A vehicle charging data security monitoring method and system

Abstract

The application provides a vehicle charging data security monitoring method, and belongs to the technical field of data processing. The method comprises the following steps: issuing a power adjustment instruction containing a target power value and an adjustment time to a plurality of charging terminals; acquiring a response timestamp and a real-time power value sequence reported by each terminal; acquiring an actual total power change curve from a power supply node; performing time alignment and accumulation on the real-time power value sequence based on the response timestamp to obtain a theoretical total power change curve; comparing the theoretical total power curve with the actual total power curve point by point to obtain a power deviation value at a continuous time point; if the power deviation value at the continuous time point is greater than a first threshold value, it is determined that at least one terminal reports abnormal data; and determining an abnormal charging terminal associated with the power deviation value based on the contribution degree of the real-time power value sequence of each terminal to the theoretical total power curve. The application can accurately identify an abnormal data source.

Description

Technical Field

[0001] This application relates to the field of data processing, and in particular to a method and system for monitoring the safety of vehicle charging data. Background Technology

[0002] With the rapid development of the new energy vehicle industry, the large-scale deployment of electric vehicle charging infrastructure has become an inevitable trend. In scenarios such as public charging stations, parking lots of commercial complexes, and residential communities, multiple charging terminals often share a single power supply node. These charging terminals are managed and scheduled uniformly through a control terminal.

[0003] During vehicle charging, the secure monitoring of charging data is crucial. Charging data not only affects user billing but also the load balance and safe operation of the power grid. However, existing charging data monitoring methods primarily rely on data reported by individual charging terminals, using encryption and digital signatures to ensure data integrity during transmission. These methods, dependent on a single data source, have limited verification capabilities. When a charging terminal malfunctions or is controlled by a malicious attacker, its reported data may be completely distorted. Traditional methods lack objective verification mechanisms independent of the terminal itself, making it difficult to detect such anomalies.

[0004] Meanwhile, multiple charging terminals may collude to falsify data, such as simultaneously falsely reporting or concealing charging power, in order to interfere with grid dispatch or steal electricity. Since the data from each terminal may conform to protocol specifications when viewed individually, traditional anomaly detection methods based on single-point data cannot identify such coordinated behavior. Summary of the Invention

[0005] This application provides a method and system for monitoring the security of vehicle charging data, which improves upon the aforementioned problems.

[0006] To achieve the above objectives, this application adopts the following technical solution: In a first aspect, embodiments of this application propose a method for secure monitoring of vehicle charging data, applied to a vehicle charging data security monitoring system. The system includes multiple charging terminals and a control terminal, with the multiple charging terminals sharing a single power supply node. The method is applicable to the control terminal and includes: A power adjustment command is issued to multiple charging terminals. The power adjustment command includes a target power value and an adjustment time, as well as a power perturbation verification waveform generated by the control terminal and assigned to each charging terminal. The power perturbation verification waveform is used to superimpose a known fluctuation pattern with limited amplitude on the output power of the charging terminal during the power change process after the adjustment time, so that each charging terminal adjusts its output power to the target power value at the adjustment time. The dynamic response data reported by each charging terminal during the power adjustment command process is obtained. The dynamic response data includes at least the response timestamp when the actual power of the corresponding charging terminal begins to change, the real-time power value sequence during the power change process, and the measured disturbance waveform corresponding to the power perturbation verification waveform extracted from the real-time power value sequence. Obtain the actual total power change curve from the power supply node, and the actual total power change curve should at least cover the time period from the adjustment time to the last response time; The real-time power value sequence is time-aligned based on the response timestamp of each charging terminal, and the theoretical total power change curve is obtained by accumulating it moment by moment. By comparing the theoretical total power change curve with the actual total power change curve point by point, the power deviation values ​​at multiple consecutive time points are obtained. If there are consecutive time points where the power deviation value is greater than the first threshold, it is determined that at least one charging terminal under the power supply node has reported abnormal data. Based on the contribution of the real-time power value sequence of each charging terminal to the power value at each moment of the theoretical total power change curve, and the degree of matching between the measured disturbance waveform and the power micro-disturbance verification waveform, abnormal charging terminals associated with the power deviation value are determined. If the degree of matching between the measured disturbance waveform and the power micro-disturbance verification waveform of any charging terminal is lower than a preset verification threshold, then the charging terminal is determined to be an abnormal charging terminal.

[0007] In conjunction with the first aspect, optionally, the dynamic response data also includes the slope value of the power change of the charging terminal during the power change process, and the method further includes: The control terminal compares the power change slope value with the corresponding hardware characteristic slope reference value of the charging terminal; If the slope value of the power change is greater than the baseline value of the slope of the hardware feature than the second threshold, then the corresponding charging terminal is determined to be an abnormal charging terminal.

[0008] In conjunction with the first aspect, optionally, based on the contribution of the real-time power value sequence of each charging terminal to the power value at each moment of the theoretical total power change curve, abnormal charging terminals associated with the power deviation value are determined, including: Obtain the power residual sequence at each time point between the theoretical total power change curve and the actual total power change curve; Correlation analysis was performed between the power residual sequence and the real-time power value sequence of each charging terminal; Based on the results of correlation analysis, charging terminals that are positively correlated with the power residual sequence are identified as abnormal charging terminals.

[0009] In conjunction with the first aspect, optionally, correlation analysis can be performed between the power residual sequence and the real-time power value sequence of each charging terminal, including: The real-time power value sequence corresponding to each charging terminal is shifted forward or backward by multiple different time offsets on the time axis; The similarity value corresponding to the time offset is obtained by multiplying the shifted real-time power value sequence and the power residual sequence point by point within the same time interval and accumulating them. Obtain the time offset that maximizes the similarity value and the corresponding maximum similarity value; If the maximum similarity value is greater than the preset similarity threshold, and the time offset corresponding to the maximum similarity value matches the power change start time indicated by the response timestamp of the charging terminal, then it is determined that the real-time power value sequence of the charging terminal is correlated with the power residual sequence, and the corresponding charging terminal is identified as an abnormal charging terminal associated with the power deviation value.

[0010] In conjunction with the first aspect, optionally, each charging terminal has a primary communication link and a backup communication link, wherein the primary communication link and the backup communication link use different physical communication media to send power adjustment commands to multiple charging terminals, including: The same power adjustment command is sent to the same charging terminal simultaneously through the first communication link and the second communication link, and the charging terminal is instructed to report dynamic response data simultaneously through the first communication link and the second communication link. The first dynamic response data and the second dynamic response data reported by the same charging terminal are received respectively based on the first communication link and the second communication link; The first dynamic response data and the second dynamic response data are compared item by item, including at least the response timestamp, real-time power value sequence and power change slope value. If the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any item, the charging terminal is determined to be an abnormal charging terminal.

[0011] In conjunction with the first aspect, optionally, if the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any item, the charging terminal is determined to be an abnormal charging terminal, including: Obtain the first response timestamp and the first real-time power value sequence from the first dynamic response data, and the second response timestamp and the second real-time power value sequence from the second dynamic response data; The first response timestamp is compared with the second response timestamp. If the time difference between the two is greater than the preset time deviation threshold, the abnormal charging terminal is determined to be an abnormal charging terminal.

[0012] In conjunction with the first aspect, optionally, if the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any item, the charging terminal is determined to be an abnormal charging terminal, including: If the time difference between the first response timestamp and the second response timestamp does not exceed the time deviation threshold, the first real-time power value sequence and the second real-time power value sequence are compared in shape, and the dynamic time warping distance between the two power change curves is obtained. If the dynamic time warp distance is greater than the preset morphological deviation threshold, the charging terminal is determined to be an abnormal charging terminal.

[0013] In conjunction with the first aspect, optionally, if the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any item, the charging terminal is determined to be an abnormal charging terminal, including: If the dynamic time warping distance does not exceed the shape deviation threshold, and the difference between the power values ​​of the first real-time power value sequence and the second real-time power value sequence at the same time continuously exceeds the preset amplitude deviation threshold, the charging terminal is determined to be an abnormal charging terminal.

[0014] Secondly, this application proposes a vehicle charging data security monitoring system, including multiple charging terminals and a control terminal, wherein the multiple charging terminals share a single power supply node, and the system is configured as follows: A power adjustment command is sent to multiple charging terminals. The power adjustment command includes the target power value and the adjustment time, so that each charging terminal adjusts its output power to the target power value at the adjustment time. The dynamic response data reported by each charging terminal during the process of responding to the power adjustment command is obtained. The dynamic response data includes at least the response timestamp when the actual power of the corresponding charging terminal begins to change and the real-time power value sequence during the power change process. Obtain the actual total power change curve from the power supply node, and the actual total power change curve should at least cover the time period from the adjustment time to the last response time; The real-time power value sequence is time-aligned based on the response timestamp of each charging terminal, and the theoretical total power change curve is obtained by accumulating it moment by moment. By comparing the theoretical total power change curve with the actual total power change curve point by point, the power deviation values ​​at multiple consecutive time points are obtained. If there are consecutive time points where the power deviation value is greater than the first threshold, it is determined that at least one charging terminal under the power supply node has reported abnormal data. Based on the contribution of each charging terminal's real-time power value sequence to the power value at each moment of the theoretical total power change curve, abnormal charging terminals associated with power deviation values ​​are identified.

[0015] A third aspect of this invention provides an electronic device, which includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method proposed in the first aspect of the present invention.

[0016] A fourth aspect of the present invention provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the method as described in the first aspect of the present invention.

[0017] In summary, the above method and apparatus have the following technical effects: This application proposes a method for monitoring vehicle charging data security, comprising: issuing power adjustment instructions containing target power values ​​and adjustment times to multiple charging terminals; acquiring response timestamps and real-time power value sequences reported by each terminal; obtaining the actual total power change curve from the power supply node; aligning and accumulating the real-time power value sequence based on the response timestamps to obtain the theoretical total power change curve; comparing the theoretical total power curve with the actual total power curve point by point to obtain power deviation values ​​at consecutive time points; if the power deviation value at consecutive time points is greater than a first threshold, determining that at least one terminal has reported abnormal data; and identifying the abnormal charging terminal associated with the power deviation value based on the contribution of each terminal's real-time power value sequence to the theoretical total power curve. This invention can accurately identify abnormal data sources. Attached Figure Description

[0018] Figure 1 This is a flowchart illustrating a vehicle charging data security monitoring method proposed in an embodiment of this application. Detailed Implementation

[0019] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0020] Example 1 Please see Figure 1 This application proposes a vehicle charging data security monitoring method, applied to a vehicle charging data security monitoring system. The system includes multiple charging terminals and a control terminal, with the multiple charging terminals sharing a single power supply node. The method is applicable to the control terminal and includes the following steps: S101: Issue power adjustment instructions to multiple charging terminals. The power adjustment instructions include a target power value and an adjustment time, as well as a power perturbation verification waveform generated by the control terminal and assigned to each charging terminal. The power perturbation verification waveform is used to superimpose a known fluctuation pattern with limited amplitude on the output power of the charging terminal during the power change process after the adjustment time, so that each charging terminal adjusts its output power to the target power value at the adjustment time.

[0021] Understandably, a unified power adjustment command can be sent to multiple charging terminals sharing a single power supply node. This command includes core parameters: the target power value, the adjustment time, and a power perturbation verification waveform. The target power value specifies the new output power level that each charging terminal needs to achieve, while the adjustment time defines the unified point in time for all charging terminals to perform this power adjustment. The power perturbation verification waveform is a small-amplitude fluctuation pattern generated by the control terminal and assigned to each charging terminal. This could be a small sine wave, a pseudo-random sequence, or a specifically coded power ripple. Its amplitude is much smaller than the normal charging power and will not significantly affect the charging process itself or the power grid, but it is sufficient to be captured by the measuring equipment of the charging terminal and the power supply node. After receiving this waveform command, each charging terminal, during the process of performing power adjustment and changing from the current power to the target power, needs to superimpose this known perturbation waveform onto its output power. The purpose of this command is to enable all charging terminals that receive the command to synchronously adjust their respective output power from the current value to the target power value required by the command at the preset adjustment time. For example, the control terminal can set the target power value to 30kW, the adjustment time to 2:00:00 PM, and assign a specific perturbation verification waveform to each charging terminal. Each charging terminal is required to simultaneously start adjusting its output power to 30kW at 2:00:00 PM, and modulate the perturbation waveform on the power output during the change process.

[0022] S102: Obtain the dynamic response data reported by each charging terminal during the process of responding to the power adjustment command. The dynamic response data includes at least the response timestamp when the actual power of the corresponding charging terminal begins to change, the real-time power value sequence during the power change process, and the measured disturbance waveform extracted from the real-time power value sequence, corresponding to the power perturbation verification waveform.

[0023] Upon receiving a power adjustment command, each charging terminal drives its power conversion unit to perform actual power adjustment. During this dynamic response process, the charging terminal monitors its own output power changes and reports the monitored data to the control terminal. The reported dynamic response data includes at least a response timestamp, a real-time power value sequence, and a measured disturbance waveform.

[0024] Understandably, the response timestamp records the moment when the charging terminal actually detects a change in output power. Due to communication latency, internal processing time, and differences in the response characteristics of power devices, the actual start time of power change for each charging terminal may not perfectly match the adjustment time specified in the instruction. This timestamp reflects the actual delay from receiving the instruction to generating a physical response.

[0025] The real-time power value sequence records the output power values ​​of the charging terminal continuously sampled at a certain sampling frequency during power changes. This sequence describes the trajectory of the terminal's output power from its initial value to its target value, including the rate of power increase or decrease, and whether there is overshoot or oscillation. The sequence includes the contribution of the perturbation verification waveform.

[0026] The measured perturbation waveform is the actual perturbation component superimposed on the power output, extracted locally by the charging terminal from the real-time power value sequence through filtering, demodulation, or correlation operations. Since the perturbation waveform assigned to each charging terminal is known, unique, or has a specific pattern, this measured perturbation waveform can be used to verify whether the terminal has truly executed the perturbation command and whether the power data it reports is indeed generated by its own physical output.

[0027] For example, after receiving an instruction to adjust the power at 14:00:00 with a target power value of 30kW, a charging terminal actually detects the power change starting at 14:00:05, and reports a response timestamp of 14:00:05. Simultaneously, starting from 14:00:05, the terminal records the output power value every 0.1 seconds, forming a set of data: 20kW at 14:00:05, 24kW at 14:00:06, 28kW at 14:00:07, 30kW at 14:00:08, and so on, until the power stabilizes at the target value. This series of power values ​​constitutes a real-time power value sequence. Furthermore, the terminal extracts the measured disturbance waveform corresponding to the power perturbation verification waveform from this sequence, such as a small-amplitude sinusoidal fluctuation.

[0028] S103: Obtain the actual total power change curve from the power supply node. The actual total power change curve should at least cover the time period from the adjustment time to the last response time.

[0029] Understandably, the control terminal does not rely on data reported by each charging terminal to understand the total power change, but directly obtains the independently measured actual total power change curve from the power supply node. Specifically, the obtained actual total power change curve is a continuous or discrete data sequence with time as the horizontal axis and power value as the vertical axis, reflecting the actual change in total power of the power supply node within a specific time period. The time coverage of this curve starts at least from the adjustment time specified in the power adjustment command and continues until the moment when the last charging terminal actually completes its power response. The last response time refers to the moment when the latest actual power of all charging terminals begins to change, or the moment when the latest power reaches a stable state, depending on the sampling accuracy of the actual total power curve and monitoring requirements. This actual total power change curve should also include the total perturbation performance formed by the superimposed perturbation waveforms of each charging terminal.

[0030] For example, assuming the control terminal sets the adjustment time to 14:00:00, and the actual response times of each charging terminal are 14:00:03, 14:00:05, and 14:00:07 respectively, then the final response time is 14:00:07. In this case, the actual total power change curve obtained by the control terminal from the power supply node needs to cover at least the time period from 14:00:00 to 14:00:07.

[0031] S104: Based on the response timestamp of each charging terminal, the real-time power value sequence is time-aligned and accumulated moment by moment to obtain the theoretical total power change curve.

[0032] Since the actual power change start time (response timestamp) of each charging terminal is different, the real-time power value sequences they report are misaligned on the time axis and cannot be directly added. Therefore, it is necessary to perform time alignment processing on all sequences based on a unified absolute time.

[0033] Specifically, using the actual physical timeline as a reference, the real-time power value sequence reported by each charging terminal is placed in the correct time position according to its response timestamp. For example, if the response timestamp of charging terminal A is 14:00:03, its reported power value sequence is [(14:00:03, 20kW), (14:00:04, 24kW), (14:00:05, 28kW)]; and the response timestamp of charging terminal B is 14:00:05, its sequence is [(14:00:05, 18kW), (14:00:06, 24kW), (14:00:07, 30kW)]. After time alignment, the power value of each terminal at each absolute moment can be clearly determined.

[0034] After alignment, for each absolute time point, the power values ​​of all charging terminals at that time are summed. For example, at 14:00:03, only terminal A has 20kW, and the total power is 20kW; at 14:00:05, terminal A has 28kW, terminal B has 18kW, and the total power is 46kW. This process continues, summing the power values ​​at each sampling time point from the adjustment time to the final response time, ultimately yielding a complete time series, which is the theoretical total power change curve. This curve represents the dynamic change in total power that should occur at the power supply node, calculated based on the data autonomously reported by each charging terminal.

[0035] S105: Compare the theoretical total power change curve with the actual total power change curve point by point to obtain the power deviation value at multiple consecutive time points.

[0036] Understandably, after obtaining the theoretical total power change curve and the actual total power change curve, these two curves are placed on the same time coordinate system. For each sampling time point within the time period from the adjustment time to the final response time, the difference between the theoretical total power value and the actual total power value can be calculated separately.

[0037] S106: If there are consecutive time points where the power deviation value is greater than the first threshold, then it is determined that at least one charging terminal under the power supply node has reported abnormal data.

[0038] Understandably, it is possible to check whether there exists a continuous time interval in which the power deviation value exceeds a preset first threshold at every point in time. The first threshold is a preset numerical limit used to distinguish between deviations within the normal fluctuation range and significant abnormal deviations. This threshold can be determined comprehensively based on factors such as the historical load fluctuations of the power supply node, the accuracy of the measuring instruments, and the normal response characteristics of the charging terminal. The specific method of obtaining this threshold is not limited in this application.

[0039] If there are multiple consecutive time points where the power deviation value at each time point consistently exceeds the first threshold, it indicates that the theoretical total power synthesized from the data reported by each charging terminal during this time period continuously deviates from the actual total power measured at the power supply node. Understandably, if this deviation is continuous, it confirms that at least one charging terminal's reported real-time power value sequence is abnormal at the current power supply node. This abnormality may manifest in various forms, such as data tampering, data reporting delays, or power value scaling.

[0040] S107: Based on the contribution of the real-time power value sequence of each charging terminal to the power value at each moment of the theoretical total power change curve and the degree of matching between the measured disturbance waveform and the power micro-disturbance verification waveform, abnormal charging terminals associated with the power deviation value are determined. If the degree of matching between the measured disturbance waveform and the power micro-disturbance verification waveform of any charging terminal is lower than a preset verification threshold, the charging terminal is determined to be an abnormal charging terminal.

[0041] Understandably, the specific terminal can be identified in this step. Since the theoretical total power change curve is formed by summing the real-time power value sequences reported by all charging terminals moment by moment, each charging terminal's real-time power value sequence contributes to the power value at each moment on the theoretical total power curve. When there is a persistent deviation between the theoretical total power curve and the actual total power curve, this deviation is essentially caused by abnormal contribution values ​​from one or more charging terminals.

[0042] Specifically, for periods of sustained deviation, the control terminal examines the power value changes of each charging terminal during that period and compares them with the deviation trend between the theoretical total power and the actual total power. If the power value change trend of a charging terminal is highly consistent with the power deviation change trend—for example, when the power deviation increases, the terminal's power value also rises abnormally; when the power deviation decreases, the terminal's power value also falls—then it can be determined that there is a strong correlation between the terminal's power data and the deviation, and this terminal is highly likely to be the source causing the theoretical total power to deviate from the actual total power.

[0043] In addition, the control terminal will also match and compare the measured disturbance waveform reported by each charging terminal with the power perturbation verification waveform originally sent to that terminal by the control terminal.

[0044] The degree of matching can be calculated using methods such as correlation calculations, mean square error, or pattern recognition. If the degree of matching between the measured perturbation waveform reported by a charging terminal and the original perturbation waveform is significantly lower than the preset verification threshold, it indicates that the terminal did not actually superimpose the perturbation waveform into the power output as instructed, or that the power data it reported did not originate from its own physical output but was forged or tampered with. In this case, even if its power change trend superficially matches the total deviation, the charging terminal should be directly identified as an abnormal charging terminal. Understandably, by actively injecting and verifying known perturbations, an objective verification method independent of the terminal's self-reported data is provided, which can effectively identify various abnormal behaviors, including collaborative fraud.

[0045] For example, suppose there are three charging terminals A, B, and C under a certain power supply node. The control terminal detected that the theoretical total power was consistently 3kW higher than the actual total power at three consecutive time points from 14:00:03 to 14:00:05. By examining the real-time power value sequences of each terminal, it was found that the power values ​​of terminals A and C remained stable during this period, while the power value of terminal B was exactly 3kW, 3.1kW, and 2.9kW higher than its expected power value at these three time points, respectively. It can be inferred that the power value sequence reported by terminal B is the main reason for the deviation of the theoretical total power curve from the actual total power curve. Therefore, terminal B is identified as an abnormal charging terminal associated with the power deviation. Simultaneously, the control terminal further examined the measured disturbance waveform of terminal B and found that its correlation with the micro-disturbance verification waveform sent to B was only 0.2, lower than the verification threshold of 0.8. This confirmed that terminal B's data was falsified, and terminal B was ultimately identified as an abnormal charging terminal associated with the power deviation.

[0046] As one implementation method, specifically, step S107 may include the following steps: S1071: Obtain the power residual sequence of the theoretical total power change curve and the actual total power change curve at each time point.

[0047] Understandably, organizing the power deviation values ​​obtained at each time point in chronological order creates a power residual sequence. The power residual sequence is a time-ordered data set, where each element corresponds to a residual value at a specific time point. This residual value is the theoretical total power minus the actual total power. This sequence comprehensively records the degree of deviation between the theoretical and actual total power at every moment throughout the entire time period from the adjustment time to the final response time. A positive residual indicates that the theoretical total power is higher than the actual total power, while a negative residual indicates that the theoretical total power is lower than the actual total power.

[0048] S1072: Perform correlation analysis between the power residual sequence and the real-time power value sequence of each charging terminal.

[0049] S1073: Based on the results of correlation analysis, charging terminals that are positively correlated with the power residual sequence are identified as abnormal charging terminals.

[0050] The power residual sequence reflects the deviation between the theoretical total power and the actual total power at each moment, while the real-time power value sequence reported by each charging terminal records the trajectory of its own power change over time. By comparing and analyzing the power value sequence and the power residual sequence of each charging terminal, it is possible to determine whether there is any statistical correlation between the two.

[0051] Specifically, if a charging terminal is the source of power deviation, then the trend of its power value change should show some consistency with the trend of the power residual change. For example, when the power residual increases, the power value of the terminal may also rise abnormally in sync; when the power residual decreases, the power value of the terminal may fall in sync. Conversely, if the power change of a charging terminal is completely unrelated to the power residual, then the terminal is likely not the source of the abnormal data.

[0052] For example, a synchronous trend comparison can be performed on two sequences. For instance, plot the real-time power value sequence of charging terminal A as one curve, and the power residual sequence as another curve. Observe whether the peaks and troughs of the two curves correspond in time, and whether their rising and falling trends are synchronized. If the fluctuations of the two curves are highly similar, it indicates a strong correlation between the power change of the terminal and the total power deviation. Suppose that within a certain time period, the power residual sequence begins to rise at 14:00:03, reaches its peak at 14:00:04, and begins to fall back at 14:00:05. At this time, observing the real-time power value sequence of charging terminal B, we find that its power value also begins to rise at 14:00:03, reaches its peak at 14:00:04, and falls back at 14:00:05, perfectly synchronized with the trend of the residual sequence. Meanwhile, the power value of charging terminal C remains stable throughout this time period. Through this comparison, we can preliminarily determine that there is a correlation between the power change of terminal B and the total power deviation.

[0053] During actual charging, there is a certain response delay between each charging terminal receiving the power adjustment command and actually starting to change the output power. This delay is recorded through a response timestamp. However, when it is necessary to perform correlation analysis between the real-time power value sequence and the power residual sequence, the power data reported by a certain terminal may itself have a time offset. This could be due to communication delay, clock asynchrony, or a malicious attacker deliberately shifting the time point of power change to cover up their abnormal behavior.

[0054] Optionally, in order to eliminate the impact of potential response delays on correlation analysis, as one implementation method, this can be achieved through steps S201-S204: S201: Shift the real-time power value sequence corresponding to each charging terminal forward or backward by multiple different time offsets on the time axis.

[0055] To address this situation, the real-time power value sequence of each charging terminal can be shifted along the time axis. Specifically, the sequence is shifted forward as a whole, i.e., shifted in the negative direction of the time axis, which is equivalent to making the power change occur earlier, or shifted backward, i.e., shifted in the positive direction of the time axis, which is equivalent to making the power change occur later. Each shift is performed by a fixed time interval, forming a series of new sequences with different time offsets.

[0056] Multiple different time offsets refer to the control terminal attempting a series of continuous or discrete translation steps. For example, starting from -5 seconds, with a step size of 0.1 seconds, gradually increasing to +5 seconds, a total of 101 different time offsets are attempted. For each offset, the original sequence is translated by the corresponding time, generating a new translated sequence.

[0057] S202: Multiply the shifted real-time power value sequence and the power residual sequence point by point within the same time interval and accumulate them to obtain the similarity value corresponding to the time offset.

[0058] For each shifted real-time power value sequence, it can be placed on the same time axis as the power residual sequence, and the time interval covered by both can be selected as the calculation range. Within this time interval, each sequence corresponds to a value at each time point: one from the shifted real-time power value and the other from the power residual.

[0059] The real-time power value after shifting and the power residual value at each time point can be multiplied sequentially to obtain a product value for that time point. If both sequences are at a high level at the same time, the product result is large; if both are at a low level, the product result is medium; if one is high and the other is low, the product result may be small or even negative. After multiplying all time points, the control terminal sums the product values ​​from all time points to obtain a total sum. This total sum is the similarity value at the current time offset.

[0060] For example, suppose the power residual sequence has values ​​of [3.0, 3.0, 2.8] at three consecutive time points, and the real-time power value sequence of a charging terminal after translation at a certain time offset has values ​​of [20, 24, 28] in the same time period. Then the calculation process of point-by-point multiplication and accumulation is as follows: First time point: 3.0 × 20 = 60 Second time point: 3.0 × 24 = 72 The third time point: 2.8 × 28 = 78.4 Summation: 60 + 72 + 78.4 = 210.4 This 210.4 represents the similarity value at that time offset. It's understandable that when two sequences have similar fluctuation trends, they are often at the same peak or trough at the same time point, resulting in a larger and more positive product, leading to a higher similarity value after summing. Conversely, if the two sequences have opposite or unrelated fluctuation trends, the product will cancel each other out, resulting in a lower similarity value after summing. Therefore, the similarity value reflects the degree of matching between the two sequences at that time offset.

[0061] S203: Obtain the time offset that maximizes the similarity value and the corresponding maximum similarity value.

[0062] Understandably, all attempted time offsets and their corresponding similarity values ​​are compared, and the highest similarity value is identified as the maximum similarity value. Simultaneously, the time offset corresponding to this maximum similarity value is recorded.

[0063] For example, suppose the control terminal attempts to measure the real-time power value sequence of charging terminal B using multiple time offsets ranging from -2.0 seconds to +2.0 seconds with a step size of 0.1 seconds, and calculates a series of similarity values. Wherein: At a time offset of -0.5 seconds, the similarity value is 185.6. At a time offset of +0.3 seconds, the similarity value is 210.4. At a time offset of +0.4 seconds, the similarity value is 205.2. The similarity values ​​for all other offsets are below 200. After comparison, the maximum similarity value was 210.4, corresponding to an optimal time offset of +0.3 seconds. This means that when the real-time power value sequence of charging terminal B is shifted backward by 0.3 seconds, the sequence matches the power residual sequence to the highest degree.

[0064] Understandably, the maximum similarity value quantifies the correlation strength between the power change of the charging terminal and the total power deviation. On the other hand, the optimal time offset reveals the time lag or lead relationship between the power change of the terminal and the power residual.

[0065] S204: If the maximum similarity value is greater than the preset similarity threshold, and the time offset corresponding to the maximum similarity value matches the power change start time indicated by the response timestamp of the charging terminal, then it is determined that the real-time power value sequence of the charging terminal is correlated with the power residual sequence, and the corresponding charging terminal is identified as an abnormal charging terminal associated with the power deviation value.

[0066] In this application, after obtaining the maximum similarity value of each charging terminal and its corresponding time offset, these data need to be double-verified. Only when both conditions are met can the charging terminal be identified as an abnormal charging terminal associated with the power deviation value.

[0067] The first condition is that the maximum similarity value is greater than a preset similarity threshold. The similarity threshold is a pre-defined numerical limit used to distinguish between accidental numerical coincidences and genuine trend correlations. If the maximum similarity value of a charging terminal exceeds this threshold, it indicates that there is a significant synchronicity between the power change trend of the terminal and the change trend of the power residual sequence.

[0068] The second condition is that the time offset corresponding to the maximum similarity value matches the start time of the power change indicated by the response timestamp of the charging terminal. The response timestamp records the moment when the terminal's actual power begins to change, reflecting the inherent delay in the terminal's response to power adjustment commands. The time offset corresponding to the maximum similarity value is the time shift that maximizes the match between the terminal's power value sequence and the power residual sequence. If these two time parameters match, it indicates that the terminal's power change is not only synchronized with the total power deviation in trend but also conforms to its normal physical response characteristics in time. Conversely, if the time offset and the response timestamp are significantly inconsistent, even if the maximum similarity value is high, it may be due to coincidence or other reasons.

[0069] For example, suppose the response timestamp of charging terminal B is 14:00:05, indicating that its actual power began to change 5 seconds later than the adjustment time. In correlation analysis, the control terminal found that shifting the real-time power value sequence of terminal B backward by 5.1 seconds resulted in the highest matching degree with the power residual sequence, with a maximum similarity value of 210.4, while the preset similarity threshold is 200. At this point, the maximum similarity value is greater than the threshold, and the optimal time offset of 5.1 seconds highly matches the response timestamp of 5 seconds, satisfying both conditions simultaneously. Based on this, the control terminal determines that the real-time power value sequence of charging terminal B is correlated with the power residual sequence and identifies terminal B as an abnormal charging terminal associated with the power deviation value.

[0070] Example 2 This embodiment proposes a method for safe monitoring of vehicle charging data. The difference from Embodiment 1 is that the dynamic response data also includes the power change slope value of the charging terminal during power change. The method further includes: S301: The control terminal compares the power change slope value with the corresponding hardware characteristic slope reference value of the charging terminal.

[0071] Understandably, the power change slope reflects the rate of change of the output power of the charging terminal from the initial value to the target value during the response to the power adjustment command. It is usually expressed as the increase or decrease in power per unit time, such as "increase of 5 kilowatts per second" or "decrease of 3 kilowatts per second". This slope value is jointly determined by the power control unit, the response characteristics of the power electronic devices, and the control algorithm inside the charging terminal, and the specific value is not limited in this application.

[0072] The control terminal can pre-store the hardware characteristic slope reference value for each charging terminal. This reference value is obtained through specialized calibration tests during the installation and deployment of the charging terminal, or during subsequent periodic maintenance. For example, in the calibration test, the control terminal issues standard power adjustment commands to the charging terminal and collects the power change process under ideal conditions, extracting the standard slope value reflecting the hardware characteristics of the terminal. This reference value will not be changed by communication data forgery or software-level tampering.

[0073] Understandably, for each charging terminal, the power change slope value in the dynamic response data is compared with the hardware characteristic slope benchmark value of that terminal stored in the database. This comparison can be a direct numerical comparison to observe the degree of difference between the two.

[0074] For example, a charging terminal's hardware characteristic slope baseline value, calibrated during installation, is "5.0 kW per second increase". During this power adjustment response, the terminal reported a power change slope value of "5.1 kW per second increase". The control terminal compares these two values, 5.1 kW / s and 5.0 kW / s, to determine if they match.

[0075] S302: If the power change slope value and the hardware characteristic slope benchmark value are greater than the second threshold, then the corresponding charging terminal is determined to be an abnormal charging terminal.

[0076] After comparing the power change slope value with the hardware characteristic slope reference value, the degree of difference between the two can be calculated. This difference can be an absolute difference, which is the absolute value of the reported slope value minus the reference slope value, or a relative difference, which is the percentage of the absolute difference to the reference value.

[0077] In this application, the second threshold is a pre-defined numerical limit used to distinguish between differences within the normal fluctuation range and significant abnormal differences. The setting of this threshold incorporates various factors, including hardware measurement errors, the influence of ambient temperature on power devices, and minor changes caused by the normal aging process. Under normal operating conditions, even if the charging terminal is functioning well, its actual power change slope may differ slightly from the reference value during calibration, but this difference is typically limited to within the second threshold.

[0078] Understandably, if the difference calculated by the control terminal exceeds the second threshold, it indicates that the power change slope of the charging terminal's current response has deviated significantly from its inherent hardware characteristics. This deviation could be due to a hardware failure in the charging terminal's power control unit, or it could be that the power data reported by the charging terminal has been tampered with, forging a slope value that does not conform to its hardware capabilities. When the difference between the power change slope value and the hardware characteristic slope benchmark value exceeds the second threshold, the control terminal can determine that the dynamic response data currently reported by the charging terminal is unreliable and identify it as an abnormal charging terminal.

[0079] Example 3 This embodiment proposes a method for secure monitoring of vehicle charging data. Unlike Embodiment 1, each charging terminal has a primary communication link and a backup communication link, which employ different physical communication media. For example, the primary communication link can use public 4G or 5G wireless communication, utilizing mobile communication networks for data transmission; while the backup communication link can use a dedicated fiber optic network, establishing an independent transmission channel through laid fiber optic lines. Alternatively, the primary communication link can use a Wi-Fi wireless local area network, while the backup communication link can use an industrial Ethernet wired network. Furthermore, the primary communication link can use power line carrier communication, utilizing the power line itself for data transmission, while the backup communication link can use independent wireless radio frequency communication.

[0080] In this embodiment, sending power adjustment commands to multiple charging terminals may include the following steps: S401: The same power adjustment command is sent to the same charging terminal simultaneously through the first communication link and the second communication link, and the charging terminal is instructed to report dynamic response data simultaneously through the first communication link and the second communication link.

[0081] S402: Receive the first dynamic response data and the second dynamic response data reported by the same charging terminal based on the first communication link and the second communication link respectively.

[0082] S403: Compare the first dynamic response data with the second dynamic response data item by item, including at least the comparison response timestamp, real-time power value sequence and power change slope value.

[0083] Understandably, the purpose of the comparison is to check whether the data reported by the same charging terminal for the same power adjustment event through two different paths are consistent.

[0084] For the response timestamp, the response timestamps can be extracted from the first dynamic response data and the second dynamic response data, and these two time values ​​can be directly compared. The response timestamp records the moment when the actual power of the charging terminal begins to change. Theoretically, the response timestamps of the same terminal reported through the two links should be exactly the same.

[0085] For a real-time power value sequence, the series of continuous power values ​​contained in the first dynamic response data can be compared point by point with the power value sequence in the second dynamic response data. This includes comparing whether the lengths of the two sequences are the same, whether the power values ​​at each corresponding time point are equal, and whether the curve shapes of the entire power change process match.

[0086] For the power change slope value, the power change slope value can be extracted from the two sets of data, that is, the rate of change of power from the initial value to the target value, and the two slope values ​​can be compared.

[0087] S404: If the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any item, the charging terminal is determined to be an abnormal charging terminal.

[0088] Consistency thresholds are numerical limits set for different data items to distinguish between minor differences within the normal error range and significant abnormal differences.

[0089] For example, for response timestamps, considering the possible slight differences in transmission delay between the two communication links, a time deviation threshold, such as 50 milliseconds, can be set; for real-time power values, considering the accuracy limitations of data acquisition and quantization, a power deviation threshold, such as 0.5 kilowatts, can be set; for power change slope values, considering the rounding errors in the calculation process, a slope deviation threshold, such as 0.2 kilowatts per second, can be set.

[0090] Specifically, the first response timestamp and the first real-time power value sequence in the first dynamic response data, and the second response timestamp and the second real-time power value sequence in the second dynamic response data can be obtained. The first response timestamp and the second response timestamp are compared. If the time difference between the two is greater than the preset time deviation threshold, the abnormal charging terminal is determined to be an abnormal charging terminal.

[0091] If the time difference between the first response timestamp and the second response timestamp does not exceed the time deviation threshold, the first real-time power value sequence and the second real-time power value sequence are compared in shape, and the dynamic time warping distance between the two power change curves is obtained. If the dynamic time warping distance is greater than the preset shape deviation threshold, the charging terminal is determined to be an abnormal charging terminal.

[0092] Understandably, once it is confirmed that the time difference between the first and second response timestamps does not exceed the preset time deviation threshold, it indicates that the two data points are basically consistent at the starting point of time. At this point, it is necessary to continue to examine whether the details of the power change process are consistent. The control terminal treats the first real-time power value sequence and the second real-time power value sequence as two curves of power changing over time, and compares the shapes of these two curves.

[0093] During morphological comparison, the control terminal employs a dynamic time warping algorithm to calculate the similarity between two curves. Dynamic time warping is an algorithm used to measure the similarity between two time series. Its characteristic is that it allows for non-linear scaling or misalignment of the two series along the time axis, thereby finding the optimal matching path between them. Using this algorithm, the dynamic time warped distance between two power change curves can be calculated. The smaller the distance value, the more similar the shapes of the two curves; the larger the distance value, the more significant the difference in shape between the two curves. Specific algorithms have been disclosed in relevant technical documents and are not limited in this application.

[0094] For example, suppose a charging terminal reports a first real-time power value sequence of [20.0, 22.0, 24.5, 27.0, 29.0, 30.0] via a first link, presenting a smoothly rising curve. A second real-time power value sequence reported via a second link is [20.0, 21.0, 24.0, 28.0, 29.5, 30.0]. Although the overall trend is also upward, the numerical change trajectory at several intermediate time points differs from the first sequence. The control terminal performs dynamic time warping calculations on these two sequences, obtaining a warping distance of 2.8, while the preset shape deviation threshold is 2.0. Since 2.8 is greater than 2.0, the shape difference between these two power change curves is determined to exceed the normal range; therefore, the charging terminal is identified as an abnormal charging terminal.

[0095] After obtaining the dynamic time warp distance, the control terminal compares it with a preset morphological deviation threshold. The morphological deviation threshold is a pre-set numerical limit used to distinguish between morphological differences within the normal error range and significant abnormal morphological differences. If the dynamic time warp distance is greater than the morphological deviation threshold, it indicates that there is a substantial difference in the morphology of the two power change curves, a difference that cannot be explained by normal measurement errors or sampling deviations.

[0096] Furthermore, if the dynamic time warping distance does not exceed the shape deviation threshold, and the difference between the power values ​​of the first real-time power value sequence and the second real-time power value sequence at the same time continuously exceeds the preset amplitude deviation threshold, the charging terminal is determined to be an abnormal charging terminal.

[0097] Even after confirming a high degree of overall similarity in the overall shape of the two curves using a dynamic time warping algorithm (meaning the dynamic time warping distance does not exceed a preset shape deviation threshold), it is not immediately possible to conclude that the two data points are completely identical. Overall shape similarity only indicates that the fluctuation trends of the two curves roughly match, but it does not guarantee that the power values ​​at every specific moment correspond accurately. At this point, the control terminal needs to bring the two curves back to the same time axis for precise comparison of point-by-point values.

[0098] Specifically, the first real-time power value sequence and the second real-time power value sequence are aligned in time. For each identical sampling moment, the absolute value of the difference between the first power value and the second power value is calculated to obtain the instantaneous power deviation value at that moment. Then, the control terminal sequentially checks these instantaneous power deviation values ​​along the time axis to observe whether there is a continuous time interval in which the instantaneous power deviation value exceeds a preset amplitude deviation threshold at every moment.

[0099] The amplitude deviation threshold is a pre-defined numerical limit used to distinguish between numerical fluctuations within the normal measurement error range and significant numerical deviations. Considering the inherent accuracy limitations of power measurement and the potential for minor errors during data quantization, allowing a certain range of instantaneous deviations is reasonable. However, if the deviation consistently exceeds this threshold, it indicates that while the two curves may appear similar in their overall trend, there is a persistent deviation in their specific values.

[0100] If the control terminal detects a continuous time interval in which the instantaneous power deviation value at each moment is greater than the amplitude deviation threshold, it determines that there is a numerical difference between the two sets of data of the charging terminal that cannot be explained by normal error, and identifies the charging terminal as an abnormal charging terminal.

[0101] This application proposes a method for monitoring vehicle charging data security, comprising: issuing power adjustment instructions containing target power values ​​and adjustment times to multiple charging terminals; acquiring response timestamps and real-time power value sequences reported by each terminal; obtaining the actual total power change curve from the power supply node; aligning and accumulating the real-time power value sequence based on the response timestamps to obtain the theoretical total power change curve; comparing the theoretical total power curve with the actual total power curve point by point to obtain power deviation values ​​at consecutive time points; if the power deviation value at consecutive time points is greater than a first threshold, determining that at least one terminal has reported abnormal data; and identifying the abnormal charging terminal associated with the power deviation value based on the contribution of each terminal's real-time power value sequence to the theoretical total power curve. This invention can accurately identify abnormal data sources.

[0102] Based on the same inventive concept, embodiments of this application also propose a vehicle charging data security monitoring system, including multiple charging terminals and a control terminal, wherein the multiple charging terminals share a single power supply node, and the system is configured as follows: A power adjustment command is sent to multiple charging terminals. The power adjustment command includes the target power value and the adjustment time, so that each charging terminal adjusts its output power to the target power value at the adjustment time. The dynamic response data reported by each charging terminal during the process of responding to the power adjustment command is obtained. The dynamic response data includes at least the response timestamp when the actual power of the corresponding charging terminal begins to change and the real-time power value sequence during the power change process. Obtain the actual total power change curve from the power supply node, and the actual total power change curve should at least cover the time period from the adjustment time to the last response time; The real-time power value sequence is time-aligned based on the response timestamp of each charging terminal, and the theoretical total power change curve is obtained by accumulating it moment by moment. By comparing the theoretical total power change curve with the actual total power change curve point by point, the power deviation values ​​at multiple consecutive time points are obtained. If there are consecutive time points where the power deviation value is greater than the first threshold, it is determined that at least one charging terminal under the power supply node has reported abnormal data. Based on the contribution of each charging terminal's real-time power value sequence to the power value at each moment of the theoretical total power change curve, abnormal charging terminals associated with power deviation values ​​are identified.

[0103] Based on the same inventive concept, embodiments of this application also propose an electronic device, which includes: At least one processor; and a memory communicatively connected to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executed by the at least one processor to enable the at least one processor to perform the vehicle charging data security monitoring method of the embodiments of this application.

[0104] In addition, to achieve the above objectives, embodiments of this application also propose a computer-readable storage medium storing a computer program, which, when executed by a processor, implements the vehicle charging data security monitoring method of embodiments of this application.

[0105] The following is a detailed introduction to the various components of the electronic device: In this context, the processor is the control center of the electronic device. It can be a single processor or a collective term for multiple processing elements. For example, a processor can be one or more central processing units (CPUs), an application-specific integrated circuit (ASIC), or one or more integrated circuits configured to implement embodiments of the present invention, such as one or more digital signal processors (DSPs), or one or more field-programmable gate arrays (FPGAs).

[0106] Alternatively, the processor can perform various functions of the electronic device by running or executing software programs stored in memory and by calling data stored in memory.

[0107] The memory is used to store the software program that executes the solution of the present invention, and the execution is controlled by the processor. The specific implementation method can be referred to the above method embodiment, which will not be repeated here.

[0108] Optionally, the memory can be read-only memory (ROM) or other types of static storage devices capable of storing static information and instructions, random access memory (RAM) or other types of dynamic storage devices capable of storing information and instructions, or electrically erasable programmable read-only memory (EEPROM), compact disc read-only memory (CD-ROM) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto. The memory can be integrated with the processor or exist independently and coupled to the processor through an interface circuit of an electronic device; the embodiments of the present invention do not specifically limit this.

[0109] A transceiver is used to communicate with network devices or with terminal devices.

[0110] Optionally, the transceiver may include a receiver and a transmitter. The receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.

[0111] Optionally, the transceiver can be integrated with the processor or exist independently and coupled to the processor through the router's interface circuit. This embodiment of the invention does not specifically limit this.

[0112] Furthermore, the technical effects of the electronic device can be referred to the technical effects of the data transmission method in the above method embodiments, and will not be repeated here.

[0113] It should be understood that the processor in the embodiments of the present invention can be a central processing unit (CPU), or it can be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0114] It should also be understood that the memory in the embodiments of the present invention can be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory. The non-volatile memory can be read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. The volatile memory can be random access memory (RAM), which is used as an external cache. By way of example, but not limitation, many forms of random access memory (RAM) are available, such as static RAM (SRAM), dynamic RAM (DRAM), synchronous DRAM (SDRAM), double data rate synchronous DRAM (DDRSDRAM), enhanced synchronous DRAM (ESDRAM), synchronous linked DRAM (SLDRAM), and direct rambus RAM (DRRAM).

[0115] The above embodiments can be implemented, in whole or in part, by software, hardware (such as circuits), firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, as a computer program product. A computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, all or part of the flow or function according to the embodiments of the present invention is generated. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. Computer instructions can be stored in a computer-readable storage medium or transmitted from one computer-readable storage medium to another. For example, computer instructions can be transmitted from one website, computer, server, or data center to another website, computer, server, or data center via wired (e.g., infrared, wireless, microwave, etc.) means. A computer-readable storage medium can 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 sets of available media. Available media can be magnetic media (e.g., floppy disks, hard disks, magnetic tapes), optical media (e.g., DVDs), or semiconductor media. Semiconductor media can be solid-state drives.

[0116] It should be understood that the term "and / or" in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. A and B can be singular or plural. Additionally, the character " / " in this article generally indicates an "or" relationship between the preceding and following related objects, but it can also represent an "and / or" relationship. Please refer to the context for a more accurate understanding.

[0117] In this invention, "at least one" means one or more, and "more than one" means two or more. "At least one of the following" or similar expressions refer to any combination of these items, including any combination of a single item or a plurality of items. For example, at least one of a, b, or c can represent: a, b, c, ab, ac, bc, or abc, where a, b, and c can be a single item or multiple items.

[0118] It should be understood that, in various embodiments of the present invention, the order of the above-mentioned process numbers does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0119] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this invention.

Claims

1. A method for monitoring the security of vehicle charging data, characterized in that, An application is made to a vehicle charging data security monitoring system, the system comprising multiple charging terminals and a control terminal, wherein the multiple charging terminals share a single power supply node, and the method is applicable to the control terminal, comprising: A power adjustment command is issued to multiple charging terminals. The power adjustment command includes a target power value and an adjustment time, as well as a power perturbation verification waveform generated by the control terminal and assigned to each charging terminal. The power perturbation verification waveform is used to superimpose a known fluctuation pattern with limited amplitude on the output power of the charging terminal during the power change process after the adjustment time, so that each charging terminal adjusts its output power to the target power value at the adjustment time. The dynamic response data reported by each charging terminal during the process of responding to the power adjustment command is obtained. The dynamic response data includes at least the response timestamp of the actual power of the corresponding charging terminal starting to change, the real-time power value sequence during the power change process, and the measured disturbance waveform corresponding to the power perturbation verification waveform extracted from the real-time power value sequence. The actual total power change curve is obtained from the power supply node, and the actual total power change curve covers at least the time period from the adjustment time to the last response time; The real-time power value sequence is time-aligned based on the response timestamp of each of the charging terminals, and the theoretical total power change curve is obtained by accumulating it moment by moment. By comparing the theoretical total power change curve with the actual total power change curve point by point, the power deviation values ​​at multiple consecutive time points are obtained. If there are consecutive power deviation values ​​greater than the first threshold at the aforementioned time points, it is determined that at least one charging terminal under the power supply node has reported abnormal data. Based on the contribution of the real-time power value sequence of each charging terminal to the power value at each moment of the theoretical total power change curve and the degree of matching between the measured disturbance waveform and the power micro-disturbance verification waveform, abnormal charging terminals associated with the power deviation value are determined. If the degree of matching between the measured disturbance waveform and the power micro-disturbance verification waveform of any charging terminal is lower than a preset verification threshold, the charging terminal is determined to be an abnormal charging terminal.

2. The method for monitoring vehicle charging data security according to claim 1, characterized in that, The dynamic response data also includes the power change slope value of the charging terminal during the power change process, and the method further includes: The control terminal compares the power change slope value with the corresponding hardware feature slope reference value of the charging terminal; If the power change slope value and the hardware feature slope benchmark value are greater than the second threshold, then the corresponding charging terminal is determined to be the abnormal charging terminal.

3. The method for monitoring vehicle charging data security according to claim 2, characterized in that, Based on the contribution of the real-time power value sequence of each charging terminal to the power value at each moment of the theoretical total power change curve, abnormal charging terminals associated with the power deviation value are determined, including: Obtain the power residual sequence of the theoretical total power change curve and the actual total power change curve at each time point; The correlation analysis is performed between the power residual sequence and the real-time power value sequence of each charging terminal; Based on the results of the correlation analysis, the charging terminal that is positively correlated with the power residual sequence is identified as the abnormal charging terminal.

4. The method for monitoring vehicle charging data security according to claim 3, characterized in that, The correlation analysis between the power residual sequence and the real-time power value sequence of each charging terminal includes: The real-time power value sequence corresponding to each charging terminal is shifted forward or backward by multiple different time offsets on the time axis; The real-time power value sequence after translation is multiplied point by point with the power residual sequence in the same time interval and then accumulated to obtain the similarity value corresponding to the time offset. Obtain the time offset that maximizes the similarity value and the corresponding maximum similarity value; If the maximum similarity value is greater than a preset similarity threshold, and the time offset corresponding to the maximum similarity value matches the power change start time indicated by the response timestamp of the charging terminal, then it is determined that the real-time power value sequence of the charging terminal is correlated with the power residual sequence, and the corresponding charging terminal is identified as the abnormal charging terminal associated with the power deviation value.

5. The method for monitoring vehicle charging data security according to claim 1, characterized in that, Each of the charging terminals has a primary communication link and a backup communication link, wherein the primary communication link and the backup communication link use different physical communication media to send power adjustment commands to multiple charging terminals, including: The same power adjustment command is simultaneously sent to the same charging terminal through the first communication link and the second communication link, and the charging terminal is instructed to simultaneously report the dynamic response data through the first communication link and the second communication link. The first dynamic response data and the second dynamic response data reported by the same charging terminal are received based on the first communication link and the second communication link, respectively. The first dynamic response data and the second dynamic response data are compared item by item, including at least the response timestamp, the real-time power value sequence and the power change slope value. If the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any one of them, then the charging terminal is determined to be the abnormal charging terminal.

6. The method for monitoring vehicle charging data security according to claim 5, characterized in that, If the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any item, the charging terminal is determined to be the abnormal charging terminal, including: Obtain the first response timestamp and the first real-time power value sequence from the first dynamic response data, and the second response timestamp and the second real-time power value sequence from the second dynamic response data; The first response timestamp is compared with the second response timestamp. If the time difference between the two is greater than a preset time deviation threshold, the abnormal charging terminal is determined to be the abnormal charging terminal.

7. A method for monitoring vehicle charging data security according to claim 6, characterized in that, If the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any item, then the charging terminal is determined to be the abnormal charging terminal, including: If the time difference between the first response timestamp and the second response timestamp does not exceed the time deviation threshold, the first real-time power value sequence and the second real-time power value sequence are morphologically compared, and the dynamic time warping distance between the two power change curves is obtained. If the dynamic time warping distance is greater than the preset morphological deviation threshold, then the charging terminal is determined to be the abnormal charging terminal.

8. A method for monitoring vehicle charging data security according to claim 7, characterized in that, If the difference between the first dynamic response data and the second dynamic response data exceeds a preset consistency threshold in any item, then the charging terminal is determined to be the abnormal charging terminal, including: If the dynamic time warping distance does not exceed the shape deviation threshold, and the difference between the power values ​​of the first real-time power value sequence and the second real-time power value sequence at the same time continuously exceeds the preset amplitude deviation threshold, the charging terminal is determined to be the abnormal charging terminal.

9. A vehicle charging data security monitoring system, characterized in that, The system includes multiple charging terminals and a control terminal, with the multiple charging terminals sharing a single power supply node. The system is configured as follows: A power adjustment command is sent to a plurality of the charging terminals. The power adjustment command includes a target power value and an adjustment time, so that each of the charging terminals adjusts its output power to the target power value at the adjustment time. The dynamic response data reported by each of the charging terminals during the process of responding to the power adjustment command is obtained, wherein the dynamic response data includes at least the response timestamp of the actual power of the corresponding charging terminal starting to change and the real-time power value sequence during the power change process. The actual total power change curve is obtained from the power supply node, and the actual total power change curve covers at least the time period from the adjustment time to the last response time; The real-time power value sequence is time-aligned based on the response timestamp of each of the charging terminals, and the theoretical total power change curve is obtained by accumulating it moment by moment. By comparing the theoretical total power change curve with the actual total power change curve point by point, the power deviation values ​​at multiple consecutive time points are obtained. If there are consecutive power deviation values ​​greater than the first threshold at the aforementioned time points, it is determined that at least one charging terminal under the power supply node has reported abnormal data. Based on the contribution of the real-time power value sequence of each charging terminal to the power value at each moment of the theoretical total power change curve, the abnormal charging terminal associated with the power deviation value is determined.

10. An electronic device, characterized in that, include: At least one processor; And, a memory communicatively connected to at least one of the processors; The memory stores instructions that can be executed by at least one of the processors, which are executed by at least one of the processors to enable at least one of the processors to perform a vehicle charging data security monitoring method as claimed in any one of claims 1-8.

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