A method and device for identifying battery cell leakage in a power system

Abstract

This invention belongs to the field of vehicle fault analysis, specifically relating to a method and device for identifying battery cell leakage in a power system. This method addresses the insulation fault conditions and characteristics caused by battery cell leakage. It utilizes the data characteristic of frequent alternation between normal and abnormal resistance values ​​during battery cell leakage, characterizing the variability of battery cell leakage through parameters related to the insulation normal and abnormal time periods. Simultaneously, it leverages the fact that abnormal values ​​of positive and negative electrode insulation resistance tend to stabilize with little change, while the absolute value of the difference between insulation resistance reductions caused by other reasons is much greater than in the case of battery cell leakage. The stability of battery cell leakage is characterized by the sum of the absolute values ​​of the differences between the current sampling time's positive and negative electrode insulation resistance and the insulation resistance value at the previous sampling time. Therefore, the battery cell leakage identification method of this invention can judge fault data from multiple data feature perspectives, improving the reliability and accuracy of battery cell leakage identification.

Description

Technical Field

[0001] This invention belongs to the field of vehicle fault analysis, and specifically relates to a method and device for identifying battery cell leakage in a power system. Background Technology

[0002] Since its emergence in the 1970s, lithium-ion batteries have experienced rapid development and are widely used in digital products, automobiles, and energy storage. However, lithium-ion batteries themselves have inherent safety hazards that cannot be ignored, and these safety issues become increasingly acute as their energy density increases. In lithium-ion battery power systems, cell leakage is a significant safety threat. Therefore, to ensure the safety of lithium-ion batteries, it is necessary to accurately identify cell leakage faults in the power system and implement early warning systems.

[0003] In existing technologies, new energy vehicles typically have the function of automatically reporting faults. However, during on-site handling, due to the wide variety of fault types, it is difficult to pinpoint the specific cause of the fault, resulting in the inability to accurately identify power system faults. Although cell leakage faults in the power system have the data characteristic of unstable insulation resistance, in principle, any situation that causes unstable insulation resistance may exhibit data characteristics similar to those of the power system. Therefore, these situations often interfere with the determination of cell leakage, leading to missed or false alarms of cell leakage faults. This makes the detection results of cell leakage faults unreliable and the fault identification efficiency low. Summary of the Invention

[0004] The purpose of this invention is to provide a method and apparatus for identifying leakage in power system cells, which solves the problems of unreliable detection results and low fault identification efficiency in the prior art for detecting leakage faults in power system cells.

[0005] To achieve the above objectives, the present invention provides a method for identifying battery cell leakage in a power system, comprising the following steps:

[0006] 1) Obtain the insulation resistance data of the positive and negative terminals of the vehicle with insulation fault and determine whether the insulation resistance values ​​of the positive and negative terminals are abnormal;

[0007] 2) Calculate the average and minimum resistance values ​​of the positive and negative poles at the current sampling time when the insulation resistance values ​​of the positive and negative poles are abnormal;

[0008] 3) When the insulation resistance values ​​of the positive and negative poles are abnormal, calculate the absolute value of the difference between the current sampling time of the positive / negative pole insulation resistance value and the previous sampling time, and sum the absolute values ​​of all such differences for the vehicle with the insulation abnormality.

[0009] 4) Calculate the number of times the insulation is normal and the insulation is abnormal for the positive and negative poles, the average time and the maximum time of the insulation is normal, and the average time and the maximum time of the insulation is abnormal.

[0010] 5) Based on the sum of the average resistance, minimum resistance, and absolute values ​​of the differences obtained in steps 2)-4), as well as the number of times, average time, and maximum time of the insulation normal / abnormal time period, determine whether the vehicle with the insulation abnormality has cell leakage.

[0011] This identification method utilizes the data characteristic of frequent alternation between normal and abnormal resistance values ​​during cell leakage. It characterizes the variability of cell leakage by using parameters related to the normal insulation period and the abnormal insulation period. Furthermore, abnormal values ​​of positive and negative electrode insulation resistance tend to be stable with little change. However, when insulation resistance is reduced due to other reasons, the absolute value of the difference will be much greater than that in the case of cell leakage. Therefore, this identification method can also use the sum of the absolute values ​​of the differences between the current sampling time's positive and negative electrode insulation resistance and the insulation resistance at the previous sampling time as an indicator to characterize the stability of cell leakage. In other words, it judges fault data from multiple data feature perspectives, improving the reliability and accuracy of cell leakage identification.

[0012] Furthermore, the conditions for determining whether the vehicle with the insulation abnormality has cell leakage are as follows:

[0013] ① The number of times the positive electrode insulation abnormality occurs is greater than the first set threshold, the average positive electrode insulation resistance is less than the first set threshold, the minimum positive electrode insulation resistance is greater than the second set threshold, and the sum of the insulation values ​​of the difference between the positive electrode insulation resistance values ​​at two consecutive sampling times is less than the third set threshold; or the number of times the negative electrode insulation abnormality occurs is greater than the second set threshold, the average negative electrode insulation resistance is less than the fourth set threshold, the minimum negative electrode insulation resistance is greater than the fifth set threshold, and the sum of the insulation values ​​of the difference between the negative electrode insulation resistance values ​​at two consecutive sampling times is less than the sixth set threshold.

[0014] ②The average time of the positive electrode insulation abnormality period is less than the first set time threshold; or the average time of the negative electrode insulation abnormality period is less than the second set time threshold.

[0015] ③ The maximum time of normal insulation of the positive electrode is less than the third set time threshold; or the maximum time of normal insulation of the negative electrode is less than the fourth set time threshold;

[0016] ④ The average time of the normal insulation period of the positive electrode is less than the fifth set time threshold; or the average time of the normal insulation period of the negative electrode is less than the sixth set time threshold;

[0017] The third, fourth, fifth, and sixth set time thresholds are all greater than the first set time threshold and the second set time threshold;

[0018] When the insulation resistance values ​​of the positive and negative terminals of a vehicle with insulation abnormality simultaneously meet the above conditions, it is determined that the vehicle with insulation abnormality has a cell leakage problem.

[0019] Furthermore, when the positive and negative electrode insulation resistance values ​​are lower than a set threshold, the positive and negative electrode insulation resistance values ​​are determined to be abnormal.

[0020] Furthermore, the positive and negative insulation resistance values ​​and the sampling time of the corresponding resistance values ​​are extracted within a set time after the first abnormal insulation resistance value appears on the day before the insulation fault is reported by the vehicle, and are used as the positive and negative insulation resistance value data of the vehicle with insulation fault.

[0021] Furthermore, if the insulation resistance value is normal at the previous sampling time and abnormal at the current sampling time, the time corresponding to the insulation resistance value at the current sampling time is marked as the start time of the abnormality; if the insulation resistance value is abnormal at the previous sampling time and normal at the current sampling time, the time corresponding to the insulation resistance value at the current sampling time is marked as the start time of the normality; the normal insulation time period and the abnormal insulation time period are determined according to the marking.

[0022] Furthermore, if the time interval between the current sampling time and the previous sampling time exceeds a set time interval threshold, the positive and negative insulation resistance data corresponding to the current sampling time will not be used as the insulation resistance data of the vehicle with insulation abnormality.

[0023] If the time interval between the current sampling time and the previous sampling time exceeds the set time interval threshold, there may be a situation where data acquisition is missing or the vehicle is powered off and idle. In order to avoid these situations from interfering with the data during this period (such as causing an increase in the duration of the normal / abnormal insulation period of the positive and negative poles), the insulation resistance data of the positive and negative poles corresponding to the current sampling time will not be used as the data used to judge the leakage of the power system cell.

[0024] Furthermore, the set time interval threshold is the time interval between the moment when the insulation resistance value first appears abnormal the day before the insulation fault is reported by the vehicle and the moment when the last sampling time corresponding to the positive and negative insulation resistance values ​​of the previous day.

[0025] The present invention also provides a power system cell leakage identification device, which is used to implement the above-mentioned power system cell leakage identification method.

[0026] This battery cell leakage detection device can achieve the same beneficial effects as the aforementioned power system battery cell leakage detection method. Attached Figure Description

[0027] Figure 1 This is an example diagram of setting up a fault table in an embodiment of the power system cell leakage identification method of the present invention;

[0028] Figure 2 This is a schematic diagram of the data morphology characteristics of battery cell leakage faults in an embodiment of the power system battery cell leakage identification method of the present invention;

[0029] Figure 3 This is a schematic diagram of the data morphology characteristics of insulation alarm vehicle air conditioning insulation faults in an embodiment of the power system cell leakage identification method of the present invention;

[0030] Figure 4 This is a schematic diagram of an insulation alarm vehicle situation caused by insulation failure due to cell leakage identified in an embodiment of the power system cell leakage identification method of the present invention;

[0031] Figure 5a This is a graph showing the change in positive electrode insulation resistance of vehicle 1 in an embodiment of the power system cell leakage identification method of the present invention;

[0032] Figure 5b This is a graph showing the change in the negative electrode insulation resistance of vehicle 2 in an embodiment of the power system cell leakage identification method of the present invention;

[0033] Figure 5c This is a graph showing the change in positive electrode insulation resistance of vehicle 3 in an embodiment of the power system cell leakage identification method of the present invention.

[0034] Figure 5d This is a graph showing the change in positive electrode insulation resistance of a vehicle that falsely reports leakage in a power system cell leakage identification method according to the present invention.

[0035] Figure 5e This is a newly added diagram showing the change in the negative electrode insulation resistance of a correctly identified vehicle in an embodiment of the power system cell leakage identification method of the present invention. Detailed Implementation

[0036] To make the objectives, technical solutions, and advantages of the present invention clearer, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments.

[0037] Example of a method for identifying battery cell leakage in a power system:

[0038] This embodiment provides a technical solution for a power system cell leakage identification method, referring to... Figure 1 The details are as follows:

[0039] 1) Obtain the insulation resistance data of the positive and negative terminals of the vehicle with insulation fault and determine whether the insulation resistance values ​​of the positive and negative terminals are abnormal.

[0040] The vehicle acquires and records the positive and negative insulation resistance values ​​through sampling at a fixed sampling period. Therefore, when a vehicle reports an insulation fault, the positive and negative insulation resistance values ​​and the corresponding sampling times within a set time period after the first occurrence of abnormal insulation resistance values ​​on the day before the vehicle reports the insulation fault are extracted as the positive and negative insulation resistance value data of the vehicle with insulation fault. The set time period is the time interval between the first occurrence of abnormal insulation resistance values ​​on the day before the vehicle reports the insulation fault and the last sampling time corresponding to the positive and negative insulation resistance values ​​on the previous day. In this embodiment, the sampling times of the positive and negative insulation resistance values ​​and the corresponding resistance values ​​within the time period from the first occurrence of abnormal insulation resistance values ​​on the day before the vehicle reports the fault to 23:59:59 on the previous day are directly extracted as the positive and negative insulation resistance value data of the vehicle with insulation fault used to determine the leakage of the power system cell. For vehicles with insulation faults, in order to process only the data after the first occurrence of insulation problems and simplify the data, the above-mentioned extraction is performed. When the insulation resistance of the positive and negative electrodes is lower than the set threshold, the insulation resistance of the positive and negative electrodes is determined to be abnormal. In this embodiment, the set threshold is 2500kΩ.

[0041] If the insulation resistance value is normal at the previous sampling time but abnormal at the current sampling time, the time corresponding to the insulation resistance value at the sampling time is marked as the start time of the abnormality; if the insulation resistance value is abnormal at the previous sampling time but normal at the current sampling time, the time corresponding to the insulation resistance value at the sampling time is marked as the start time of the normality. Based on these marks, the normal insulation time period and the abnormal insulation time period are determined. For example, the time period between adjacent normal start times and abnormal start times is the normal insulation time period, and the time period between adjacent abnormal start times and normal start times is the abnormal insulation time period.

[0042] If the time interval between the current sampling moment and the previous sampling moment exceeds a set time interval threshold, data acquisition may be missing or the vehicle may be powered off and idle. To avoid interference from these situations with the data during this period (such as increasing the duration of the normal / abnormal insulation time between the positive and negative electrodes), the insulation resistance values ​​of the positive and negative electrodes corresponding to the current sampling moment are not used as the data for judging cell leakage in the power system. This set time interval threshold is usually related to the time interval between sampling moments; in this embodiment, the set time interval threshold is 60 seconds.

[0043] 2) Calculate the average and minimum resistance values ​​of the positive and negative poles at the current sampling time when the insulation resistance values ​​of the positive and negative poles are abnormal.

[0044] 3) When the insulation resistance values ​​of the positive and negative poles are abnormal, calculate the absolute value of the difference between the insulation resistance value of the positive and negative poles at the current sampling time and the insulation resistance value at the previous sampling time, and sum the absolute values ​​of all these differences for the vehicle with the insulation abnormality.

[0045] When cell leakage occurs, the abnormal values ​​of the insulation resistance of the positive and negative terminals tend to stabilize with little change, so the sum of their absolute differences should be small. However, when the insulation resistance decreases due to water vapor or other reasons, the absolute value of the difference will be much greater than that in the case of cell leakage. Therefore, the sum of the absolute values ​​of the differences between the insulation resistance of the positive and negative terminals at the current sampling time and the insulation resistance at the previous sampling time is used as an indicator to distinguish this difference.

[0046] 4) Calculate the number of times the insulation is normal and the insulation is abnormal for the positive and negative poles, the average time and the maximum time of the insulation is normal, and the average time and the maximum time of the insulation is abnormal.

[0047] The essence of leakage is that the slow and continuous leakage of the battery cell causes instability in the insulation resistance value. In particular, there is a data feature of frequent alternation between normal and abnormal resistance values. Therefore, this feature is characterized by parameters related to the insulation normal time period and the insulation abnormal time period.

[0048] 5) Based on the sum of the average resistance, minimum resistance, and absolute values ​​of the differences obtained in steps 2)-4), as well as the number of times, average time, and maximum time of the insulation normal / abnormal time period, determine whether the vehicle with the insulation abnormality has cell leakage.

[0049] The conditions for determining whether a vehicle with insulation abnormalities has battery cell leakage are as follows:

[0050] Condition 1: The number of positive electrode insulation abnormality periods exceeds a first set threshold, the average positive electrode insulation resistance is less than a first set threshold, the minimum positive electrode insulation resistance is greater than a second set threshold, and the sum of the insulation values ​​of the differences between the positive electrode insulation resistance values ​​at two consecutive sampling times is less than a third set threshold; or the number of negative electrode insulation abnormality periods exceeds a second set threshold, the average negative electrode insulation resistance is less than a fourth set threshold, the minimum negative electrode insulation resistance is greater than a fifth set threshold, and the sum of the insulation values ​​of the differences between the negative electrode insulation resistance values ​​at two consecutive sampling times is less than a sixth set threshold. Condition 1 is equivalent to classifying a situation with a high frequency of abnormality and a low average resistance value as an insulation resistance data pattern indicating cell leakage.

[0051] In this embodiment, the first and second set threshold values ​​are both 120 times, the first and fourth set resistance threshold values ​​are both 800kΩ, the second and fifth set resistance threshold values ​​are both 0kΩ, and the third and sixth set resistance threshold values ​​are both 15000kΩ. Through creative research, the insulation problem of non-cell leakage does not show frequent alternation between normal and abnormal resistance values, averaging once every 1-2 minutes. Therefore, the specific threshold value for different times can be determined based on an average of once every 1-2 minutes. Since normal vehicle operation generally exceeds 4 hours, the threshold value of 120 times (corresponding to a time range of approximately 4 hours) is set in this embodiment. This threshold value is effective as long as the actual vehicle operation time is greater than 4 hours. Furthermore, it is impossible for non-cell leakage to exceed 10 times under normal circumstances. Therefore, although the threshold value of 120 times does not change with time, it can play a distinguishing role because the difference between normal and abnormal is huge.

[0052] Condition 2: The average time of the positive electrode insulation abnormality period is less than the first set time threshold; or the average time of the negative electrode insulation abnormality period is less than the second set time threshold. Condition 2 is equivalent to judging the case of short insulation abnormality time as the insulation resistance data form of cell leakage; in this embodiment, the first and second set time thresholds are both 20 seconds.

[0053] Condition 3: The maximum duration of the normal insulation period for the positive electrode is less than the third set time threshold; or the maximum duration of the normal insulation period for the negative electrode is less than the fourth set time threshold. In this embodiment, both the third and fourth set time thresholds are 180 seconds.

[0054] Condition 4: The average time of the normal insulation period of the positive electrode is less than the fifth set time threshold; or the average time of the normal insulation period of the negative electrode is less than the sixth set time threshold. In this embodiment, both the fifth and sixth set time thresholds are 120 seconds.

[0055] Based on the data characteristic of short insulation abnormality time when cell leakage occurs, the third, fourth, fifth, and sixth set time thresholds are all greater than the first and second set time thresholds. When the insulation resistance data of the positive and negative terminals of a vehicle with insulation abnormality simultaneously meet the above conditions, it is determined that the vehicle has cell leakage. For specific data morphology characteristics of insulation faults caused by cell leakage in vehicles with insulation alarms, please refer to [reference needed]. Figure 2As can be seen, when the cell leaks, normal and abnormal resistance values ​​alternate repeatedly. Since the essence of the leakage warning is that the slow and continuous leakage of the cell causes instability in the insulation resistance value, the management system will report a normal insulation resistance value of 2540kΩ under this situation. The true value will only be reported when the insulation resistance value stabilizes. Therefore, the data characteristic of the insulation resistance value frequently alternating between the normal value (2540kΩ) and the lower resistance value (below 400kΩ) is caused. Furthermore, the figure shows the visual effect of one X value corresponding to two Y values ​​at the same time (in reality, it is still one X value corresponding to one Y value). It is just that the two Y values ​​switch too frequently, resulting in too many points on the horizontal axis with days as the unit, making it look like two curves of the resistance value when the cell leaks.

[0056] Insulation faults caused by water ingress into the vehicle are more similar in nature to those caused by cell leakage in the power system. They share more similar fault characteristics compared to other insulation faults. Therefore, to further isolate water-related issues from cell leakage fault diagnosis, the self-recovery characteristic of data patterns corresponding to water-induced insulation faults can be utilized. Data points in the 0-400kΩ, 400-2500kΩ, and 2500-2540kΩ ranges can be counted. The system's positive or negative terminals must simultaneously meet the following conditions: the number of data points in the 400-2500kΩ range is 0 (this requires a non-plug-in state, as the charger may cause a decrease in insulation resistance) and the number of data points in the 0-400kΩ range is greater than 100. Only then can the data pattern be identified as the data pattern characteristic corresponding to cell leakage faults. Figure 2 The first half of the data points corresponds to the insulation resistance value during the early evolution of the fault. Since this embodiment only starts identification when the insulation fault is reported, the insulation resistance value of the vehicle system is lower than 1000 ohms, or the total voltage of the vehicle system is lower than 1000 volts, that is, identification begins when the first fault occurs. At this time, the insulation resistance value is already low, thus avoiding the first half of the data points, so the above-mentioned conditions can be met.

[0057] Reference Figure 3 The data pattern of insulation faults caused by the air conditioning in the vehicle also shows the characteristic of frequent alternation between the normal value (2540kΩ) and the low value (400kΩ) insulation resistance. In fact, the sum of the insulation values ​​of the difference between the negative terminals of the two data points caused by the air conditioning is much greater than the corresponding value of the insulation fault caused by core leakage. Therefore, according to the judgment index in condition 1 that the sum of the insulation values ​​of the difference between the negative terminals of the two data points is less than 15000kΩ, the influence of the data pattern of insulation faults caused by the air conditioning can be ruled out.

[0058] Therefore, the above judgment criteria can effectively distinguish the data patterns of insulation faults caused by vehicle air conditioning, water, and battery cell leakage, thereby obtaining a more accurate fault location. (Refer to...) Figure 4 Through specific experiments, from February 1, 2021 to September 6, 2021, a total of 5 vehicles with insulation alarms caused by cell leakage were identified. Among them, 3 vehicles were correctly identified and used as standard case vehicles with data morphology characteristics of insulation faults caused by cell leakage, 1 vehicle was newly identified correctly, and 1 vehicle was a false alarm. Figures 5a-5e These are schematic diagrams illustrating the changes in insulation resistance of these five vehicles with insulation alarms. Figure 5a This is a graph showing the change in the positive insulation resistance of vehicle 1 in case study. Figure 5b This is a graph showing the change in the negative electrode insulation resistance of vehicle 2 in case study. Figure 5c The graph shows the change in the positive insulation resistance of vehicle 3 in case study. Figure 5d The graph shows the change in positive insulation resistance of a vehicle that is falsely reporting an error. Figure 5e This is a newly added graph showing the change in negative electrode insulation resistance for correctly identified vehicles; among which, Figures 5a-5e The bounding boxes in the image define the regions or extraction scenarios for logical recognition by the algorithm. Specifically, the bounding boxes represent data portions that match the characteristics of battery cell leakage. Figures 5a-5e Considering the characteristics of each vehicle, for the four vehicles with a 20-second sampling period, the above conditions are applicable to determine the data format of insulation fault caused by cell leakage. The only false alarm belongs to vehicle 21KX01HE-0001 with a 1-second sampling period. Because its available data time is very short, but the number of sampling points is large, it is more likely to cause misjudgment.

[0059] Example of a power system cell leakage detection device:

[0060] This embodiment provides a technical solution for a power system battery cell leakage identification device. This device is used to implement the aforementioned power system battery cell leakage identification method and can achieve the same beneficial effects. The specific working principle and steps of this device have been described in detail in the embodiments of the power system battery cell leakage identification method, and will not be repeated here.

[0061] This invention addresses the insulation faults caused by cell leakage and their characteristics. It utilizes the data feature of frequent alternation between normal and abnormal resistance values ​​during cell leakage, characterizing the variability of leakage through parameters related to the normal and abnormal insulation periods. Simultaneously, it leverages the fact that abnormal values ​​of positive and negative electrode insulation resistance tend to stabilize with minimal change, while the absolute value of the difference in insulation resistance caused by other factors is much greater than in the case of cell leakage. By using the sum of the absolute values ​​of the differences between the current sampling time's positive and negative electrode insulation resistance and the insulation resistance at the previous sampling time as an indicator, the stability of cell leakage is characterized. Therefore, this invention's cell leakage identification method can judge fault data from multiple data feature perspectives, improving the reliability and accuracy of cell leakage identification.

[0062] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that modifications or equivalent substitutions can still be made to the specific implementation of the present invention. Any modifications or equivalent substitutions that do not depart from the spirit and scope of the present invention should be covered within the scope of protection of the claims of the present invention.

Claims

1. A power supply system cell liquid leakage recognition method characterized by, Includes the following steps: 1) Obtain the insulation resistance data of the positive and negative terminals of the vehicle with insulation abnormality and determine whether the insulation resistance values ​​of the positive and negative terminals are abnormal; 2) Calculate the average and minimum resistance values ​​of the positive and negative poles at the current sampling time when the insulation resistance values ​​of the positive and negative poles are abnormal; 3) When the insulation resistance values ​​of the positive and negative electrodes are abnormal, calculate the absolute value of the difference between the positive electrode insulation resistance value at the current sampling time and the previous sampling time, and calculate the absolute value of the difference between the negative electrode insulation resistance value. Then, calculate the sum of the absolute values ​​of the differences between the positive and negative electrodes of all vehicles with insulation abnormalities, so as to characterize the stability of the abnormal values ​​of the positive and negative electrode insulation resistance values ​​when the battery cell is leaking. 4) Calculate the number of times the insulation is normal and the insulation is abnormal for the positive and negative poles, the average time and the maximum time of the insulation is normal, and the average time and the maximum time of the insulation is abnormal, respectively, to characterize the data feature of frequent alternation of normal and abnormal resistance values ​​when the cell leaks. 5) Based on the sum of the average resistance, minimum resistance, absolute value of the difference obtained in steps 2)-4), as well as the number of times, average time and maximum time of the insulation normal and abnormal time periods, determine whether the vehicle with the insulation abnormality has cell leakage.

2. The power source system cell liquid leakage identification method according to claim 1, characterized by, The conditions for determining whether a vehicle with insulation abnormalities has battery cell leakage are as follows: The number of positive electrode insulation abnormality periods exceeds the first set threshold, the average positive electrode insulation resistance is less than the first set threshold, the minimum positive electrode insulation resistance is greater than the second set threshold, and the sum of the insulation values ​​of the difference between the positive electrode insulation resistance values ​​at two consecutive sampling times is less than the third set threshold; or the number of negative electrode insulation abnormality periods exceeds the second set threshold, the average negative electrode insulation resistance is less than the fourth set threshold, the minimum negative electrode insulation resistance is greater than the fifth set threshold, and the sum of the insulation values ​​of the difference between the negative electrode insulation resistance values ​​at two consecutive sampling times is less than the sixth set threshold. The average time of the positive electrode insulation abnormality period is less than the first set time threshold; or the average time of the negative electrode insulation abnormality period is less than the second set time threshold. The maximum time of normal insulation of the positive electrode is less than the third set time threshold; or the maximum time of normal insulation of the negative electrode is less than the fourth set time threshold. The average time of the normal period of positive electrode insulation is less than the fifth set time threshold; or the average time of the normal period of negative electrode insulation is less than the sixth set time threshold. The third, fourth, fifth, and sixth set time thresholds are all greater than the first set time threshold and the second set time threshold; When the insulation resistance values ​​of the positive and negative terminals of a vehicle with insulation abnormality simultaneously meet the above conditions, it is determined that the vehicle with insulation abnormality has a cell leakage problem.

3. The power system cell leakage identification method according to claim 1, characterized in that, When the insulation resistance values ​​of the positive and negative electrodes are lower than the set threshold, the insulation resistance values ​​of the positive and negative electrodes are determined to be abnormal.

4. The power system cell leakage identification method according to claim 1, characterized in that, The positive and negative insulation resistance values ​​and the sampling time of the corresponding resistance values ​​are extracted within a set time after the first occurrence of the insulation resistance abnormality on the day before the vehicle with insulation abnormality is reported. These are used as the positive and negative insulation resistance value data of the vehicle with insulation abnormality.

5. The power system cell leakage identification method according to claim 1, characterized in that, If the insulation resistance value is normal at the previous sampling time and abnormal at the current sampling time, the time corresponding to the insulation resistance value at the current sampling time is marked as the start time of the abnormality; if the insulation resistance value is abnormal at the previous sampling time and normal at the current sampling time, the time corresponding to the insulation resistance value at the current sampling time is marked as the start time of the normality; the normal insulation time period and the abnormal insulation time period are determined according to the marking.

6. The power system cell leakage identification method according to claim 1, characterized in that, If the time interval between the current sampling time and the previous sampling time exceeds the set time interval threshold, the positive and negative insulation resistance data corresponding to the current sampling time will not be used as the insulation resistance data of the vehicle with insulation abnormality.

7. The power system cell leakage identification method according to claim 4, characterized in that, The set time is the time interval between the moment when the insulation resistance value first appears on the day before the vehicle with insulation abnormality is reported and the moment of the last sampling of the positive and negative insulation resistance values ​​on the day before.

8. A power system cell leakage detection device, characterized in that, The power system cell leakage identification device is used to implement the power system cell leakage identification method according to any one of claims 1-7.

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