A flywheel energy storage system communication anti-interference simulation detection method

Abstract

The present application relates to the technical field of communication anti-interference detection, in particular to a flywheel energy storage system communication anti-interference simulation detection method, comprising the following steps: obtaining torque data to generate disturbance characteristics, comparing interference levels to inject electromagnetic signals, monitoring error code statistics and delay errors, analyzing communication levels to generate link anti-interference simulation detection results. In the present application, the disturbance characteristics are constructed by extracting torque mutation points and guided to inject interference frequency bands, forming the causal linkage of disturbance response and electromagnetic interference, and enhancing the pertinence and effectiveness of interference injection; the fluctuation trend of the error rate and the delay peak value are identified by the sliding window to dynamically depict the communication quality degradation process; the synchronization error is calculated by combining the interference spectrum and the error time point to improve the monitoring ability of the time consistency change of the link; the grade mapping is carried out on the basis of multi-dimensional indexes to realize the transformation of anti-interference performance from static test to dynamic evaluation, and to improve the test granularity, adaptability and accuracy.

Description

Technical Field

[0001] This invention relates to the field of communication anti-interference detection technology, and in particular to a method for simulating and detecting communication anti-interference in flywheel energy storage systems. Background Technology

[0002] The field of communication anti-interference detection technology encompasses technical means for monitoring, analyzing, and identifying abnormal factors such as electromagnetic interference, signal distortion, and interference noise in power systems, industrial control networks, intelligent devices, and related communication links. Its core content lies in improving the communication reliability of systems in complex electromagnetic environments by establishing communication link stability models, collecting communication signal status data, introducing interference source signals for comparative testing, and evaluating anti-interference performance levels. It covers anti-interference performance testing methods in communication systems, interference injection simulation methods, data acquisition and comparison mechanisms, and experimental evaluation frameworks, and is widely used in the evaluation and verification of communication stability of related equipment and systems in high-reliability communication scenarios such as power systems, rail transit, and aerospace.

[0003] Among them, the communication anti-interference simulation test method for flywheel energy storage systems refers to a technical solution for testing the anti-interference performance of communication lines between flywheel energy storage devices and monitoring communication systems. It mainly targets the testing and analysis of data transmission errors and signal distortion caused by electromagnetic interference. It covers specific aspects such as setting up communication terminal equipment in the experimental environment, injecting high-frequency disturbance signals into the communication lines through a power disturbance generator, collecting data transmission status in real time under different interference intensities and comparing the communication bit error rate, and judging the anti-interference capability of the communication link based on the bit error rate. It adopts methods such as setting interference level simulation, electromagnetic injection method, and bit error rate monitoring and analysis to carry out the whole process of testing and verification.

[0004] In existing flywheel energy storage system communication anti-interference simulation testing processes, there is a lack of independent perception capability for disturbance behavior. Interference injection is not based on the equipment operating status and actual disturbance amplitude, but only relies on preset electromagnetic levels for equivalent testing. This results in a lack of targeted and dynamic adjustment mechanisms for injection strategies, making it difficult to match the changes in interference impact under real working scenarios. Bit error rate statistics are often based on sampling for fixed durations or static measurement segments, failing to identify sudden or phased changes in bit error generation, affecting the analysis of the response characteristics of the communication link under disturbance excitation, and posing a risk of misjudging the stability level. Timing errors are not included in the detection parameter system, resulting in the inability to effectively expose communication delays or synchronization offsets, weakening the detection mechanism's sensitivity to subtle time-related differences. Anti-interference assessment results mostly rely on single indicators of bit error rate statistics, and the assessment model lacks joint analysis between the disturbance background and communication status, making it difficult to quantify the composite impact of electromagnetic interference on the performance of various dimensions of the communication link, reducing the test accuracy and applicability. Summary of the Invention

[0005] The purpose of this invention is to overcome the shortcomings of existing technologies and propose a method for simulating and detecting communication anti-interference in flywheel energy storage systems.

[0006] To achieve the above objectives, the present invention adopts the following technical solution: a method for simulating and detecting communication anti-interference in flywheel energy storage systems, comprising the following steps:

[0007] S1: Obtain the torque sampling data stream in the flywheel energy storage module, determine the sampling period and calculate the angular acceleration sequence, identify the maximum change point through differential peak detection, extract the corresponding timestamp and acceleration value, and generate dynamic torque disturbance characteristics;

[0008] S2: Based on the dynamic torque disturbance characteristics, compare with the standard electromagnetic interference level, identify the frequency band that first exceeds the EMC immunity threshold, inject an equivalent electromagnetic interference signal into the communication link, and generate an interference injection spectrum identifier.

[0009] S3: Monitor the timing data of the bit error rate at the receiving end, construct a sliding time window after the injection of the equivalent electromagnetic interference signal, count the CRC check failures within the window, identify the period of maximum bit error and calculate the average bit error delay, and generate communication quality degradation characteristics.

[0010] S4: Based on the timestamps of the interference injection spectrum identifier and the communication quality degradation characteristics, calculate the time synchronization error, compare it with the standard time accuracy threshold, and generate a response delay index;

[0011] S5: Perform joint EMC criterion analysis based on the response delay index and the dynamic torque disturbance characteristics, map the communication reliability level, and generate link anti-interference simulation test results.

[0012] As a further aspect of the present invention, the dynamic torque disturbance characteristics include disturbance timestamp, acceleration change amplitude, and angular acceleration peak frequency; the interference injection spectrum identifier includes interference frequency band, radiation field strength level, and electromagnetic interference type; the communication quality degradation characteristics include peak bit error rate, average bit error delay, and CRC failure count; the response delay index includes time synchronization error value, out-of-tolerance duration, and maximum response delay; and the link anti-interference simulation detection results include anti-interference level, communication reliability level, and EMC compliance judgment result.

[0013] As a further aspect of the present invention, the specific steps for obtaining the dynamic torque disturbance characteristics are as follows:

[0014] S111: Obtain the torque sampling data stream in the flywheel energy storage module, identify the time series and sampling period corresponding to each data point, perform differential processing on all data sequences, statistically analyze the angle change value and time difference between the current time point and the previous time point, and calculate the angular acceleration value sequence to obtain the angular acceleration sequence value;

[0015] S112: Based on the angular acceleration sequence values, calculate the angular acceleration difference between any data point and its adjacent points, compare all differences with a set standard rate of change threshold, filter out all extreme points that exceed the threshold, and extract the corresponding time points and angular acceleration values ​​to obtain the time acceleration pair that exceeds the threshold.

[0016] S113: Based on the aforementioned over-threshold time acceleration pairs, calculate the absolute value of the angular acceleration difference, the time interval, and the acceleration slope value for all changing time points within adjacent intervals, calculate the disturbance amplitude change rate sequence, obtain the data point timestamp and acceleration value corresponding to the maximum disturbance amplitude, and generate dynamic torque disturbance characteristics.

[0017] As a further aspect of the present invention, the specific steps for obtaining the interference injection spectrum identifier are as follows:

[0018] S211: Based on the dynamic torque disturbance characteristics, obtain the frequency component distribution of the corresponding disturbance event in the time domain, perform a fast Fourier transform operation to obtain the frequency sequence, compare the disturbance intensity of each frequency point with the corresponding frequency point of the EMC immunity threshold curve, determine the starting frequency value of the first disturbance intensity exceeding the threshold of the corresponding frequency point, and generate the over-threshold frequency band value.

[0019] S212: Based on the above-threshold frequency band value, match the radiation test field strength range specified by the interference injection, configure the injection time period, configure the interference coupling parameters for different communication channels, insert the corresponding interference signal into each communication link according to the injection frequency and time interval, and obtain the injection disturbance sequence value.

[0020] S213: Based on the injected disturbance sequence value, statistically analyze the signal changes generated by the injected interference in each channel within the action period, calculate the maximum amplitude response index caused by the interference in each frequency band, identify the frequency range with the largest response and the corresponding time segment, and generate an interference injection spectrum identifier.

[0021] As a further aspect of the present invention, the specific steps for obtaining the communication quality degradation characteristics are as follows:

[0022] S311: Monitor the timing data of the bit error rate at the receiving end. After the equivalent electromagnetic interference signal is injected, record the number of bit errors per unit time and form a bit error sequence in time order. Divide the window segments and calculate the bit error rate. By traversing all window bit error rates, determine all sets that exceed the judgment threshold and obtain the set value of high bit error window.

[0023] S312: Based on the set value of the high bit error rate window, count the cumulative number of CRC check failures within the corresponding period of the window and store them in the fault count sequence. Count the error bits in each window and record the first and last occurrence times. Obtain the start and end time interval of the maximum bit error rate window and generate the maximum bit error rate period interval value.

[0024] S313: Based on the maximum bit error period interval value, extract the actual time point and error length of the bit error event within the corresponding time period, accumulate the interval of each event and obtain its average value, calculate the average bit error delay index, and combine it with its continuous impact on communication quality to generate communication quality degradation characteristics.

[0025] As a further aspect of the present invention, the specific steps for obtaining the response latency indicator are as follows:

[0026] S411: Based on the timestamps of the interference injection spectrum identifier and the communication quality degradation feature, extract the occurrence time of the corresponding interference triggering event and the start time of the communication response degradation event, perform time-series comparison on each pair of interference frequency bands and communication anomaly features, and construct the interference-response time difference sequence to obtain the interference-response time difference sequence value.

[0027] S412: Based on the interference response time difference sequence value, obtain the time difference between all interference triggers and communication responses, record the magnitude and frequency of each time difference deviating from the average error in the whole sequence, compare it with the standard maximum synchronization deviation value, identify the segments with abnormal fluctuations in duration, and obtain the time synchronization error measurement result.

[0028] S413: Based on the time synchronization error measurement results, the time period corresponding to the error value is compared with the standard error limit item by item. All error segments are checked for exceeding the limit and the total number of segments and the proportion of abnormal segments are counted. The response stability of the entire communication link is judged and analyzed by the maximum error value and the exceeding limit ratio, and a response delay index is established.

[0029] As a further aspect of the present invention, the specific steps for obtaining the link anti-interference simulation detection results are as follows:

[0030] S511: Based on the response delay index and the dynamic torque disturbance characteristics, construct the interference response delay sequence and the disturbance amplitude sequence, perform time alignment processing, set the maximum tolerance window, filter joint data pairs with time differences within the tolerance range, perform data mapping between interference triggering and communication response, and obtain disturbance-delay mapping trend records.

[0031] S512: Based on the disturbance-delay mapping trend record, construct a two-dimensional data space according to the change range of disturbance amplitude and delay response, jointly classify the disturbance value and response value, count the frequency and range of each type of data point, mark the corresponding level classification identifier, and obtain the reliability level classification result;

[0032] S513: Based on the reliability level classification results, match the various classification labels according to the reliability level standards in the communication standard, and assign them to the corresponding level categories. Select the level with the highest proportion in all data as the anti-interference performance level under the current link state, and establish the link anti-interference simulation detection results.

[0033] Compared with the prior art, the advantages and positive effects of the present invention are as follows:

[0034] In this invention, disturbance features are constructed by extracting torque mutation points and guiding interference frequency band injection, forming a causal linkage between disturbance response and electromagnetic interference, thereby enhancing the targeting and effectiveness of interference injection; the bit error rate fluctuation trend and delay peak are identified by a sliding window, realizing a dynamic characterization of the communication quality degradation process; the synchronization error is calculated by combining the interference spectrum and bit error time points, improving the monitoring capability of link time consistency changes; and a level mapping is performed based on multi-dimensional indicators, realizing the transformation of anti-interference performance from static testing to dynamic evaluation, improving the granularity, adaptability and accuracy of testing. Attached Figure Description

[0035] Figure 1 This is a flowchart of the main steps of the present invention;

[0036] Figure 2 This is a flowchart of the steps for obtaining dynamic torque disturbance characteristics according to the present invention;

[0037] Figure 3 This is a flowchart of the steps for obtaining the interference injection spectrum identifier in this invention;

[0038] Figure 4 This is a flowchart of the steps for obtaining communication quality degradation characteristics according to the present invention;

[0039] Figure 5 This is a flowchart of the steps for obtaining the response delay index in this invention;

[0040] Figure 6This is a flowchart of the steps for obtaining the link anti-interference simulation detection results of the present invention. Detailed Implementation

[0041] To make the objectives, technical solutions, and advantages of this invention clearer, the invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative and not intended to limit the invention.

[0042] In the description of this invention, it should be understood that the terms "length," "width," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientation or positional relationships, are based on the orientation or positional relationships shown in the accompanying drawings and are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of the invention. Furthermore, in the description of this invention, "a plurality of" means two or more, unless otherwise explicitly specified.

[0043] Please see Figure 1 A method for simulating and testing communication anti-interference in flywheel energy storage systems includes the following steps:

[0044] S1: Obtain the torque sampling data stream in the flywheel energy storage module, determine the sampling period and calculate the angular acceleration sequence, identify the maximum change point through differential peak detection (a mechanical vibration detection method conforming to ISO10816 standard), extract the corresponding timestamp and acceleration value, and generate dynamic torque disturbance characteristics;

[0045] S2: Based on the dynamic torque disturbance characteristics, compare with the electromagnetic interference level of the IEC61000-4-8 standard, identify the frequency band that first exceeds the EMC immunity threshold (the electromagnetic compatibility test limit set according to the IEC61000-4 series standards), inject an equivalent electromagnetic interference signal (radiated immunity test signal conforming to the ISO11452-2 standard) into the communication link, and generate an interference injection spectrum identifier;

[0046] S3: Monitor the timing data of the bit error rate (BER) at the receiver, construct a sliding time window (500ms according to the communication quality assessment window defined by the 3GPP TS36.104 protocol) after the equivalent electromagnetic interference signal is injected, count the CRC check failures within the window (following the cyclic redundancy check mechanism of the IEEE 802.3 standard), identify the period of maximum bit error and calculate the average bit error delay, and generate communication quality degradation characteristics.

[0047] S4: Based on the timestamps of the interference injection spectrum identifier and communication quality degradation characteristics, calculate the time synchronization error (TSE), compare it with the IEEE 1588 standard time accuracy threshold (≤1μs error requirement specified by the precision clock synchronization protocol), and generate a response delay index;

[0048] S5: Perform joint EMC criterion analysis based on response delay index and dynamic torque disturbance characteristics, map to IEC61850-90-5 communication reliability level (the 4-level reliability classification defined by the power system communication standard), and generate link anti-interference simulation test results.

[0049] Dynamic torque disturbance characteristics include disturbance timestamp, acceleration change amplitude, and peak frequency of angular acceleration; interference injection spectrum identifiers include interference frequency band, radiation field strength level, and electromagnetic interference type; communication quality degradation characteristics include peak bit error rate, average bit error delay, and number of CRC failures; response delay indicators include time synchronization error value, out-of-tolerance duration, and maximum response delay; and link anti-interference simulation test results include immunity level, communication reliability level, and EMC compliance judgment results.

[0050] Please see Figure 2 The specific steps of S1 are as follows:

[0051] S111: Obtain the torque sampling data stream in the flywheel energy storage module, identify the time series and sampling period corresponding to each data point, perform differential processing on all data sequences, statistically analyze the angle change value and time difference between the current time point and the previous time point, and calculate the angular acceleration value sequence to obtain the angular acceleration sequence value;

[0052] To obtain the torque sampling data stream from the flywheel energy storage module, it is necessary to call the angular velocity data sequence recorded in real time by the sensor nodes. The data sampling frequency is set to 200Hz, which means 200 data points are recorded per second, with a sampling period of 5ms. The sampled data is represented in array form. During data acquisition, the difference in angular velocity between any two adjacent data points is defined as... The time difference at each point in time is defined as Calculate the angular acceleration value using the formula For example, when ,but , The above operation needs to be performed on all data points to organize them into a sequence. This dataset serves as the foundation for subsequent perturbation identification. During data processing, it should be free of frame drops or abnormal zero values. If any such data is found... Data from consecutive sampling periods exceeding two cycles should be removed to avoid affecting trend analysis. Furthermore, if the continuous sampling time exceeds 60 seconds, the data should be segmented every minute to prevent system storage overload or slow processing due to excessive data volume. In actual sampling, a flywheel simulation device was used with an angular velocity range of 100 rad / s to 600 rad / s. Example data is as follows:

[0053] Table 1. Examples of Angular Velocity and Acceleration Calculations

[0054]

[0055] As shown in Table 1, with a constant sampling interval of 0.005 seconds, the angular acceleration sequence can be obtained item by item using the adjacent difference method. For the interval of sudden change in angular velocity, its The value changes significantly, and this type of numerical change sequence is the angular acceleration sequence value.

[0056] S112: Based on the angular acceleration sequence values, calculate the angular acceleration difference between any data point and its neighboring points, compare all differences with a set standard rate of change threshold, filter out all extreme points that exceed the threshold, and extract their corresponding time points and angular acceleration values ​​to obtain the time acceleration pairs that exceed the threshold.

[0057] Based on the angular acceleration sequence values ​​and using the differences between adjacent terms within the sequence as a basis, a continuous difference operation is performed. The difference operation is defined as follows: The obtained difference sequence is compared with the change threshold given by the ISO 10816 standard. ISO 10816 specifies that the threshold for identifying sudden changes in vibration acceleration is generally not less than 500 rad / s. 2 In this embodiment, it is set to 600 rad / s 2 ,like If a sudden change occurs at that time point, then that time point is considered to have occurred, and the time point is recorded. Corresponding The values ​​form a disturbance pair, which may occur during actual monitoring. ,but To determine if a data point meets the mutation condition, all data points that meet the condition are selected to form a change sequence. Assume the following perturbation points are identified in a sampled dataset:

[0058] Table 2 Data on abrupt changes in angular acceleration

[0059]

[0060] As shown in Table 2, a total of 4 change points met the set threshold conditions. The judgment process strictly relied on comparing the absolute value of the difference with the threshold of 600, avoiding subjective judgment or fuzzy standards. These change points were extracted using an index-based filtering method. and The final output is the change over-threshold time acceleration pair.

[0061] S113: Based on the changing over-threshold time acceleration pairs, calculate the absolute value of the angular acceleration difference between adjacent intervals at all changing time points, the time interval between changes, and the acceleration slope value, using the following formula:

[0062] ;

[0063] Calculate the rate of change sequence of disturbance amplitude The timestamp and acceleration value of the data point corresponding to the maximum disturbance amplitude are obtained to generate dynamic torque disturbance characteristics, wherein... Representing the Angular acceleration values ​​at each point of change This represents the angular acceleration value at the previous point of change. Representing the The time interval between perturbation pairs Representing the The cumulative value of the sampling period of the segment. Representing the System response delay correction value in segment data sampling This represents the number of all perturbation points that satisfy the threshold condition.

[0064] Based on the pairs of accelerations exceeding the threshold time, the ratio of the angular acceleration difference to its time interval is calculated for each pair. This, combined with the system response delay and the cumulative value of the sampling period, forms a sequence of disturbance amplitude change rates. This is the system response delay correction value, set in practice. s, Substitute the sample data from Table 2 into the calculation, where:

[0065] , (The initial state is 0 by default);

[0066] , , ;

[0067] , , , ;

[0068] , , , ;

[0069] , , , ;

[0070] Calculate each item in turn:

[0071] ;

[0072] ;

[0073] ;

[0074] ;

[0075] final:

[0076]

[0077] This result indicates that the disturbance peak is located at Corresponding data points, i.e. At time t, the angular acceleration is 2400 rad / s². 2 This indicates that the disturbance is strongest at that point, ultimately generating dynamic torque disturbance characteristics.

[0078] The disturbance amplitude change rate sequence represents the comprehensive reflection of the degree of angular acceleration jump between various torque disturbance points and their corresponding time changes during the operation of the flywheel energy storage module. This sequence not only quantifies the abrupt change amplitude of the disturbance intensity, but also combines the system response delay and sampling period to reflect the coupling relationship between the density of the disturbance on the time axis and the system response characteristics, thereby constructing a dynamic change curve that can be used to continuously monitor the torque disturbance trend. Each item in this sequence corresponds to the joint influence of a disturbance behavior in both spatial (acceleration) and temporal dimensions. The overall sequence forms the evolution trajectory of the disturbance activity, which is convenient for identifying abnormal and violent fluctuations and their occurrence intervals, and has clear time positioning and disturbance significance indication capabilities.

[0079] The formula's operational logic comprehensively reflects the intensity and temporal characteristics of angular acceleration changes between disturbance points. By summing the squared difference of the numerator with the square of the time interval and then taking the square root, the geometric distance of the disturbance in both acceleration and time dimensions is formed, which can characterize the overall amplitude change trend of the disturbance jump. The denominator adds the cumulative value of the sampling period with the system response delay correction value to form a comprehensive reflection of the disturbance point on the system response time axis. The overall division structure is used to normalize the sensitivity of the disturbance intensity to the time effect. Among them, the square term of the acceleration difference emphasizes the dominance of the acceleration jump, the square term of the time interval ensures the validity of the continuous judgment of the jump, the square root operation ensures the uniformity of units and distance properties, the overall absolute value operation avoids the influence of positive and negative changes on the cumulative disturbance judgment, and the summation operation combines the total amount of each disturbance contribution for the final judgment of the total disturbance amplitude, ensuring that the output value has complete physical meaning and continuous evolution capability.

[0080] Please see Figure 3 The specific steps of S2 are as follows:

[0081] S211: Based on the dynamic torque disturbance characteristics, obtain the frequency component distribution of the corresponding disturbance event in the time domain, perform a fast Fourier transform operation to obtain the frequency sequence, compare the disturbance intensity of each frequency point with the corresponding frequency point of the EMC immunity threshold curve, determine the starting frequency value of the first disturbance intensity exceeding the threshold of the corresponding frequency point, and generate the over-threshold frequency band value.

[0082] Based on the dynamic torque disturbance characteristics, to obtain the disturbance frequency band and interference intensity within the frequency distribution range, it is necessary to first extract the time index of each disturbance event, and then construct a symmetrical time window by extending 10 ms forward and backward from that time point. The angular acceleration sequence data within this window is normalized and converted to the frequency domain using a Fast Fourier Transform. The main peak position is located in the spectrum and the corresponding frequency value is recorded. After frequency extraction, it is converted to the unit Hz and recorded as the disturbance frequency. Then, based on the EMC immunity threshold curve given in the IEC 61000-4-8 standard, obtain the following information: Standard threshold electric field strength at the corresponding frequency Set according to the reference table specified in the standard. hour The actual disturbance intensity and A comparison is made to determine whether the standard limit is exceeded. If multiple disturbance frequencies meet this condition, only the frequency that first exceeds the limit is recorded as the representative frequency band. This determination requires calculating the difference for each frequency point sequentially. , select the first This is the target frequency point; in the example, if... , , ,and , , Then filter out The corresponding 120Hz is the first over-threshold frequency value; the final over-threshold frequency value is obtained.

[0083] S212: Based on the frequency value of the over-threshold band, match the radiation test field strength range specified by the interference injection, configure the injection time period, configure the interference coupling parameters for different communication channels, insert the corresponding interference signal into each communication link according to the injection frequency and time interval, and obtain the injected disturbance sequence value.

[0084] Based on the over-threshold frequency value, and matching the interference injection radiation intensity value specified in ISO 11452-2 standard, the injection signal frequency is set within the selected frequency band range. Set the injection time as The signal amplitude range is selected as to Between these values, the upper limit of the amplitude reference standard is set to The injected signal is determined to be a sine wave. The signal injection operation is completed within a selected period, and the number of communication links is considered. Configure the corresponding number of interference synchronization signal generator channels, such as setting... Then, signals with the same frequency but staggered start and end times were injected into the four channels respectively, and the timing information and signal strength change values ​​of each injection event were recorded. During the injection process of each channel, the disturbed response signal samples were collected in 2 ms increments. The sample data obtained are shown in the table below:

[0085] Table 3. Examples of Injected Disturbance Signals

[0086]

[0087] As shown in Table 3, each channel completes the injection operation in a staggered manner, and forms a sequence perturbation mode by signal superposition, and finally obtains the injected perturbation sequence value.

[0088] S213: Based on the injected disturbance sequence value, statistically analyze the signal changes generated by the injected interference in each channel within the action period, calculate the maximum amplitude response index caused by the interference in each frequency band, identify the frequency range with the largest response and the corresponding time segment, and generate an interference injection spectrum identifier.

[0089] Based on the injected perturbation sequence value, the received signal change data corresponding to the injection time period are read by channel, and the amplitude peak and energy distribution range are extracted. The start time, maximum peak time and end time of signal change are recorded in each frequency band. The duration of signal response is calculated with a sampling interval of 2ms. For each data segment, determine whether the maximum disturbance intensity is greater than 3 times the standard value of the mean power density. For example, if the mean power density in channel 1 is... The threshold is then set to The detected value at any given time This means that a response is marked as valid. Based on this judgment, valid response points within each channel frequency band are extracted and their corresponding frequency indices are recorded. The index frequency of the maximum response intensity in all frequency bands is output as the feature identifier, and finally the interference injection spectrum identifier is obtained.

[0090] Please see Figure 4 The specific steps of S3 are as follows:

[0091] S311: Monitor the timing data of the bit error rate at the receiving end. After the equivalent electromagnetic interference signal is injected, record the number of bit errors per unit time and form a bit error sequence in time order. Divide the window segments and calculate the bit error rate. By traversing all window bit error rates, determine all sets that exceed the judgment threshold and obtain the set value of high bit error window.

[0092] The timing data of the bit error rate at the receiving end is monitored. After injecting an equivalent electromagnetic interference signal, the bit error count sequence output by the receiving module is directly called. This sequence is continuously collected with a time granularity of 10ms, forming a sequence of length [missing information]. Error timing array A sliding window with a length of 500ms is constructed, sliding once every 50ms to ensure sequence coverage. The number of bit errors of all bits within the sliding window is summed to obtain the total number of bit errors for each window. Then, divide this total by the total number of bits received within the window to calculate the bit error rate for each window. ,like If the received data bits are 100,000 and the error rate is 180 within a 500ms window, then the window is recorded as an error window. If the filtering criteria are met, the entire error sequence window set is traversed in this manner, and a total of [number] sequences are extracted. Identify and record the start and end times of any abnormal windows that meet the specified conditions. The results are presented in [the format of the data]. The data is stored in a specific format, and the set of high error rate windows is ultimately obtained.

[0093] S312: Based on the set value of high bit error rate windows, count the cumulative number of CRC check failures within the corresponding period of the window and store them in the fault count sequence. Count the error bits in each window and record the first and last occurrence times. Obtain the start and end time interval of the maximum bit error rate window and generate the maximum bit error rate period interval value.

[0094] Based on the high error rate window set value, CRC check failure counts are performed on the erroneous data within each abnormal window. Using the IEEE 802.3 standard's cyclic redundancy check rules, a polynomial remainder matching operation is performed on each bit group. If the set generator polynomial structure is not met, it is determined to be an erroneous block. The cumulative number of erroneous blocks within the entire window is counted and used as the CRC error value for that window. Then iterate through all The value identifies the window index where the maximum error value is located. The corresponding start and end times are recorded as to Calculate the time difference This refers to the period of concentrated bit error. In the example, if the CRC failure counts of windows 1 to 5 are 8, 15, 22, 12, and 9 respectively, then window 3 has the largest error rate, with a start and end time of 1.0 to 1.5 seconds and a time difference of 0.5 seconds. This gives us the maximum error period range.

[0095] S313: Based on the maximum bit error period interval value, extract the actual time point and error length of the bit error event within the corresponding time period, accumulate the intervals of each event and obtain their average value, using the formula:

[0096] ;

[0097] Calculate the average delay index of bit error rate And, combined with its continuous impact on communication quality, communication quality degradation characteristics are generated, among which, For the first The time interval between the occurrence of each bit error event For all The average value, For the first Duration of the error in each event This represents the total number of events within the maximum error period.

[0098] Based on the maximum error period range, count the number of error events within that period. Extract the time points of each error event. Duration First, calculate the average interval of all events. Then for each and Take the absolute value of the difference between them to form a set of fluctuation distances, and then combine them into a set. Accumulate and count the number of events simultaneously. The average delay metric for bit error events is obtained using the following formula, assuming... Second, Second, seconds, then:

[0099] ;

[0100] ;

[0101] ;

[0102] This result represents the average bit error delay within the bit error period, which is used to measure the overall communication stability fluctuation level and ultimately generate communication quality degradation characteristics.

[0103] Table 4 Error Event Delay Statistics Table

[0104]

[0105] As shown in Table 4, the bit error events fluctuate significantly. The superimposed delay value and absolute deviation calculation results are used to deduce the degree of communication degradation, thus constituting the communication quality degradation characteristics in the system.

[0106] The average bit error rate (AER) is a composite measure of the dispersion and sustained impact of bit error events over time in a communication system after being subjected to electromagnetic interference. This indicator reflects not only the frequency and distribution of bit error events within a monitoring period but also the duration of each error. By combining the time interval deviation and the duration of the error, it characterizes the anti-interference stability of the communication link under interference scenarios. A high AER indicates that bit error events occur frequently and exhibit strong temporal non-uniformity, while also having a long cumulative impact period. This reflects fluctuations and degradation risks in communication quality within this range. Therefore, this indicator can serve as an important reference for identifying communication stability fluctuations and fault trends.

[0107] The formula's operational logic lies in comprehensively measuring the temporal volatility and sustained impact of bit error events during communication. First, it compares the occurrence time of each bit error event with the overall average time interval, calculates the absolute difference, and sums them. This reflects the dispersion of bit error events in time distribution; a larger value indicates less concentrated bit error events and more severe fluctuations. Second, it sums the durations of all bit error events to quantify their cumulative impact on the link's continuous flow. This sum, combined with the temporal dispersion, provides the basis for calculating the total impact of the overall degradation index. In the denominator, the sum of the number of events k and its square root is used as a normalization factor, where the number of events k represents the total scale of the events. This is used to reduce the denominator value to suppress the average delay under low event frequency, so that even when the number of bit error events is small but the fluctuation is strong, the formula can still reflect the significant degradation of communication quality and thus be sensitive to short-term high-intensity disturbances. Therefore, the formula outputs a delay characteristic index that can accurately reflect the trend of declining communication quality by weighting the bit error fluctuation intensity, the total bit error duration and the event scale.

[0108] Please see Figure 5 The specific steps of S4 are as follows:

[0109] S411: Based on the timestamps of the interference injection spectrum identifier and the communication quality degradation characteristics, extract the occurrence time of the corresponding interference triggering event and the start time of the communication response degradation event, perform time-series comparison on each pair of interference frequency bands and communication anomaly characteristics, and construct the interference-response time difference sequence to obtain the interference-response time difference sequence value.

[0110] Based on the timestamps of the interference injection spectrum identifier and the communication quality degradation characteristics, the peak time of the spectrum triggered by the interference is extracted respectively. Start time of communication anomaly By comparing the recording formats and precision differences between the two types of time data, their time axes were unified to a millisecond precision format under the same time base. Interference triggering events were paired with corresponding communication quality degradation events. During the matching process, a maximum time tolerance of 2 seconds was set. If an interference event failed to match its corresponding communication response event within 2 seconds, that interference point was removed. All valid interference-response pairings were then selected, and the time difference was calculated for each pair of data. Forming a time difference series If in a certain group and ,but Complete all data transformation operations in this manner, and organize the results into a tabular format, as shown in the following example:

[0111] Table 5. Examples of Interference-Response Time Difference

[0112]

[0113] As shown in Table 5, each interference event has a corresponding communication response time point. By calculating and summarizing the time differences, the interference response time difference sequence value is finally obtained.

[0114] S412: Based on the interference response time difference sequence value, obtain the time difference between all interference triggers and communication responses, record the magnitude and frequency of each time difference deviating from the average error in the whole sequence, compare it with the standard maximum synchronization deviation value, identify the segments with abnormal duration fluctuations, and obtain the time synchronization error measurement result.

[0115] Based on the interference response time difference sequence values, all time difference data within the sequence are processed. First, the average, maximum, minimum, and standard deviation of each time difference are calculated. Then, the variation amplitude of adjacent time differences is calculated to extract the time difference fluctuation index. Simultaneously, the time difference values ​​are compared with the error limit of 1 μs in the IEEE 1588 protocol. During this comparison, all time difference values ​​are converted to μs and screened, marking data points exceeding 1000 μs and recording their location and error value. For example, if... If the error exceeds the limit, the data is tagged and included in the abnormal error statistics set. During the statistical process, the offset distance is calculated for all time difference sequences, and the length and number of segments that continuously exceed the error limit are included in the abnormal segment information table. Finally, the time synchronization error measurement result is obtained by combining various error judgment items.

[0116] S413: Based on the time synchronization error measurement results, the time period corresponding to the error value is compared with the standard error limit item by item. All error segments are checked for exceeding the limit and the total number of segments and the proportion of abnormal segments are counted. The response stability of the entire communication link is judged and analyzed by the maximum error value and the exceeding ratio, and a response delay index is established.

[0117] Based on the time synchronization error measurement results, the error statistics are sequentially compared with the IEEE 1588 time synchronization threshold of 1μs for interval judgment. The judgment benchmark is set as whether the error is less than or equal to 1μs. All time difference data segments are scanned according to this rule, and normal segments that meet the conditions and abnormal segments that do not meet the conditions are recorded respectively. The synchronization stability evaluation value is formed by statistically analyzing the percentage of abnormal segments to the total number of segments. The time period with the largest error value is selected from the abnormal segments, and its time index and error value are recorded. At the same time, the maximum duration of the abnormal segment is calculated and used as the basis for link instability assessment. If the maximum error segment is the 7th segment of the sequence, with an error of 1800μs and a duration of 4 consecutive segments totaling 2 seconds, then this information is constructed as the final output content, used as the synchronization stability criterion, and a response delay index is established.

[0118] Please see Figure 6 The specific steps of S5 are as follows:

[0119] S511: Based on the response delay index and dynamic torque disturbance characteristics, construct the interference response delay sequence and disturbance amplitude sequence, perform time alignment processing, set the maximum tolerance window, filter joint data pairs with time differences within the tolerance range, perform data mapping between interference triggering and communication response, and obtain disturbance-delay mapping trend records.

[0120] Based on the response delay index and dynamic torque disturbance characteristics, the occurrence time sequence of disturbance events and the corresponding torque disturbance amplitude are first extracted from the time-synchronized acquisition system. Assuming the recorded disturbance event times within the monitoring period are 13.020 seconds, 14.505 seconds, and 15.330 seconds, with corresponding disturbance amplitudes of 220 Nm, 315 Nm, and 420 Nm, respectively, the response delay timestamps of the communication system are also extracted. These timestamps are 13.024 seconds, 14.509 seconds, and 15.339 seconds, with corresponding delays of 4 ms, 4 ms, and 9 ms. By aligning the disturbance time and delay time along the time axis and setting the maximum... With a maximum time matching deviation of 5ms, item-by-item screening and matching were performed to obtain three sets of effective joint data points, constructing a disturbance-delay control group. Subsequently, the disturbance amplitude and delay value were normalized and plotted as a two-dimensional curve sequence. Observing the curve trend, it was found that the three points were located on a gradually rising trend, that is, the stronger the disturbance, the longer the response delay. Further analysis of the growth direction and relative slope of the statistical data confirmed that the curve met the monotonically rising characteristic. Based on this trend, it was determined to be a positive correlation segment. The consistent mapping characteristic trend between the disturbance amplitude and the communication response in the sample was recorded, and the mapping curve was encoded into the data structure, finally obtaining the disturbance-delay mapping trend record.

[0121] S512: Based on the disturbance-delay mapping trend record, a two-dimensional data space is constructed according to the change range of disturbance amplitude and delay response, the disturbance value and response value are jointly classified, the frequency and range of each type of data point are statistically analyzed, the corresponding level classification identifier is marked, and the reliability level classification result is obtained;

[0122] Based on the disturbance-delay mapping trend record, the joint disturbance amplitude and response delay data obtained from the previous sub-step are divided into three segments according to the disturbance amplitude: 0–150Nm, 151–300Nm, and 301–450Nm; and the response delay is divided into three segments: 0–5ms, 6–10ms, and over 11ms. The three joint sample points are then placed into a nine-square grid classification structure. Calculations show that the first group of samples (220Nm and 4ms) falls into the second region (151–300Nm, 0–5ms), and the second group (315Nm and 4ms) falls into the fifth region (301–450Nm, 0–5ms). Three groups of 420Nm and 9ms fell into the sixth zone (301–450Nm, 6–10ms). The sample density of the three types of landing points was estimated. The three points were independently distributed in different regions with a density of 1. There was no duplicate sample density in each region. Then, by calculating the mean of the horizontal and vertical coordinates of each classification center point and comparing it with the communication level classification line of the IEC61850-90-5 standard, it was found that the second zone was between the lower limit and the median of the level 2 threshold, the fifth zone was in the inner zone of level 3, and the sixth zone was in the edge zone of level 4. The classification result was determined that the sample belonged to level 2, 3, and 4, and the reliability level classification result was finally obtained.

[0123] S513: Based on the reliability level classification results, match the various classification labels according to the reliability level standards in the communication standard, and assign them to the corresponding level categories. Select the level with the highest proportion in all data as the anti-interference performance level under the current link state, and establish the link anti-interference simulation test results.

[0124] Based on the reliability level classification results, the three samples obtained above are labeled as Level 2, Level 3, and Level 4, respectively, corresponding to level labels L2, L3, and L4 in the system structure. Counting the number of samples in each level reveals that each of the three types accounts for one sample, representing 33.3% of the total. The mean disturbance and mean delay for each level are calculated: Level 2 sample has a disturbance value of 220 Nm and a delay of 4 ms; Level 3 sample has a disturbance value of 315 Nm and a delay of 4 ms; and Level 4 sample has a disturbance value of 420 Nm and a delay of 9 ms. These are summarized as the average disturbance of 220 Nm and the average delay of Level 2. The average disturbance and delay for Level 3 are 315 Nm and 4 ms respectively, and the average disturbance and delay for Level 4 are 420 Nm and 9 ms respectively. According to the definition of IEC61850-90-5, Level 4 is the classification range with the strongest communication performance fluctuation. Therefore, this level is set as the current anti-interference main label level of the link. The statistical characteristic indicators of this level are output as the link status result, that is, the level proportion is 33.3%, the average disturbance is 420 Nm, the average delay is 9 ms, and the corresponding time index is 15.330 seconds to 15.339 seconds. Finally, the link anti-interference simulation test result is established.

[0125] The above are merely preferred embodiments of the present invention and are not intended to limit the present invention in any other way. Any person skilled in the art may make changes or modifications to the above-disclosed technical content to create equivalent embodiments that can be applied to other fields. However, any simple modifications, equivalent changes, and modifications made to the above embodiments based on the technical essence of the present invention without departing from the scope of the present invention shall still fall within the protection scope of the present invention.

Claims

1. A method for simulating and detecting communication anti-interference in flywheel energy storage systems, characterized in that, Includes the following steps: S1: Obtain the torque sampling data stream in the flywheel energy storage module, determine the sampling period and calculate the angular acceleration sequence, identify the maximum change point through differential peak detection, extract the corresponding timestamp and acceleration value, and generate dynamic torque disturbance characteristics; S2: Based on the dynamic torque disturbance characteristics, compare with the standard electromagnetic interference level, identify the frequency band that first exceeds the EMC immunity threshold, inject an equivalent electromagnetic interference signal into the communication link, and generate an interference injection spectrum identifier. S3: Monitor the timing data of the bit error rate at the receiving end, construct a sliding time window after the injection of the equivalent electromagnetic interference signal, count the CRC check failures within the window, identify the period of maximum bit error and calculate the average bit error delay, and generate communication quality degradation characteristics. S4: Based on the timestamps of the interference injection spectrum identifier and the communication quality degradation characteristics, calculate the time synchronization error, compare it with the standard time accuracy threshold, and generate a response delay index; S5: Perform joint EMC criterion analysis based on the response delay index and the dynamic torque disturbance characteristics, map the communication reliability level, and generate link anti-interference simulation test results; The specific steps for obtaining the interference injection spectrum identifier are as follows: S211: Based on the dynamic torque disturbance characteristics, obtain the frequency component distribution of the corresponding disturbance event in the time domain, perform a fast Fourier transform operation to obtain the frequency sequence, compare the disturbance intensity of each frequency point with the corresponding frequency point of the EMC immunity threshold curve, determine the starting frequency value of the first disturbance intensity exceeding the threshold of the corresponding frequency point, and generate the over-threshold frequency band value. S212: Based on the above-threshold frequency band value, match the radiation test field strength range specified by the interference injection, configure the injection time period, configure the interference coupling parameters for different communication channels, insert the corresponding interference signal into each communication link according to the injection frequency and time interval, and obtain the injection disturbance sequence value. S213: Based on the injected disturbance sequence value, statistically analyze the signal changes generated by the injected interference in each channel within the action period, calculate the maximum amplitude response index caused by the interference in each frequency band, identify the frequency range with the largest response and the corresponding time segment, and generate an interference injection spectrum identifier.

2. The method for simulating and detecting communication anti-interference in flywheel energy storage systems according to claim 1, characterized in that, The dynamic torque disturbance characteristics include disturbance timestamp, acceleration change amplitude, and peak frequency of angular acceleration. The interference injection spectrum identifier includes interference frequency band, radiation field strength level, and electromagnetic interference type. The communication quality degradation characteristics include peak bit error rate, average bit error delay, and number of CRC failures. The response delay index includes time synchronization error value, out-of-tolerance duration, and maximum response delay. The link anti-interference simulation test results include anti-interference level, communication reliability level, and EMC compliance judgment results.

3. The method for simulating and detecting communication anti-interference in flywheel energy storage systems according to claim 1, characterized in that, The specific steps for obtaining the dynamic torque disturbance characteristics are as follows: S111: Obtain the torque sampling data stream in the flywheel energy storage module, identify the time series and sampling period corresponding to each data point, perform differential processing on all data sequences, statistically analyze the angle change value and time difference between the current time point and the previous time point, and calculate the angular acceleration value sequence to obtain the angular acceleration sequence value; S112: Based on the angular acceleration sequence values, calculate the angular acceleration difference between any data point and its adjacent points, compare all differences with a set standard rate of change threshold, filter out all extreme points that exceed the threshold, and extract the corresponding time points and angular acceleration values ​​to obtain the time acceleration pair that exceeds the threshold. S113: Based on the aforementioned over-threshold time acceleration pairs, calculate the absolute value of the angular acceleration difference, the time interval, and the acceleration slope value for all changing time points within adjacent intervals, calculate the disturbance amplitude change rate sequence, obtain the data point timestamp and acceleration value corresponding to the maximum disturbance amplitude, and generate dynamic torque disturbance characteristics.

4. The method for simulating and detecting communication anti-interference in a flywheel energy storage system according to claim 1, characterized in that, The specific steps for obtaining the communication quality degradation characteristics are as follows: S311: Monitor the timing data of the bit error rate at the receiving end. After the equivalent electromagnetic interference signal is injected, record the number of bit errors per unit time and form a bit error sequence in time order. Divide the window segments and calculate the bit error rate. By traversing all window bit error rates, determine all sets that exceed the judgment threshold and obtain the set value of high bit error window. S312: Based on the set value of the high bit error rate window, count the cumulative number of CRC check failures within the corresponding period of the window and store them in the fault count sequence. Count the error bits in each window and record the first and last occurrence times. Obtain the start and end time interval of the maximum bit error rate window and generate the maximum bit error rate period interval value. S313: Based on the maximum bit error period interval value, extract the actual time point and error length of the bit error event within the corresponding time period, accumulate the interval of each event and obtain its average value, calculate the average bit error delay index, and combine it with its continuous impact on communication quality to generate communication quality degradation characteristics.

5. The method for simulating and detecting communication anti-interference in a flywheel energy storage system according to claim 1, characterized in that, The specific steps for obtaining the response latency indicator are as follows: S411: Based on the timestamps of the interference injection spectrum identifier and the communication quality degradation feature, extract the occurrence time of the corresponding interference triggering event and the start time of the communication response degradation event, perform time-series comparison on each pair of interference frequency bands and communication anomaly features, and construct the interference-response time difference sequence to obtain the interference-response time difference sequence value. S412: Based on the interference response time difference sequence value, obtain the time difference between all interference triggers and communication responses, record the magnitude and frequency of each time difference deviating from the average error in the whole sequence, compare it with the standard maximum synchronization deviation value, identify the segments with abnormal fluctuations in duration, and obtain the time synchronization error measurement result. S413: Based on the time synchronization error measurement results, the time period corresponding to the error value is compared with the standard error limit item by item. All error segments are checked for exceeding the limit and the total number of segments and the proportion of abnormal segments are counted. The response stability of the entire communication link is judged and analyzed by the maximum error value and the exceeding limit ratio, and a response delay index is established.

6. The method for simulating and detecting communication anti-interference in a flywheel energy storage system according to claim 1, characterized in that, The specific steps for obtaining the link anti-interference simulation test results are as follows: S511: Based on the response delay index and the dynamic torque disturbance characteristics, construct the interference response delay sequence and the disturbance amplitude sequence, perform time alignment processing, set the maximum tolerance window, filter joint data pairs with time differences within the tolerance range, perform data mapping between interference triggering and communication response, and obtain disturbance-delay mapping trend records. S512: Based on the disturbance-delay mapping trend record, construct a two-dimensional data space according to the change range of disturbance amplitude and delay response, jointly classify the disturbance value and response value, count the frequency and range of each type of data point, mark the corresponding level classification identifier, and obtain the reliability level classification result; S513: Based on the reliability level classification results, match the various classification labels according to the reliability level standards in the communication standard, and assign them to the corresponding level categories. Select the level with the highest proportion in all data as the anti-interference performance level under the current link state, and establish the link anti-interference simulation detection results.

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