sampling rate needs to be adjusted according to step S202, the sampling time should be adjusted accordingly to ensure that the subsequently collected data can better reflect the operating status of the charging pile. For example, if it is determined that the sampling rate needs to be increased, the sampling time will be shortened accordingly, so that data can be collected more intensively and more subtle changes in parameters such as voltage and current can be captured. Especially for some key startup stages or time periods where abnormalities may occur, shortening the sampling time can provide more detailed data; if the sampling rate is reduced, the sampling time will become longer, which can reduce the amount of data and storage and processing costs to a certain extent, while ensuring that the basic information of the data is not affected.

[0067] S204: Adjust the acquisition amount of collected data and the corresponding acquisition time according to the sampling time and the sampling rate.

[0068] It can be seen that when monitoring the startup sequence of charging piles to obtain collected data, the prediction model is introduced in combination with the fuzzy logic algorithm to determine and adjust the sampling rate. When encountering a rapidly changing voltage fluctuation moment and the existing sampling frequency is insufficient, the prediction model is used to estimate the future sampling moment, and then the fuzzy logic algorithm is used to flexibly adjust the sampling rate based on the predicted value and confidence interval, and then adjust the sampling time and the amount and time of collected data, effectively avoiding the omission of key data points, ensuring that the relevant information on the impact of voltage fluctuations on the startup of charging piles can be fully obtained, and improving the accuracy and comprehensiveness of the evaluation of the charging pile startup performance.

[0069] In actual use, the voltage curve is determined according to actual needs. It contains voltage fluctuation information of various amplitudes, frequencies and durations, aiming to simulate the complex and changeable voltage changes in the real environment as accurately as possible. However, when dealing with the more subtle voltage fluctuation amplitudes in the voltage curve, due to the limitation of the minimum adjustable voltage amplitude step of the voltage simulator, when converting it into an operating parameter, its value cannot be set accurately, and only an approximate value close to it can be taken. This approximate value operation will cause the simulated voltage signal finally output by the voltage simulator to deviate from the voltage signal expected by the original voltage curve, thereby affecting the accuracy of the entire test.

[0070] Please refer to Figure 3 , Figure 3 This is another flow chart of a method for testing the startup timing of a charging pile by a voltage simulator in an embodiment of the present application; Therefore, in some embodiments, step S102 specifically includes: S301, partitioning the voltage curve according to the minimum voltage amplitude step, the minimum frequency adjustment step and the time step that can be adjusted by the voltage simulator, and screening out a target area that is smaller than the minimum voltage amplitude step, the minimum frequency adjustment step or the time step; Among them, the minimum voltage amplitude step refers to the minimum increment of the voltage amplitude that the voltage simulator can accurately adjust, and refers to the finest adjustment unit that the simulator can achieve when adjusting the output voltage amplitude, which is used to indicate the resolution of the voltage amplitude adjustment. The minimum frequency adjustment step refers to the minimum increment of the voltage frequency that the voltage simulator can accurately adjust, and refers to the minimum precise adjustment amount when changing the output voltage frequency, which is used to reflect the fineness of the frequency adjustment. The time step refers to the minimum interval on the time axis of the voltage curve, and refers to the minimum time unit used when describing the voltage change, which is used to indicate the time resolution. Partitioning refers to dividing the voltage curve into different parts according to certain rules, and refers to dividing the voltage curve into multiple continuous sub-areas, so as to analyze and process different parts of the voltage curve in more detail. The target area refers to those areas in the voltage curve where the change in voltage amplitude, frequency or duration is less than the corresponding minimum step of the voltage simulator, which is used to indicate the part of the voltage curve that may cause precision loss due to the limitation of the simulator resolution.

[0071] In some embodiments, due to the performance limitations of the voltage simulator, its adjustable minimum step size may not be able to accurately reproduce all the details in the voltage curve, so the voltage curve needs to be partitioned. For example, for a complex voltage curve, it may contain voltage fluctuations of various amplitudes, frequencies, and durations, and the voltage simulator may not be able to accurately reproduce all subtle voltage changes. By considering the minimum voltage amplitude step size, minimum frequency adjustment step size, and time step size of the voltage simulator, areas where accuracy problems may occur due to insufficient resolution can be found. The amplitude, frequency, and time information of the voltage curve will be compared with the minimum adjustment step size of the voltage simulator to find out the parts that cannot be accurately adjusted in amplitude change, frequency change, or time interval, and mark them as target areas.

[0072] In some specific embodiments, the minimum voltage amplitude step, minimum frequency adjustment step and time step of the voltage simulator are clearly defined, and these parameters can be obtained from the device manual of the voltage simulator or by testing its performance; then, each time point of the voltage curve is traversed, and the amplitude difference, frequency difference and time difference between adjacent time points are calculated; finally, the area where the amplitude difference is less than the minimum voltage amplitude step, the frequency difference is less than the minimum frequency adjustment step, or the time difference is less than the time step is marked as the target area, which is not limited here.

[0073] S302, determining a loss amount according to a change in amplitude, a change in frequency or a change in duration in the target area and a corresponding minimum voltage amplitude step, a minimum frequency adjustment step or a time step; The loss refers to the deviation caused by the inability to accurately simulate the voltage curve due to the minimum step size limitation of the voltage simulator, and refers to the degree of difference between the actual voltage curve in the target area and the closest voltage curve that can be simulated.

[0074] In some embodiments, after finding the target area, it is necessary to quantify the precision loss in these areas. By calculating the change in amplitude, frequency, and duration in the target area and comparing it with the corresponding minimum step size, the specific loss amount can be obtained. For example, for the amplitude change in a target area, if it is less than the minimum voltage amplitude step size, then the difference with the minimum voltage amplitude step size is the loss in amplitude of the area. When testing the startup performance of the charging pile, quantifying the loss amount helps to make targeted adjustments to these areas later to reduce the impact of precision loss on the test results. By accurately calculating these loss amounts, the severity of precision problems in different areas can be more clearly understood, providing a basis for subsequent compensation and adjustment strategies.

[0075] In some specific embodiments, for each target area, the change in its amplitude is calculated, which can be obtained by subtracting the amplitude at the starting point and the end point of the target area; then, the change in amplitude is compared with the minimum voltage amplitude step, and the difference is calculated as the amplitude loss; finally, a similar calculation is performed on the change in frequency and duration to obtain the corresponding frequency and time loss.

[0076] S303: Adjust the amplitude, frequency and duration of the subsequent area of ​​the target area according to the loss amount, so that the sum of the loss amount is reduced.

[0077] The subsequent regions refer to those regions that are located after the target region in time sequence, and refer to the portion of the voltage curve after the target region, which is used to indicate the portion that may be affected and needs to be adjusted accordingly after the target region is adjusted. Adjusting the amplitude, frequency, and duration refers to modifying the voltage curve parameters of the subsequent regions, and refers to compensating or correcting the voltage amplitude, frequency, and duration of the subsequent regions according to the calculated loss amount to reduce the overall accuracy loss.

[0078] In some embodiments, this step is performed after determining the amount of loss. Since the loss of precision in the target area may have a chain effect on the simulation of subsequent areas, it is necessary to adjust the subsequent areas. By adjusting the amplitude, frequency and duration of the subsequent areas, the precision loss previously generated in the target area can be compensated, so that the overall simulated voltage curve is closer to the original curve. For example, if the loss of voltage amplitude in a certain target area is 0.2V, the amplitude can be appropriately increased in the subsequent area to compensate for this part of the loss, so that the overall voltage curve simulation is more accurate. This adjustment helps to improve the accuracy of the simulation, making the signal output by the voltage simulator closer to the actual expected voltage curve, thereby improving the reliability of the charging pile startup timing test. When performing complex startup timing tests on charging piles, this adjustment can avoid deviations in the overall test results due to local precision losses, ensuring accurate evaluation of the performance of the charging pile under different voltage environments.

[0079] In some specific embodiments, the direction and amplitude of the adjustment are determined according to the sign and size of the loss amount; then, for the amplitude of the subsequent area, the addition or subtraction operation is performed according to the amplitude loss amount, and the frequency and duration are also adjusted accordingly, which can be implemented using simple algorithms and loop statements; finally, the adjusted subsequent areas are checked to ensure that the adjusted parameters are within a reasonable range to avoid parameters that exceed the device capabilities.

[0080] It can be seen that the voltage curve is partitioned according to the minimum voltage amplitude step, minimum frequency adjustment step and time step of the voltage simulator, and the loss amount is determined after accurately finding the target area, and then the relevant parameters of the subsequent areas are adjusted accordingly to reduce the sum of the loss amount. This overcomes the disadvantage that the simulator step size is limited to only approximate values ​​when converting working parameters, allowing the simulated voltage signal to be closer to the expected signal of the original voltage curve, reducing the deviation between the two, and restoring the actual voltage fluctuation to the greatest extent, thereby improving the accuracy of the test, making the judgment of the charging pile startup status based on this test more reliable, and avoiding wrong judgments caused by parameter deviations.

[0081] In the previous embodiment, step S102 and step S103 use an actual voltage simulator to implement the function of simulating voltage; however, an actual test environment is required, and the test cost is relatively high.

[0082] Therefore, in some embodiments, step S102 and step S103 are replaced by: Please refer to Figure 4 , Figure 4 This is another flow chart of a method for testing the startup timing of a charging pile by a voltage simulator in an embodiment of the present application; S401, inputting the circuit structure of the charging pile into a simulation circuit model; Among them, the circuit structure of the charging pile refers to the connection mode and parameter information of various electronic components (such as transformers, rectifiers, power converters, controllers, etc.) inside the charging pile, and refers to the circuit topology structure, the electrical characteristics of the components (such as resistance, capacitance, inductance, characteristic parameters of transistors, etc.), which is used to indicate how the charging pile converts and controls the input electrical energy to realize the function of charging electric vehicles. The analog circuit model is a software or algorithm model that abstracts and digitally represents the actual circuit. It refers to the simulation of the behavior of the actual circuit through computer programs and mathematical models. It can simulate the changes of physical quantities such as voltage and current in the circuit, and is used to predict and analyze the performance and behavior of the circuit without using the actual circuit.

[0083] In some embodiments, when deciding to use an analog circuit instead of an actual voltage simulator for testing. When you want to avoid the high cost and complex hardware construction brought by the actual test environment, inputting the circuit structure of the charging pile into the analog circuit model is the basis of the entire simulation process. By converting the actual physical circuit into a digital model, the powerful computing power of the computer can be used to simulate the behavior of the circuit under different voltage inputs, avoiding the risk of damage and resource consumption that may be caused by physical construction and testing. Moreover, for different charging pile designs, their circuit structures can be quickly input into the analog circuit model to provide a virtual test platform for subsequent voltage simulation and performance testing.

[0084] In some specific embodiments, professional circuit design software (such as Cadence or Proteus) is used. First, open the software and create a new circuit design project; then, according to the actual circuit schematic of the charging pile, add various electronic components one by one in the software, such as selecting appropriate transformers, switch tubes, capacitors, inductors, etc. from the component library, and wiring according to the actual connection method; finally, set the parameters of each component, such as the transformer ratio, the capacitance value of the capacitor, the on-resistance of the switch tube, etc., and input the complete charging pile circuit structure into the simulation circuit model in the software.

[0085] S402, dividing the voltage curve into voltage segments, where the voltage segments correspond to amplitude, frequency and duration; Among them, voltage segments refer to the multiple small segments into which the voltage curve is divided, which refers to the sub-parts into which the voltage curve is divided according to certain rules. Each voltage segment has its own independent amplitude, frequency and duration characteristics, which are used to describe and process different parts of the voltage curve in more detail.

[0086] In some embodiments, this step is performed after the charging pile circuit structure is input into the analog circuit model. When different voltage inputs need to be provided to the analog circuit, dividing the voltage curve into voltage segments helps to more accurately simulate the voltage input conditions at different stages. For a complex voltage curve, which may contain multiple voltage fluctuations, dividing it into segments can more conveniently provide data basis for the subsequent creation of the corresponding voltage source module.

[0087] S403, creating a corresponding voltage source module according to the voltage segment; Among them, the voltage source module refers to a virtual component used to generate a specific voltage in the analog circuit model. It refers to an analog circuit unit that can generate a voltage of a specific amplitude, frequency and duration. It is used to simulate the actual voltage source and provide the required voltage input for the analog circuit. Its characteristics are determined by the parameters of the voltage segment.

[0088] In some embodiments, this step is performed after the voltage curve is segmented. The corresponding voltage source module is created according to the parameters such as the amplitude, frequency and duration of each voltage segment in order to accurately reproduce the voltage input represented by the voltage curve in the analog circuit. This ensures that in the analog circuit, the voltage input received by the charging pile is as similar as possible to the complex voltage environment that may actually occur, providing a guarantee for accurately testing the startup timing and performance of the charging pile under various voltage conditions.

[0089] In some specific embodiments, a voltage source component library is found in the software; then, according to the parameters of the voltage segment, a suitable voltage source component (such as a sinusoidal voltage source, a pulse voltage source, etc.) is selected from the component library, and its parameters such as amplitude, frequency and duration are set; finally, the set voltage source component is added to the simulation circuit to ensure that its connection position and connection method in the circuit meet the design requirements.

[0090] S404, arranging the circuit structure of the voltage source module in the simulation circuit model in chronological order.

[0091] Among them, the time sequence refers to the order of arrangement according to the time sequence, which refers to the order of the voltage segments on the time axis, used to indicate the order of the voltage input of the voltage source module in the analog circuit, ensuring that the analog circuit receives the corresponding voltage input according to the time sequence of the voltage curve. It means connecting the created voltage source module to the analog circuit structure of the charging pile in time sequence, and using the voltage source module as input to provide voltage input to the analog circuit, so that the charging pile in the analog circuit can work according to the time sequence and voltage change of the actual voltage curve.

[0092] In some embodiments, this step is performed after the voltage source module is created. The voltage source module is connected to the circuit structure in chronological order so that the simulation circuit can fully reproduce the voltage change process represented by the entire voltage curve. For example, when simulating the startup process of the charging pile, the low voltage source module at the startup moment is first connected to the circuit, and then the subsequent different voltage source modules are connected in sequence as time progresses, so that the simulation circuit of the charging pile can receive different voltage inputs in sequence, just like experiencing different voltage fluctuations in the actual environment. This helps to accurately test the startup performance and timing of the charging pile in a complex voltage fluctuation environment, and ensure the integrity and authenticity of the simulation test.

[0093] It can be seen that the circuit structure of the charging pile is input into the simulation circuit model, which enables the software to build a virtual model that is highly consistent with the actual charging pile circuit, subdividing the voltage curve into voltage segments, each segment corresponds to a specific amplitude, frequency and duration, and creating corresponding voltage source modules based on these voltage segments. The software can accurately control the parameters of each module to ensure the accuracy and stability of the simulated voltage signal. Finally, in the simulation circuit model, the voltage source module is connected to the circuit structure in chronological order. The software can strictly perform the simulation process according to the actual time logic and circuit connection relationship, avoiding errors and uncertainties that may be caused by hardware connection problems in the actual simulator. Through this software simulation method, the working state of the charging pile under various voltage fluctuations can be simulated in a virtual environment with high fidelity, without the need to build a complex actual test environment, which greatly reduces the test cost and time cost.

[0094] The following describes an exemplary charging pile startup timing test system 500 using a voltage simulator provided in an embodiment of the present application. Figure 5 It is a schematic diagram of an exemplary hardware structure of a charging pile startup timing test system 500 using a voltage simulator provided in an embodiment of the present application.

[0095] In some embodiments, the system 500 for testing the startup timing of a charging pile by a voltage simulator is a computer device or the system 500 for testing the startup timing of a charging pile by a voltage simulator includes a computer device. The computer device includes a processor, a memory, and a network interface connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program, and a database. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is used to store data. The network interface of the computer device is used to communicate with other external terminals or servers through a network connection. In some embodiments, the network interface can be a wired network interface, and in some embodiments, the network interface can also be a wireless network interface. When the computer program is executed by the processor, the method in the embodiment of the present application is implemented.

[0096] Those skilled in the art will understand that Figure 5 The structure shown in the figure is only a block diagram of a part of the structure related to the solution of the present application, and does not constitute a limitation on the computer device to which the solution of the present application is applied. The specific computer device may include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0097] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0098] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0099] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that includes one or more available media integrated. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium (e.g., a solid-state hard disk), etc.

[0100] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A method for testing the startup timing of a charging pile by a voltage simulator, characterized in that: include: Acquire a voltage curve, where the voltage curve is determined according to voltage fluctuations occurring in a simulated actual usage scenario, and the voltage curve includes voltage fluctuations of various amplitudes, frequencies, and durations; Setting working parameters according to the voltage curve; Inputting the operating parameters into the voltage simulator; causing the voltage simulator to send a simulated voltage signal to the connected charging pile, wherein the voltage signal changes according to the voltage curve; Monitoring the startup timing of the charging pile to obtain collected data; Determine whether the collected data is abnormal according to the judgment rule; The judgment rules include whether the electrical parameters have reached a set threshold value for normal operation and whether the startup sequence is within a reasonable time range.

2. The method according to claim 1, characterized in that The step of monitoring the startup timing of the charging pile to obtain collected data specifically includes: Input the collected data collected within a time period greater than a preset time threshold into a prediction model to obtain predicted values ​​and corresponding confidence intervals at multiple future sampling moments; According to the predicted value and the confidence interval, a fuzzy logic algorithm is used to determine whether the sampling rate needs to be adjusted; adjusting the sampling time according to the sampling rate; The acquisition amount of the collected data and the corresponding acquisition time are adjusted according to the sampling time and the sampling rate.

3. The method according to claim 2, characterized in that The step of using a fuzzy logic algorithm to determine whether the sampling rate needs to be adjusted according to the predicted value and the confidence interval specifically includes: In the formula, is the sampling rate adjustment degree, For rules, For rules The total rule activation strength, Typical values ​​corresponding to different degrees of adjustment of sampling rate requirements, To adjust the sampling rate accordingly, To adjust the threshold, , when it is greater than 0, the sampling rate needs to be adjusted. The degree of sampling rate adjustment is ,exist , when it is not greater than 0, there is no need to adjust the sampling rate; In the formula, For rules The total rule activation strength, is the result of the first rule, is the result of the second rule, As a result of the third rule; , , as a parameter.

4. The method according to claim 3, characterized in that The first rule is that when the confidence interval is within the first interval, the change in the predicted value is divided by the first adjustment amount; The second rule is that when the confidence interval is within the second interval, the change in the predicted value is divided by the second adjustment amount; The third rule is that when the confidence interval is in the third interval, the change in the predicted value is divided by the third adjustment amount; the first interval is greater than the second interval, which is greater than the third interval; the first adjustment amount is greater than the second adjustment amount, which is greater than the third adjustment amount.

5. The method according to claim 1, characterized in that The step of setting the working parameters according to the voltage curve specifically includes: Partitioning the voltage curve according to the minimum voltage amplitude step, the minimum frequency adjustment step and the time step that can be adjusted by the voltage simulator, and screening out a target area that is smaller than the minimum voltage amplitude step, the minimum frequency adjustment step or the time step; Determine the loss amount according to the change amount of amplitude, the change amount of frequency or the change amount of duration in the target area and the corresponding minimum voltage amplitude step, minimum frequency adjustment step or time step; The amplitude, frequency and duration of the subsequent area of ​​the target area are adjusted according to the loss amount so that the sum of the loss amount is reduced.

6. The method according to claim 1, characterized in that The steps of setting working parameters according to the voltage curve; inputting the working parameters into a voltage simulator; and causing the voltage simulator to send a simulated voltage signal to a connected charging pile, wherein the voltage signal changes according to the voltage curve, specifically include: Input the circuit structure of the charging pile into the simulation circuit model. dividing the voltage curve into voltage segments, wherein the voltage segments correspond to amplitude, frequency and duration; Creating a corresponding voltage source module according to the voltage segment; In the simulation circuit model, the voltage source modules are arranged in the circuit structure in chronological order.

7. The method according to claim 1, characterized in that Before the step of inputting the working parameters to the voltage simulator; and causing the voltage simulator to send a simulated voltage signal to the connected charging pile, wherein the voltage signal changes according to the voltage curve, the method further includes: Obtaining load parameters, where the load parameters are determined by the load occurring in the simulated actual usage scenario; Adjusting the load simulator according to the load parameter so that the output load of the load simulator is the same as the load parameter; Activate the connection channel between the load simulator and the charging pile.

8. A charging pile startup timing test system using a voltage simulator, characterized in that: The system for testing the charging pile startup timing by using a voltage simulator includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the system for testing the charging pile startup timing by using a voltage simulator to execute the method described in any one of claims 1-7.

9. A computer program product comprising instructions, characterized in that When the computer program product runs on a system for testing the startup sequence of a charging pile through a voltage simulator, the system for testing the startup sequence of a charging pile through a voltage simulator executes the method according to any one of claims 1 to 7.

10. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on a system for testing the startup sequence of a charging pile through a voltage simulator, the system for testing the startup sequence of a charging pile through a voltage simulator executes the method according to any one of claims 1 to 7.

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