An intelligent protection system, device and method for a high-power direct-current charging pile

Abstract

The application relates to the technical field of charging protection, in particular to an intelligent protection system, device and method for a high-power direct-current charging pile, which determines an interference abnormality coefficient of a charging stage by deeply analyzing low-frequency odd harmonic components contained in a current during a charging process of the direct-current charging pile and abnormal waveform change characteristics, further combines the interaction of harmonic currents on temperature changes to construct a state abnormality coefficient, analyzes the abnormality degree existing in the operation state, and evaluates the operation state of the charging pile based on the same. The application aims to evaluate the harmonic influence caused by the change of an input side and accurately evaluate the operation state of the charging pile.

Description

Technical Field

[0001] This application relates to the field of charging protection technology, specifically to an intelligent protection system, device, and method for a high-power DC charging pile. Background Technology

[0002] As a crucial infrastructure in modern transportation, the stability and reliability of the power supply system for new energy vehicle charging stations directly impact the normal operation of production and daily life. However, during actual operation, charging stations are frequently prone to malfunctions due to various complex factors, such as short circuits and leakage. Failure to address these issues promptly and accurately can lead to serious consequences.

[0003] Despite continuous technological advancements and the increasing application of intelligent monitoring methods in charging pile operation monitoring, existing conventional monitoring methods still fail to fully consider the impact of the power distribution network on the charging current quality, leading to an increase in harmonic currents. These unmonitored fluctuations further reduce the stability of charging piles and cause the response efficiency and effectiveness of intelligent protection systems to fall short of expectations. Summary of the Invention

[0004] In view of the above, it is necessary to provide an intelligent protection system, device and method for high-power DC charging piles to solve the above problems.

[0005] According to one aspect of this application, an intelligent protection method for a high-power DC charging pile is provided, the method comprising:

[0006] Acquire the current and temperature at various moments during the charging process of the DC charging pile;

[0007] The entire charging process is divided into charging stages based on the charging capacity. The frequency distribution characteristics of the current in each charging stage are analyzed to determine the low-frequency significant characteristics of each charging stage. Abrupt change detection is performed on the current in each charging stage, and the difference between the abrupt change point and the adjacent current is compared to determine the abrupt change significance value of each charging stage. The determination coefficient of the current is combined with the current to determine the abnormal fluctuation coefficient of each charging stage. The interference abnormality significance coefficient of each charging stage is determined by combining the low-frequency significant characteristics and the abnormal fluctuation coefficient of each charging stage.

[0008] Trend analysis is performed on all temperatures in each charging stage. The difference distribution between the interference anomaly significance coefficients of each DC charging pile and other charging piles in each charging stage is analyzed to obtain the state anomaly coefficient of each DC charging pile in each charging stage. Intelligent protection is implemented for the DC charging pile based on the magnitude of the state anomaly coefficient.

[0009] Specifically, determining the low-frequency salient features of each charging stage involves:

[0010] Based on the frequency amplitude spectrum of the current in each charging stage, the fundamental current frequency and odd harmonic frequencies are obtained.

[0011] By comparing the amplitudes corresponding to the odd harmonic frequencies with the amplitudes corresponding to the fundamental current frequencies, the relative magnitudes of the odd harmonic components can be determined.

[0012] The differences between the amplitudes corresponding to all odd harmonic frequencies and the amplitudes corresponding to the largest odd harmonic frequency are accumulated and positively fused with the relative magnitudes of the odd harmonic components to obtain the low-frequency salient features of each charging stage.

[0013] Specifically, the relative magnitude of the odd harmonic components is the ratio of the sum of the amplitudes corresponding to all odd harmonic frequencies to the amplitude corresponding to the fundamental current frequency.

[0014] Specifically, determining the significant value of the mutation in each charging stage involves:

[0015] Calculate the ratio between each abrupt change point and its two adjacent currents, and take the average of all ratios obtained from all abrupt change points as the abrupt change significance value for each charging stage.

[0016] Specifically, the abnormal fluctuation coefficient for each charging stage is the ratio of the mutation significance value to the determination coefficient.

[0017] Specifically, the interference anomaly significance coefficient for each charging stage is the product of the low-frequency significant feature and the abnormal fluctuation coefficient.

[0018] The specific process for obtaining the state anomaly coefficient of each DC charging pile at each charging stage is as follows:

[0019] Obtain the trend test statistics for all temperatures in each charging stage;

[0020] The average difference between the interference anomaly significance coefficients of each DC charging pile and all other DC charging piles is calculated and positively fused with the trend test statistic to obtain the state anomaly coefficient of each DC charging pile in each charging stage.

[0021] Specifically, the intelligent protection of the DC charging pile includes:

[0022] When the normalized value of the abnormal state coefficient of the DC charging pile in the current charging stage is greater than the preset threshold, charging is stopped; otherwise, charging continues.

[0023] According to another aspect of this application, an intelligent protection device for a high-power DC charging pile is provided, including a memory, a processor, and a computer program stored in the memory and running on the processor, wherein the processor executes the computer program to implement the steps of any of the methods described above.

[0024] According to another aspect of this application, an intelligent protection system for a high-power DC charging pile is provided, wherein the system stores a computer program, which, when executed by a processor, implements any of the methods described above.

[0025] This application has at least the following beneficial effects:

[0026] This application acquires current and temperature data at every moment during the DC charging process of a charging pile, enabling real-time monitoring of the charging pile's operational status and providing more comprehensive data support for subsequent analysis. Dividing the charging process into different stages facilitates targeted analysis of the characteristics of each stage, identifying stage-specific anomalies or fluctuations. By analyzing the current frequency distribution characteristics of each charging stage, typical current characteristics of each stage can be identified, providing a basis for subsequent anomaly identification. Current mutation detection compares the difference between mutation points and adjacent currents. Mutation detection can capture drastic changes in current data in real time, promptly detecting potential equipment failures or other anomalies during battery charging. The comparison of mutation points with adjacent currents helps identify potential problems early and provide warnings to prevent problem escalation. Determining the abnormal fluctuation coefficient of the charging stage quantifies the charging process. The amplitude of current fluctuations provides an objective basis for judging the intensity of anomalies. Furthermore, considering that temperature is an important indicator for evaluating whether charging equipment is working properly, trend testing of temperature can help determine whether there is an overheating risk in the charging pile. Analyzing the differences in the significance coefficients of interference anomalies between different charging piles can help identify performance differences among charging piles and prevent equipment failures caused by current fluctuations during charging. Intelligent protection based on the state anomaly coefficients during charging can automatically activate the protection mechanism when potential faults occur in the equipment, realizing comprehensive monitoring and intelligent protection of DC charging piles, improving equipment stability and safety, and providing valuable data information for subsequent maintenance and optimization. This method can not only accurately assess the harmonic effects caused by changes on the input side, but also effectively make up for the efficiency deficiencies of existing intelligent protection systems. Attached Figure Description

[0027] Figure 1 A flowchart illustrating the steps of an intelligent protection method for a high-power DC charging pile provided in this application;

[0028] Figure 2 A flowchart for obtaining the state anomaly coefficient provided in this application. Detailed Implementation

[0029] In the description of the embodiments in this application, the words "exemplary," "or," and "for example" are used to indicate examples, illustrations, or descriptions. Any embodiment or design scheme described as "exemplary" or "for example" in the embodiments of this application should not be construed as being more preferred or advantageous than other embodiments or design schemes. Specifically, the use of the words "exemplary," "or," and "for example" is intended to present the relevant concepts in a specific manner.

[0030] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs. The terminology used in this application's specification is for the purpose of describing particular embodiments only and is not intended to be limiting of the application.

[0031] It should also be noted that the terms "first" and "second" in this application and its accompanying drawings are used to distinguish similar objects, rather than to describe a specific order or sequence. The methods disclosed in the embodiments of this application or the methods shown in the flowcharts include one or more steps for implementing the method. Without departing from the scope of this application, the execution order of multiple steps can be interchanged, and some steps can also be deleted.

[0032] Please see Figure 1 The diagram illustrates a flowchart of a smart protection method for a high-power DC charging pile according to an embodiment of this application. The method includes the following steps:

[0033] Step 1: Obtain the current and temperature at various moments during the DC charging process.

[0034] The current and temperature of the DC charging pile are collected in real time using current and temperature sensors. In this embodiment, the time interval for current acquisition is set to 1ms, and the time interval for temperature acquisition is set to 1s. An IIR filter is used to preprocess the collected data to reduce noise and interference in the data.

[0035] Step 2: Divide the entire charging process into charging stages based on the charging capacity, analyze the frequency distribution characteristics of the current in each charging stage, and determine the low-frequency significant features of each charging stage; perform abrupt change detection on the current in each charging stage, compare the difference between the abrupt change point and the adjacent current, determine the abrupt change significance value of each charging stage, combine the current to obtain the coefficient of determination, and determine the abnormal fluctuation coefficient of each charging stage; combine the low-frequency significant features and abnormal fluctuation coefficient of each charging stage to determine the interference abnormality significance coefficient of each charging stage.

[0036] Electric vehicles introduce harmonic currents into the power distribution network during charging, which degrades the power quality of charging stations and causes losses in distribution transformers. These losses increase with the harmonic content in the circuit. Furthermore, charging stability is affected by the number of charging stations connected and changes in their internal temperature, exacerbating transformer losses. These factors all impact the normal operation of charging stations, leading to the following analysis of their influence characteristics during operation.

[0037] Due to the charging characteristics of vehicle-mounted power batteries, DC charging stations typically employ a multi-stage charging mode, namely a constant current charging stage, a constant voltage charging stage, and a trickle charging stage. In the initial charging stage, when the battery level is below 70%, a larger current is needed to quickly increase the battery's charge; this is the constant current charging stage, where the charging station charges the battery with a fixed current value. Once the battery voltage reaches a preset constant voltage charging threshold, it enters the constant voltage charging stage. In this mode, the charging voltage remains constant, while the charging current gradually decreases as the battery level increases. Constant voltage charging is typically used for charging batteries from 70% to 90% charge. Finally, the battery is charged with a very small constant current; this is the trickle charging stage. Thus, the corresponding charging stage can be determined based on the battery's charge level. Each charging stage is susceptible to various disturbances. Let's analyze the impact characteristics using one charging stage of a charging station as an example.

[0038] When the charging process is affected by harmonic currents, low-frequency odd-order harmonic currents will account for a larger proportion of the current, such as the 3rd and 5th harmonics. The higher the proportion of low-frequency odd-order harmonic currents, the greater the loss to the charging pile transformer. Therefore, this application first uses Discrete Fourier Transform to obtain the frequency amplitude spectrum of the current at each charging stage. The measured charging current is usually composed of fundamental current and harmonic currents, with the fundamental current being the main component. The frequency with the maximum amplitude in the frequency amplitude spectrum is then taken as the fundamental current frequency. The resulting harmonic current frequencies are usually odd multiples of the fundamental current frequency. Therefore, N times the fundamental current frequency is taken as the harmonic frequency; in this application, N takes any odd number within the range [3, 9]. The amplitudes corresponding to the harmonic frequencies in the frequency amplitude spectrum are arranged in ascending order of frequency to form the odd-order harmonic sequence. First, the ratio of the sum of all data in the odd-order harmonic sequence to the amplitude corresponding to the fundamental current frequency is calculated and denoted as the relative magnitude R of the harmonic frequency component. The obtained R reflects the amount of odd-order harmonic components contained in the charging current; the larger the R, the more overall harmonic current components are contained in the current. Further, combining the distribution characteristics of odd-order harmonics at low frequencies, the significant low-frequency characteristics are obtained. Its formula is: Where J represents the total number of odd harmonic sequences, , Let A and J represent the i-th and J-th data points in the odd harmonic sequence, respectively. The larger the value of A, the higher the proportion of low-frequency odd harmonic current.

[0039] Furthermore, harmonic currents can cause abnormal changes in the current waveform. For example, during the charging process of an electric vehicle, as the number of charging piles connected increases, the coordination and control between different charging piles, using a multi-module parallel connection, can affect the normal operation of the charging piles, causing sudden changes or oscillations in the current waveform. The greater the degree of such changes or oscillations, the more likely the unstable current changes will cause losses in the charging pile transformer, affecting the charging quality. Therefore, for each charging stage, this application uses a sliding t-test algorithm to obtain all abrupt changes in the current. Then, it calculates the ratio between each abrupt change point and its two adjacent currents, and takes the average of all ratios obtained from all abrupt changes as the significance value of the abrupt change for each charging stage, denoted as M. The obtained M reflects the significant characteristics of the current waveform abrupt changes in the charging pile during that charging stage. Further, for the degree of oscillation in the current waveform, this application uses the least squares method to fit the current. The greater the degree of oscillation, the greater the deviation between the measured current and the fitted straight line. Therefore, the determination coefficient of the fitted straight line obtained in each charging stage is calculated, denoted as V. The obtained V reflects the degree of fitting of the current waveform during this charging stage. A smaller V indicates a worse fitting effect and more significant oscillation characteristics of the current waveform. Therefore, the abnormal fluctuation coefficient for each charging stage can be obtained. Its formula is: The result B reflects the abnormal changes in the charging current waveform, including abrupt changes and oscillations.

[0040] Therefore, for a given charging pile, the low-frequency salient characteristics and abnormal fluctuation coefficients for each charging stage can be obtained. These two characteristics reflect the influence of input-side changes on the current during the charging pile's operation from different perspectives. The product of the low-frequency salient characteristics and abnormal fluctuation coefficients for each charging stage is then used as the interference anomaly salient coefficient for that stage, denoted as C. The larger the obtained C, the more pronounced the harmonic interference and waveform anomalies of the charging pile current.

[0041] Step 3: Perform trend analysis on all temperatures in each charging stage, analyze the difference distribution between the interference anomaly significance coefficients of each DC charging pile and other charging piles in each charging stage, and obtain the state anomaly coefficient of each DC charging pile in each charging stage; perform intelligent protection for the DC charging pile based on the magnitude of the state anomaly coefficient.

[0042] Due to the presence of harmonic currents, the effective value of the actual current in the cable will be greater than the fundamental current, increasing the loss of the charging pile transformer, accelerating cable aging, and causing internal heating of the charging pile over time, further affecting the equipment's performance and lifespan. Therefore, the higher the degree of harmonic influence of the charging pile current and the more obvious the increasing temperature trend, the more unstable the charging pile's operation. Furthermore, the Mankendall test is used to obtain the trend test statistic for all temperatures at each charging stage, denoted as T. The larger the T, the more significant the temperature increase characteristic of the charging pile at the corresponding charging stage. Multiple charging piles typically operate simultaneously within a charging station, and at the same time, different charging piles are in different charging stages, resulting in different overall magnitudes of the charging current. However, if the current of a particular charging pile is more affected by harmonics, the significance coefficient of the corresponding harmonic interference and waveform anomaly characteristics will be significantly larger compared to other charging piles. Therefore, the mean of the difference in the significance coefficient of interference anomalies between a particular charging pile and all other charging piles is calculated, denoted as D. The obtained D reflects the difference in the degree of harmonic influence between the charging pile and other charging piles. Therefore, the state anomaly coefficient F of each DC charging pile in each charging stage is calculated using the following formula: , where exp() represents an exponential function with the natural constant e as the base. The larger the obtained F, the greater the possibility of abnormal operation of the charging pile.

[0043] The flowchart for obtaining the state anomaly coefficient is as follows: Figure 2 As shown.

[0044] This application conducts an in-depth analysis of the low-frequency odd-order harmonic components and abnormal waveform changes in the current during the charging process of charging piles. Furthermore, it analyzes the degree of abnormality in the operating state by combining the interaction between the harmonic current and temperature changes, and uses this to evaluate the operating status of the charging piles. Prolonged harmonic current can affect the operational stability of charging piles. Based on the above analysis, this application uses a minimization method to normalize the abnormality coefficients of all charging piles, and sets the abnormality threshold as the third quartile within the range of (0,1). If the normalized result is greater than the abnormality threshold, charging is immediately stopped, and the operator is alerted in the interactive module that the charging pile is in an abnormal state, facilitating remedial measures; otherwise, charging continues.

[0045] Based on the same concept as the method embodiments of this application, an intelligent protection device for a high-power DC charging pile is provided, including a memory, a processor, and a computer program stored in the memory and running on the processor. When the processor executes the computer program, it implements the steps of any of the methods described above.

[0046] Based on the same concept as the method embodiments of this application, an intelligent protection system for a high-power DC charging pile is provided. The system stores a computer program, which, when executed by a processor, implements any of the methods described above.

[0047] It should be noted that the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of the systems, methods, and computer program products according to embodiments of this application. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. In some alternative implementations, the functions marked in the blocks may occur in a different order than that shown in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. In the descriptions corresponding to the flowcharts and block diagrams in the accompanying drawings, the operations or steps corresponding to different blocks may also occur in a different order than disclosed in the description; sometimes there is no specific order between different operations or steps. For example, two consecutive operations or steps may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. Each block in a block diagram and / or flowchart, and combinations of blocks in a block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or action, or using a combination of dedicated hardware and computer instructions.

[0048] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A smart protection method for a high-power DC charging pile, characterized in that, The method includes the following steps: Acquire the current and temperature at various moments during the charging process of the DC charging pile; The entire charging process is divided into charging stages based on the charging capacity. The frequency distribution characteristics of the current in each charging stage are analyzed to determine the low-frequency significant features of each charging stage. Abrupt changes in the current of each charging stage are detected, and the difference between the abrupt change point and the adjacent current is compared to determine the abrupt change significance value of each charging stage. The determination coefficient of the fitting is combined with the current to determine the abnormal fluctuation coefficient of each charging stage. The product of the low-frequency significant features and the abnormal fluctuation coefficient of each charging stage is used as the interference abnormal significance coefficient of each charging stage. Trend analysis is performed on all temperatures in each charging stage. The difference distribution between the interference anomaly significance coefficients of each DC charging pile and other charging piles in each charging stage is analyzed to obtain the state anomaly coefficient of each DC charging pile in each charging stage. Intelligent protection is implemented for the DC charging pile based on the magnitude of the state anomaly coefficient. The determination of the low-frequency salient features of each charging stage specifically includes: Based on the frequency amplitude spectrum of the current in each charging stage, the fundamental current frequency and odd harmonic frequencies are obtained. By comparing the amplitudes corresponding to the odd harmonic frequencies with the amplitudes corresponding to the fundamental current frequencies, the relative magnitudes of the odd harmonic components can be determined. The differences between the amplitudes corresponding to all odd harmonic frequencies and the amplitudes corresponding to the largest odd harmonic frequency are accumulated and positively fused with the relative magnitudes of the odd harmonic components to obtain the low-frequency salient features of each charging stage. The determination of the significant value of the mutation in each charging stage is specifically as follows: Calculate the ratio between each abrupt change point and its two adjacent currents, and take the average of all ratios obtained from all abrupt change points as the abrupt change significance value for each charging stage.

2. The intelligent protection method for a high-power DC charging pile as described in claim 1, characterized in that, The relative magnitude of the odd harmonic components is specifically the ratio of the sum of the amplitudes corresponding to all odd harmonic frequencies to the amplitude corresponding to the fundamental current frequency.

3. The intelligent protection method for a high-power DC charging pile as described in claim 1, characterized in that, The abnormal fluctuation coefficient for each charging stage is specifically the ratio of the mutation significance value to the determination coefficient.

4. The intelligent protection method for a high-power DC charging pile as described in claim 1, characterized in that, The specific process for obtaining the state anomaly coefficient of each DC charging pile at each charging stage is as follows: Obtain the trend test statistics for all temperatures in each charging stage; The average difference between the interference anomaly significance coefficients of each DC charging pile and all other DC charging piles is calculated and positively fused with the trend test statistic to obtain the state anomaly coefficient of each DC charging pile in each charging stage.

5. The intelligent protection method for a high-power DC charging pile as described in claim 1, characterized in that, The intelligent protection of the DC charging pile specifically includes: When the normalized value of the abnormal state coefficient of the DC charging pile in the current charging stage is greater than the preset threshold, charging is stopped; otherwise, charging continues.

6. An intelligent protection device for a high-power DC charging pile, comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that, When the processor executes the computer program, it implements the steps of the method as described in any one of claims 1-5.

7. An intelligent protection system for a high-power DC charging pile, wherein the system stores a computer program, characterized in that, When the computer program is executed by a processor, it implements the method as described in any one of claims 1-5.

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