Battery cell liquid leakage detection method and system, computer equipment and readable storage medium

Abstract

The invention relates to a battery cell liquid leakage detection method and system, computer equipment and a readable storage medium. Acquiring resistance time sequence data of the to-be-detected battery cell under the target working condition in real time; the resistance value time sequence data comprises cell resistance values corresponding to a plurality of continuous time points; resistance change characteristic detection is carried out on the resistance time sequence data, and if it is detected that the resistance change characteristic of the resistance time sequence data meets a preset liquid leakage judgment condition, it is determined that liquid leakage occurs in the to-be-detected battery cell; the timeliness and accuracy of battery cell leakage early warning are improved, so that potential faults can be found earlier, and the safety of a battery system is guaranteed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of battery detection, in particular to a battery cell liquid leakage detection method and system, computer equipment and readable storage medium. BACKGROUND

[0002] As the core unit of energy storage and release, the sealing integrity of the battery cell is the fundamental prerequisite for ensuring the safe, reliable and long-life operation of the entire system. However, under the conditions of manufacturing, use or misuse, the battery cell may have a risk of sealing failure, resulting in electrolyte leakage. Timely and reliable detection of battery cell liquid leakage has become an indispensable key technology in high safety requirement application scenarios. SUMMARY

[0003] Currently, battery cell liquid leakage detection mainly relies on offline table lookup method; this method has the problems of early warning lag, poor real-time performance, low accuracy, and is difficult to effectively respond and warn at the initial stage of liquid leakage. Based on this, it is necessary to provide a battery cell liquid leakage detection method, device, computer equipment and readable storage medium for the above technical problems.

[0004] In a first aspect, the present application provides a battery cell liquid leakage detection method, the method comprising:

[0005] obtaining resistance time series data of a battery cell to be tested under a target working condition in real time; the resistance time series data comprises battery cell resistance values corresponding to a plurality of continuous time points;

[0006] detecting resistance value change characteristics of the resistance time series data, and if it is detected that the resistance value change characteristics of the resistance time series data meet a preset liquid leakage determination condition, determining that the battery cell to be tested has liquid leakage.

[0007] In one embodiment, the method for detecting resistance value change characteristics of the resistance time series data, and if it is detected that the resistance value change characteristics of the resistance time series data meet a preset liquid leakage determination condition, determining that the battery cell to be tested has liquid leakage, comprises:

[0008] analyzing the resistance value change rate of the resistance time series data to obtain resistance value change rate data corresponding to the resistance time series data; the resistance value change rate data comprises resistance value change rates corresponding to each of the battery cell resistance values in the resistance time series data except the first battery cell resistance value;

[0009] detecting the resistance value change rate data for abnormalities, and if it is detected that there is a target change rate jump point in the resistance value change rate data that meets the preset liquid leakage determination condition, determining that the battery cell to be tested has liquid leakage.

[0010] In one of the embodiments, the resistance value rate of change analysis on the resistance value time series data comprises:

[0011] For each pair of adjacent battery resistance values in the resistance value time series data, a resistance value rate of change corresponding to a target battery resistance value in the pair of adjacent battery resistance values is calculated according to a resistance value difference corresponding to the pair of adjacent battery resistance values and a time interval; the target battery resistance value refers to a battery resistance value with a later time point in the pair of adjacent battery resistance values;

[0012] The resistance value rates of change corresponding to a plurality of the target battery resistance values are determined as the resistance value rate of change data corresponding to the resistance value time series data.

[0013] In one of the embodiments, the abnormality detection on the resistance value rate of change data comprises:

[0014] The resistance value rate of change data is subjected to a rate of change mutation abnormality detection, if a candidate rate of change jump point satisfying a preset rate of change mutation condition is detected in the resistance value rate of change data, a neighborhood resistance value rate of change sequence in a neighborhood of the candidate rate of change jump point is determined; the neighborhood resistance value rate of change sequence comprises a plurality of resistance value rates of change within a preset time range before and after a time point of the candidate rate of change jump point.

[0015] The neighborhood resistance value rate of change sequence is subjected to a rate of change fluctuation amplitude detection, if a rate of change fluctuation amplitude of the neighborhood resistance value rate of change sequence does not exceed a preset rate of change fluctuation range, the candidate rate of change jump point is determined as a target rate of change jump point; a time point corresponding to the target rate of change jump point is a time point of the battery cell under test having a liquid leakage.

[0016] In one of the embodiments, the determination of the candidate rate of change jump point satisfying the preset rate of change mutation condition comprises:

[0017] According to a size relationship of the resistance value rates of change in the resistance value rate of change data, local maximum points in the resistance value rate of change data are determined in a time sequence; a resistance value rate of change corresponding to the local maximum point is a maximum resistance value rate of change within a preset neighborhood window with the local maximum point as a center;

[0018] The first local maximum point with a resistance value rate of change greater than a preset rate of change threshold value is determined as the candidate rate of change jump point satisfying the preset rate of change mutation condition.

[0019] In one of the embodiments,

[0020] The preset change rate threshold value ranges from 0.6 mΩ / s to 20 mΩ / s.

[0021] The preset change rate fluctuation range is 0 mΩ / s to 0.6 mΩ / s.

[0022] In one of the embodiments, the method further comprises:

[0023] In a case where the resistance change characteristic of the resistance time series data meets a preset liquid leakage determination condition, a liquid leakage early warning signal is generated to perform a battery safety early warning.

[0024] In a second aspect, the application provides a battery liquid leakage detection system, comprising a data processing unit, a resistance measurement unit and an alarm unit; the data processing unit is connected with the resistance measurement unit and the alarm unit respectively; the resistance measurement unit is connected with a battery to be tested;

[0025] The resistance measurement unit is configured to collect resistance time series data of the battery to be tested under a target working condition in real time, and transmit the resistance time series data to the data processing unit.

[0026] The data processing unit is configured to execute the battery liquid leakage detection method as described above.

[0027] The alarm unit is configured to perform a battery safety early warning according to a liquid leakage early warning signal generated by the data processing unit.

[0028] In a third aspect, the application provides a computer device, comprising a memory and a processor, the memory stores a computer program, and the processor executes the computer program to realize the steps of the method as described above.

[0029] In a fourth aspect, the application provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to realize the steps of the method as described above.

[0030] In a fifth aspect, the application provides a computer program product, comprising a computer program, and the computer program is executed by a processor to realize the steps of the method as described above.

[0031] The battery cell leakage detection method, system, computer device and readable storage medium described above; by acquiring the resistance time series data of the to-be-tested battery cell under the target working condition in real time, a foundation is laid for realizing real-time tracking of the resistance change characteristic; by detecting the resistance change characteristic of the resistance time series data, in the case that the resistance change characteristic of the resistance time series data meets the preset leakage judgment condition, it is determined that the to-be-tested battery cell has leakage, effectively avoiding problems such as leakage early warning lag caused by dependence on offline table lookup in the traditional technology, and insufficient judgment accuracy caused by incomplete working condition coverage, effectively improving the timeliness and accuracy of battery cell leakage early warning, so that potential faults can be found earlier, and the safety of the battery system is ensured. BRIEF DESCRIPTION OF DRAWINGS

[0032] In order to more clearly illustrate the technical solutions in the embodiments of the present application or the related art, the drawings needed to be used in the description of the embodiments of the present application or the related art will be briefly introduced. Obviously, the drawings in the following description are only some embodiments of the present application, and for those skilled in the art, other related drawings can also be obtained without creative labor.

[0033] Figure 1 A flowchart of a battery cell leakage detection method in an embodiment;

[0034] Figure 2 A flowchart of a resistance change characteristic detection step in an embodiment;

[0035] Figure 3 A flowchart of a resistance change rate data anomaly detection step in an embodiment;

[0036] Figure 4 A flowchart of a candidate change rate jump point determination step in an embodiment;

[0037] Figure 5 A schematic diagram of a battery cell leakage detection system in a laboratory safety test scenario in an embodiment;

[0038] Figure 6 A resistance curve diagram in the first embodiment;

[0039] Figure 7 An enlarged schematic diagram of the resistance curve in the first embodiment;

[0040] Figure 8 A resistance change rate curve diagram in the first embodiment;

[0041] Figure 9 An enlarged schematic diagram of the resistance change rate curve in the first embodiment;

[0042] Figure 10Fig. 2 is an enlarged schematic diagram of the resistance curve in the second embodiment;

[0043] Figure 11 Fig. 3 is an enlarged schematic diagram of the resistance change rate curve in the second embodiment;

[0044] Figure 12 Fig. 4 is an enlarged schematic diagram of the resistance curve in the third embodiment;

[0045] Figure 13 Fig. 5 is an enlarged schematic diagram of the resistance change rate curve in the third embodiment;

[0046] Figure 14 Fig. 6 is a structural block diagram of the cell leakage detection system in an embodiment;

[0047] Figure 15 Fig. 7 is an internal structural diagram of the computer device in an embodiment. DETAILED DESCRIPTION

[0048] In order to make the purposes, technical solutions and advantages of the present application clearer, the present application will be further described in detail below with reference to the drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and do not limit the present application.

[0049] Currently, cell leakage detection mainly relies on offline table lookup method, which usually applies a static voltage to the cell after a fault occurs (for example, a preliminary determination of leakage risk is made through primary or secondary detection) and measures the internal resistance, and then queries the corresponding internal resistance value according to the pre-constructed offline data table. However, such data table is only constructed based on empirical values under specific known operating conditions, and it is difficult to cover the complex and variable working conditions in actual applications, resulting in a large deviation in internal resistance estimation results. In addition, the table lookup method relies on static measurement at fixed time intervals, and cannot realize continuous and dynamic monitoring of small changes in cell resistance, making it difficult to capture subtle abnormalities caused by early leakage, limiting the sensitivity and reliability of leakage warning. To solve the technical problems existing in the above-mentioned traditional technology, the present application provides a cell leakage detection method, which aims to improve the timeliness and accuracy of cell leakage warning, so as to discover potential faults earlier and ensure the safety of the battery system.

[0050] In one embodiment, as shown in Figure 1 , Figure 1 Fig. 1 is a flowchart of the cell leakage detection method in an embodiment; the cell leakage detection method comprises the following steps:

[0051] Step S101, real-time acquisition of resistance time series data of the cell to be tested under a target working condition.

[0052] The to-be-tested battery cell can be a single battery cell of different types, for example, a lithium ion battery cell, a nickel-based battery cell, a sodium ion battery cell, or a lead-acid battery cell, or a battery cell with different electrolyte states, for example, a liquid battery cell, a semi-solid battery cell, or a solid battery cell, and the like, without specific limitation.

[0053] The target working condition refers to a specific working condition of the to-be-tested battery cell. The target working condition can be, but is not limited to, an electrical, thermal, mechanical, or the like working environment experienced by the to-be-tested battery cell in a safety test or actual operation process.

[0054] In an exemplary embodiment, when the to-be-tested battery cell is in a battery cell safety test phase, the target working condition can be specifically set according to the test type. In a thermal abuse test scenario, the target working condition can include, but is not limited to, a high-temperature environment (for example, gradually increasing from room temperature 25°C to 80°C, 120°C, 150°C, 200°C, or the like). In an electrical abuse test scenario, the target working condition can include, but is not limited to, overcharging, over-discharging, or the like abnormal electrical condition. In a mechanical abuse test scenario (for example, extrusion, drop, or impact test), the target working condition can include, but is not limited to, an external force extrusion or impact load with a specific direction and amplitude.

[0055] In another exemplary embodiment, when the to-be-tested battery cell has been put into an actual application scenario (for example, an electric vehicle or an energy storage system), the target working condition refers to a current real-time running environment of the to-be-tested battery cell. The target working condition can include, but is not limited to, a real-time charging and discharging current, an environmental temperature, a vibration condition, or the like comprehensive working condition.

[0056] The resistance time series data includes resistances of the battery cell at a plurality of continuous time points. It can be understood that the resistance time series data is used to reflect dynamic change characteristics of the resistance of the battery cell in the time dimension.

[0057] In an exemplary embodiment, the resistance time series data can be visually processed to intuitively observe a change trend of the resistance of the to-be-tested battery cell over time, thereby assisting in detecting a liquid leakage event. The visualization method can include, but is not limited to, a curve diagram, without specific limitation. For example, when a curve diagram is used to display the resistance time series data, the horizontal axis represents time, and the vertical axis represents the resistance of the battery cell.

[0058] In an exemplary embodiment, the to-be-tested battery cell is connected with a resistance measurement unit, and the resistance time series data of the to-be-tested battery cell under the target working condition is acquired in real time through the resistance measurement unit.

[0059] In step S102, resistance change characteristics detection is performed on the resistance time series data. If the resistance change characteristics of the resistance time series data meet a preset liquid leakage judgment condition, it is determined that the to-be-tested battery cell has a liquid leakage.

[0060] The resistance value change characteristic is used for characterizing the dynamic behavior characteristic of the resistance value of the battery cell in the time dimension. The resistance value change characteristic can include, but is not limited to, a resistance value change rate characteristic and a resistance value mutation characteristic. The resistance value change rate characteristic is used for characterizing the change amplitude and trend of the resistance value. The resistance value mutation characteristic is used for characterizing the abnormal jump behavior of the resistance value.

[0061] The preset liquid leakage judgment condition refers to a judgment rule used for judging whether the battery cell under test has a battery cell liquid leakage. The preset liquid leakage judgment condition can be set according to the resistance value dynamic response characteristic of the battery cell under various different working conditions (for example, high temperature, overcharge, extrusion, etc.) when the battery cell has a liquid leakage, which is not limited herein.

[0062] In an exemplary embodiment, the preset liquid leakage judgment condition setting method can be, but is not limited to, the following: testing the battery cell samples under different test working conditions (for example, thermal abuse, electrical abuse, mechanical abuse and normal operation, etc.), obtaining the respective resistance value time sequence sample data of each battery cell sample; extracting the liquid leakage characteristics of each resistance value time sequence sample data to obtain the resistance value dynamic response characteristics (for example, resistance value jump, abnormal resistance value change rate, etc.) related to the battery cell liquid leakage; and then setting the preset liquid leakage judgment condition according to the resistance value dynamic response characteristics, so as to ensure that the battery cell liquid leakage behavior can be timely and accurately identified under various actual scenarios, effectively supporting early warning and safety control.

[0063] In other embodiments, the preset liquid leakage judgment condition setting method can also be: for different types of battery cells, pre-testing the liquid leakage under different working conditions (for example, pre-testing the liquid leakage under electrical abuse, mechanical abuse or thermal abuse conditions), respectively determining the respective preset liquid leakage judgment conditions of each type of battery cell under different working conditions, so as to improve the identification accuracy of the same type of battery cell for the liquid leakage event caused by a specific working condition (electricity, mechanical or thermal).

[0064] In an exemplary embodiment, the resistance value time sequence data of the battery cell under test under the target working condition is obtained in real time by the resistance value measurement unit; the resistance value change characteristic of the resistance value time sequence data is detected to judge whether the resistance value change characteristic of the resistance value time sequence data meets the preset liquid leakage judgment condition; if it is detected that the resistance value change characteristic of the resistance value time sequence data meets the preset liquid leakage judgment condition, it is determined that the battery cell under test has a liquid leakage; and if it is detected that the resistance value change characteristic of the resistance value time sequence data does not meet the preset liquid leakage judgment condition, it is determined that the battery cell under test does not have a liquid leakage.

[0065] Compared with the traditional battery cell liquid leakage detection method mainly relying on offline table lookup, the present application can accurately and timely determine whether the battery cell under test has a liquid leakage by obtaining the resistance value time sequence data of the battery cell under test under the target working condition, extracting the resistance value change characteristic thereof, and combining the preset liquid leakage judgment condition, so as to effectively capture the early liquid leakage risk and improve the timeliness of early warning.

[0066] In addition, the present application can be applied to laboratory safety testing, thermal runaway monitoring, and actual operation of battery systems, and has high sensitivity, strong adaptability and wide applicability, providing an efficient and reliable solution for cell safety monitoring.

[0067] Specifically, in the laboratory safety testing scenario, the cell liquid leakage detection method proposed by the present application can be used to monitor the electrolyte leakage of single cells during various safety tests (such as thermal abuse, electrical abuse, mechanical abuse, etc.), so as to accurately evaluate the safety boundary and failure mechanism of the single cells.

[0068] In the thermal runaway monitoring scenario, the cell liquid leakage detection method proposed by the present application can be applied to early warning of thermal runaway of single cells under different working conditions. It should be noted that cell thermal runaway refers to a phenomenon that the heat release rate inside the cell is much higher than its heat dissipation capacity, resulting in a rapid and uncontrollable rise in temperature, which may eventually cause severe burning or explosion. The causes of thermal runaway mainly include two types: external misuse conditions, such as thermal misuse (high temperature environment), electrical misuse (overcharge, overdischarge, short circuit) or mechanical misuse (extrusion, impact, drop); internal defects, such as pole piece burr, lithium precipitation, etc., which may induce local short circuit or side reaction under normal working conditions. Before thermal runaway occurs, the cell usually undergoes a gradual failure evolution process: under the action of internal and external causes, a series of exothermic side reactions are first triggered inside the cell, causing gas production and causing the battery to swell; as the internal pressure rises, the battery shell may crack, causing electrolyte leakage; if the cause persists (such as misuse conditions not removed), the exothermic reaction will further accelerate, and the heat will continue to accumulate, causing the temperature to rise rapidly, and eventually entering the thermal runaway stage, which may evolve into a fire or even an explosion. By analyzing whether the resistance value change characteristics of the resistance value time series data meet the preset liquid leakage judgment condition, the present application can accurately and timely identify abnormalities in the early stage of liquid leakage, and realize early warning of thermal runaway events.

[0069] Further, in the application scenario of battery system level, single cells are usually integrated into battery modules or battery packs through series and / or parallel connection. When a single cell leaks, it may cause internal short circuit, which in turn leads to a rapid rise in temperature of the single cell itself or adjacent cells, triggering local thermal runaway, or even fire. Once a single cell catches fire, the heat and flames released by it are extremely easy to ignite surrounding cells, thereby inducing a chain reaction, causing thermal diffusion at the module level or even the entire battery pack level. Therefore, by using the cell liquid leakage detection method proposed by the present application, real-time monitoring and analysis of the resistance value time series data of each single cell can not only accurately locate the faulty cell that leaks, but also timely issue an early warning in the early stage of thermal diffusion, thereby gaining a critical time window for intervention measures such as thermal management, safety isolation or emergency shutdown, effectively suppressing the spread of thermal runaway, and improving the overall safety of the battery system.

[0070] In this embodiment, by acquiring the resistance time-series data of the cell under test under target operating conditions in real time, a foundation is laid for real-time tracking of resistance change characteristics. By detecting the resistance change characteristics of the resistance time-series data, if the resistance change characteristics of the resistance time-series data meet the preset leakage judgment conditions, it is determined that the cell under test has leaked. This effectively avoids the problems of delayed leakage warning caused by relying on offline table lookup in traditional technology, as well as insufficient judgment accuracy caused by incomplete operating condition coverage. It effectively improves the timeliness and accuracy of cell leakage warning, thereby enabling the early detection of potential faults and ensuring the safety of the battery system.

[0071] In one embodiment, such as Figure 2 As shown, Figure 2 This is a flowchart illustrating the resistance change characteristic detection step in one embodiment; resistance change characteristic detection is performed on the resistance timing data. If the resistance change characteristic of the resistance timing data meets the preset leakage judgment condition, it is determined that the cell under test has leaked, including the following steps:

[0072] Step S201: Perform resistance change rate analysis on the resistance timing data to obtain the resistance change rate data corresponding to the resistance timing data.

[0073] The resistance change rate data includes the resistance change rate corresponding to each of the remaining cell resistance values ​​in the resistance time series data, excluding the first cell resistance value. It should be noted that the resistance time series data has a strict time order. The first cell resistance value refers to the cell resistance value corresponding to the first sampling moment arranged in chronological order in the resistance time series data. Since the resistance value of the first cell lacks data from the previous moment, its change rate cannot be calculated and therefore it is not included in the generation of the resistance change rate data.

[0074] Among them, the resistance change rate refers to the rate of change of the cell resistance between two adjacent sampling times, and is used to characterize the magnitude of the resistance change.

[0075] In one exemplary embodiment, the resistance change rate data can be visualized to visually observe the resistance change amplitude and abnormal jump points of the tested cell, thereby assisting in the analysis of the timing of leakage events. The visualization method can include, but is not limited to, graphs, and is not specifically limited here. For example, when displaying the resistance change rate data using a graph, the horizontal axis represents time, and the vertical axis represents the resistance change rate.

[0076] In an exemplary embodiment, resistance change rate analysis is performed on the resistance timing data to obtain the resistance change rate data corresponding to the resistance timing data, including the following steps:

[0077] Step 1: For each pair of adjacent cell resistance values ​​in the resistance time series data, calculate the resistance change rate corresponding to the target cell resistance value among the adjacent cell resistance values ​​based on the resistance difference and time interval.

[0078] The resistance difference between adjacent cell values ​​represents the difference between the cell resistance values ​​at adjacent sampling times; the time interval represents the time difference between the sampling times of adjacent cell resistance values. The target cell resistance value refers to the cell resistance value at the later sampling point among the adjacent cell resistance values.

[0079] Step 2: Determine the resistance change rate corresponding to the resistance values ​​of multiple target cells as the resistance change rate data corresponding to the resistance time series data.

[0080] For example, the resistance timing data is denoted as , where t i , representing the i-th sampling time; R(t) i Let R(t1), R(t2), ..., R(t3) represent the resistance value of the battery cell under test at the i-th sampling time. For the resistance value time series data {R(t1), R(t2), ..., R(t3)}, ..., R(t4)}, ..., R(t5)}, ..., R(t6)}, ..., R(t7)}, ..., R(t8)}, ..., R(t9)}, ..., R(t1)}, n The resistance value of each pair of adjacent cells in )} , i=2,…,n, where R(t) i The target cell resistance is denoted as ; the resistance values ​​of adjacent cells are calculated. The corresponding resistance difference is The time interval is Furthermore, based on the resistance difference ΔR between adjacent cells... i and time interval Δt i The target cell resistance value R(t) among the adjacent cell resistance values ​​is calculated. i The corresponding resistance change rate is ΔR i / Δt i By analogy, the resistance change rate corresponding to the resistance values ​​of multiple target cells is obtained. The resistance change rate corresponding to the resistance values ​​of multiple target cells is determined as the resistance change rate data corresponding to the resistance time series data, which provides accurate data support for subsequent cell leakage detection.

[0081] Step S202: Perform anomaly detection on the resistance change rate data. If a target change rate jump point that meets the preset leakage judgment condition is detected in the resistance change rate data, it is determined that the cell under test has leaked.

[0082] The target change rate jump point includes time information (i.e., a sampling time) and a corresponding resistance value change rate specific value. It can be understood that the target change rate jump point is a time sequence feature identifier of the leakage of the battery under test, and is used to locate the time of the leakage event. It can be understood that the sampling time corresponding to the target change rate jump point is the leakage time of the battery under test, and the resistance value change rate corresponding to the target change rate jump point has a resistance value change response characteristic specific to the leakage.

[0083] In one exemplary embodiment, resistance time sequence data of the battery under test under a target working condition is acquired in real time, resistance value change rate analysis is performed on the resistance time sequence data to obtain resistance value change rate data corresponding to the resistance time sequence data, abnormality detection is performed on the resistance value change rate data to determine whether a target change rate jump point meeting a preset leakage judgment condition exists in the resistance value change rate data, if the target change rate jump point meeting the preset leakage judgment condition is detected in the resistance value change rate data, it is determined that the battery under test has leaked, the time at which the target change rate jump point is located is determined as the leakage time of the battery under test, and a battery safety early warning is performed based on the leakage time. If the target change rate jump point meeting the preset leakage judgment condition is not detected in the resistance value change rate data, it is determined that the battery under test has not leaked, and the collection and resistance value change characteristic detection of the resistance time sequence data are continuously and cyclically performed to ensure continuous and uninterrupted monitoring of the state of the battery under test.

[0084] In this embodiment, resistance value change rate analysis is performed on the resistance time sequence data to obtain resistance value change rate data reflecting the dynamic evolution trend of the resistance value of the battery under test. On this basis, abnormality detection is performed on the resistance value change rate data based on a preset leakage judgment condition. In the case where the target change rate jump point meeting the preset leakage judgment condition is detected in the resistance value change rate data, it is determined that the battery under test has leaked, the sampling time corresponding to the target change rate jump point is determined as the leakage time of the battery under test, and an early safety warning mechanism is triggered based on the leakage time of the battery under test to achieve a high-time-response and accurate time positioning of the leakage fault. In the case where the target change rate jump point is not detected, the collection and resistance value change characteristic detection of the resistance time sequence data are continuously and cyclically performed to ensure continuous and uninterrupted monitoring of the state of the battery under test. Therefore, the timeliness and accuracy of the battery leakage detection are effectively improved, which provides a key guarantee for preventing fire and explosion accidents caused by battery leakage. The response lag and limited working condition coverage of the traditional offline table lookup method are avoided, and the intelligentization and real-time level of the leakage monitoring are improved.

[0085] In one embodiment, as shown in Figure 3 Figure 3 ​A flowchart of a resistance change rate data anomaly detection step in an embodiment; the resistance change rate data is subjected to anomaly detection, and if a target change rate jump point satisfying a preset liquid leakage determination condition is detected in the resistance change rate data, it is determined that the battery under test has liquid leakage, including the following steps:

[0086] In step S301, the resistance change rate data is subjected to change rate mutation anomaly detection, and if a candidate change rate jump point satisfying a preset change rate mutation condition is detected in the resistance change rate data, a neighborhood resistance change rate sequence in a neighborhood of the candidate change rate jump point is determined.

[0087] The preset change rate mutation condition is used to preliminarily screen out abnormal jump events that may be caused by battery liquid leakage from the resistance change rate data. It should be noted that the preset change rate mutation condition needs to be set based on the typical resistance change response characteristics (such as mutation amplitude range, etc.) of the battery in a liquid leakage event. The specific parameters can be adjusted according to the battery type, working environment or safety level requirements, and are not specifically limited here.

[0088] It can be understood that by setting the preset change rate mutation condition, high-sensitivity preliminary screening of liquid leakage related mutation events can be achieved, taking into account the timeliness and anti-interference ability of the detection, laying a foundation for subsequent accurate determination.

[0089] The candidate change rate jump point refers to a potential abnormal point in the resistance change rate data that satisfies the preset change rate mutation condition and is identified by change rate mutation anomaly detection. It can be understood that whether the candidate change rate jump point is finally confirmed as a target change rate jump point needs to be jointly judged in combination with the change rate fluctuation amplitude detection result of the neighborhood resistance change rate sequence thereof.

[0090] The neighborhood resistance change rate sequence includes a plurality of resistance change rates within a preset time range before and after the time point of the candidate change rate jump point.

[0091] The time point of the candidate change rate jump point refers to the sampling time corresponding to the candidate change rate jump point. The preset time range before and after the time point of the candidate change rate jump point includes a first preset time range before the time point of the candidate change rate jump point and a second preset time range after the time point of the candidate change rate jump point.

[0092] It should be noted that the first preset time range and the second preset time range need to be set according to the dynamic characteristics of the battery liquid leakage and the actual demand for response timeliness of safety warning, and the specific values can be flexibly adjusted according to different battery types, application scenarios or system design requirements, and are not specifically limited here.

[0093] In an exemplary embodiment, the first preset time range can be set to 15 seconds, or 14 seconds, or 13 seconds, or 12 seconds, or 11 seconds, etc., for sufficiently capturing the resistance value change trend before the occurrence of the candidate change rate jump point; considering the requirement of the safety warning of the battery on the response timeliness, the second preset time range can be set to 7 seconds, or 6 seconds, or 5 seconds, or 4 seconds, or 3 seconds, etc., to ensure that the neighborhood change rate fluctuation verification can be quickly completed after the occurrence of the leakage event and the warning mechanism is timely triggered.

[0094] In step S302, the change rate fluctuation amplitude of the neighborhood resistance value change rate sequence is detected, and if the change rate fluctuation amplitude of the neighborhood resistance value change rate sequence does not exceed the preset change rate fluctuation range, the candidate change rate jump point is determined as the target change rate jump point.

[0095] The change rate fluctuation amplitude detection refers to detecting the fluctuation degree of the resistance value change rate in the neighborhood resistance value change rate sequence, that is, detecting the fluctuation degree of the resistance value change rate in the neighborhood of the candidate change rate jump point.

[0096] The change rate fluctuation amplitude of the neighborhood resistance value change rate sequence is used to quantify the fluctuation degree of the resistance value change rate in the neighborhood of the candidate change rate jump point.

[0097] In an exemplary embodiment, the method of detecting the change rate fluctuation amplitude of the neighborhood resistance value change rate sequence can be that the difference between the maximum resistance value change rate and the minimum resistance value change rate in the neighborhood resistance value change rate sequence is determined as the change rate fluctuation amplitude of the neighborhood resistance value change rate sequence. It can be understood that the neighborhood resistance value change rate sequence in the neighborhood of the candidate change rate jump point does not include the candidate change rate jump point itself.

[0098] The preset change rate fluctuation range is used to determine whether the change rate fluctuation amplitude corresponding to the neighborhood resistance value change rate sequence conforms to the dynamic characteristics of the battery leakage.

[0099] It should be noted that when the battery leaks, in addition to the obvious resistance jump point at the initial moment of the leakage, the resistance value usually presents a relatively flat change trend before and after the jump, that is, the resistance value change rate in the neighborhood fluctuates less; if the fluctuation amplitude of the neighborhood resistance value change rate sequence corresponding to the candidate change rate jump point exceeds the preset change rate fluctuation range, the candidate change rate jump point can be caused by noise, external interference or non-leakage transient events, and should not be confirmed as the target change rate jump point.

[0100] It should be noted that the preset change rate fluctuation range needs to be set according to the type of the battery cell and the dynamic characteristics of the liquid leakage event, and is not specifically limited here. In an exemplary embodiment, the preset change rate fluctuation range can be set to 0 mΩ / s~0.6 mΩ / s, or 0 mΩ / s~0.5 mΩ / s.

[0101] The time point corresponding to the target change rate jump point is the time point at which the battery cell under test leaks. The time point corresponding to the target change rate jump point refers to the sampling time corresponding to the target change rate jump point; the time point at which the battery cell under test leaks refers to the time at which the battery cell under test leaks, which is used for subsequent safety warning.

[0102] In an exemplary embodiment, taking the first preset time range as 15 seconds, the second preset time range as 5 seconds, and the preset change rate fluctuation range (used to determine whether the change rate fluctuation amplitude corresponding to the neighborhood resistance change rate sequence meets the dynamic characteristics of the battery cell leakage) as 0 mΩ / s~0.6 mΩ / s as an example: the resistance change rate data is subjected to change rate mutation anomaly detection to determine whether there is a candidate change rate jump point in the resistance change rate data that meets the preset change rate mutation condition; if a candidate change rate jump point that meets the preset change rate mutation condition is detected in the resistance change rate data, then a plurality of resistance change rates within 15 seconds before the time point at which the candidate change rate jump point is located and a plurality of resistance change rates within 5 seconds after the time point at which the candidate change rate jump point is located are obtained to obtain a neighborhood resistance change rate sequence in the neighborhood of the candidate change rate jump point. Further, the neighborhood resistance change rate sequence is subjected to change rate fluctuation amplitude detection, the change rate fluctuation amplitude of the neighborhood resistance change rate sequence is calculated, and it is determined whether the change rate fluctuation amplitude of the neighborhood resistance change rate sequence exceeds the preset change rate fluctuation range 0 mΩ / s~0.6 mΩ / s; if it is detected that the change rate fluctuation amplitude of the neighborhood resistance change rate sequence does not exceed the preset change rate fluctuation range, i.e., 0 mΩ / s~0.6 mΩ / s, then the candidate change rate jump point is determined as the target change rate jump point; if it is detected that the change rate fluctuation amplitude of the neighborhood resistance change rate sequence exceeds the preset change rate fluctuation range, i.e., 0 mΩ / s~0.6 mΩ / s, then the candidate change rate jump point is discarded to avoid misjudging a pseudo-mutation caused by noise, external interference, or a non-liquid leakage transient event as a real liquid leakage event.

[0103] In this embodiment, by detecting the rate of change mutation of the resistance value change rate data, candidate rate jump points meeting the preset rate of change mutation condition can be preliminarily identified. Further, for the candidate rate jump points, the neighborhood resistance value change rate sequence within the preset time range before and after the time point of the candidate rate jump point is extracted, and the neighborhood resistance value change rate sequence is subjected to rate fluctuation amplitude detection. If the rate fluctuation amplitude of the neighborhood resistance value change rate sequence does not exceed the preset rate fluctuation range, it is determined that the candidate rate jump point meets the dynamic characteristics of the battery leakage event, and thus the candidate rate jump point is confirmed as a target rate jump point. By introducing the neighborhood rate fluctuation amplitude detection strategy, the real leakage mutation and random interference can be effectively distinguished, and the accuracy and anti-false alarm capability of the leakage detection are effectively improved. At the same time, the time point corresponding to the target rate jump point is taken as the leakage occurrence time of the battery under test, and high-precision time positioning of the leakage event is realized, which provides reliable and timely decision basis for subsequent early safety warning, fault isolation and thermal runaway prevention and control.

[0104] In one embodiment, as shown in Figure 4 Figure 4 is a flowchart of the determination step of the candidate rate jump point in one embodiment. The determination step of the candidate rate jump point meeting the preset rate of change mutation condition includes the following steps:

[0105] Step S401, according to the size relationship of the resistance value change rate in the resistance value change rate data, the local maximum points in the resistance value change rate data are determined in time sequence.

[0106] Among them, the resistance value change rate corresponding to the local maximum point is the maximum resistance value change rate in the preset neighborhood window with the local maximum point as the center. Among them, the preset neighborhood window includes 2k+1 points, k is a positive integer; the window length of the preset neighborhood window=(2k+1)×sampling period; wherein the unit of the sampling period can include but is not limited to seconds, milliseconds, microseconds, etc.; it should be noted that the value of k needs to be set according to the actual detection requirement, which is not limited here; for example, when the period is in seconds, the value of k can be 1~6, or 2~5, or 3~4.

[0107] It can be understood that the local maximum point includes time information (i.e. sampling time) and corresponding resistance value change rate specific value. It should be noted that the resistance value change rate data is time series data, which has strict time sequence and sampling time sequence dependence; therefore, when determining the local maximum point, the local maximum point is determined in time sequence based on the preset neighborhood window according to the size relationship of the resistance value change rate.

[0108] In an exemplary embodiment, the resistance value change rate data is denoted as {r1, r2, …, r​n}, wherein r i , indicates the sampling time t i , the corresponding resistance change rate, i = 1, …, n; it is assumed that the preset neighborhood window includes 2k+1 points (k is a positive integer), that is, for the resistance change rate r j (wherein ), the resistance change rate r j The corresponding preset neighborhood window contains all resistance change rates within the index range According to the size relationship between the resistance change rates in the resistance change rate data, in chronological order, if it is identified that the resistance change rate r j satisfies: r j > r p , for all , p≠j, then r is determined as a local maximum point, wherein t j is the time at which the local maximum point is located, and r j is the resistance change rate corresponding to the local maximum point.

[0109] Step S402, the first local maximum point with a resistance change rate greater than a preset change rate threshold is determined as a candidate change rate jump point that satisfies a preset change rate mutation condition.

[0110] The preset change rate threshold is used to preliminarily screen out abnormal jump events that may be caused by cell leakage from the resistance change rate data. It should be noted that the preset change rate threshold needs to be set based on the typical resistance change response characteristics of the cell in the leakage event. The specific value can be adjusted according to the cell type, working environment or safety level requirement, and is not specifically limited here.

[0111] In an exemplary embodiment, the preset change rate threshold can be in the range of 0.5 mΩ / s~20 mΩ / s, or 0.6 mΩ / s~16 mΩ / s, or 0.6 mΩ / s~14 mΩ / s, or 0.6 mΩ / s~12 mΩ / s, or 0.6 mΩ / s~10 mΩ / s, or 0.6 mΩ / s~7 mΩ / s. The preset change rate threshold is greater than the upper limit value corresponding to the preset change rate fluctuation range.

[0112] It should be noted that in the present embodiment, the first local maximum point with a resistance change rate greater than the preset change rate threshold is determined as a candidate change rate jump point that satisfies the preset change rate mutation condition, and the reason is as follows:

[0113] When the cell has a breakage leakage, a significant and isolated resistance mutation feature is usually generated at the initial leakage time; the mutation corresponds to the initial occurrence time of the leakage event, which has early warning value. The first local maximum point with a resistance change rate greater than the preset change rate threshold is a potential abnormal point, which may correspond to the shell breakage event caused by the initial leakage of electrolyte.

[0114] If the subsequent change rate fluctuation amplitude detection detects that the change rate fluctuation amplitude of the neighborhood resistance change rate sequence in the neighborhood of the current candidate change rate jump point does not exceed the preset change rate fluctuation range, the current candidate change rate jump point can be confirmed as the target change rate jump point; in this case, the jump point appearing after the target change rate jump point usually reflects subsequent chain failure processes such as leakage intensification, internal short circuit, side reaction, cell structure failure and even thermal runaway, which no longer represents the initial breakage leakage behavior, and thus is not suitable for the determination and early warning of the initial leakage event.

[0115] If the subsequent change rate fluctuation amplitude detection detects that the change rate fluctuation amplitude of the neighborhood resistance change rate sequence in the neighborhood of the current candidate change rate jump point exceeds the preset change rate fluctuation range, the current candidate change rate jump point is discarded, and the time corresponding to the current candidate change rate jump point is taken as a new cell leakage detection starting time. In the subsequent resistance change rate data, the first local maximum point with a resistance change rate greater than the preset change rate threshold is detected as a new candidate change rate jump point, and the neighborhood resistance change rate sequence change rate fluctuation amplitude detection process is continued to be executed, and so on.

[0116] It can be understood that the embodiment can realize accurate positioning of the initial leakage by capturing the target change rate jump point, thereby supporting the timely start of early warning, fault isolation and thermal runaway prevention and control and other active safety measures.

[0117] In an exemplary embodiment, according to the size relationship of the resistance change rate in the resistance change rate data, the local maximum points in the resistance change rate data are determined in time sequence, the first local maximum point with a resistance change rate greater than the preset change rate threshold is determined as a candidate change rate jump point satisfying the preset change rate mutation condition; the neighborhood resistance change rate sequence in the neighborhood of the candidate change rate jump point is further determined; the change rate fluctuation amplitude of the neighborhood resistance change rate sequence is detected, if the change rate fluctuation amplitude of the neighborhood resistance change rate sequence does not exceed the preset change rate fluctuation range, the candidate change rate jump point is determined as the target change rate jump point; if the change rate fluctuation amplitude of the neighborhood resistance change rate sequence exceeds the preset change rate fluctuation range, the candidate change rate jump point is discarded, and the time point of the candidate change rate jump point is taken as a new cell leakage detection starting time, and the above cell leakage detection method is re-executed.

[0118] In this embodiment, by the size relationship of the resistance value change rate in the resistance value change rate data, the local maximum points are identified in time sequence, and the first local maximum point with the resistance value change rate exceeding the preset change rate threshold is further screened out as the candidate change rate jump point, so that the liquid leakage judgment is always based on the earliest mutation characteristics in the initial stage of liquid leakage, thereby improving the timing accuracy of liquid leakage detection and the effectiveness of early warning.

[0119] In one embodiment, the cell liquid leakage detection method further comprises:

[0120] In the case where the resistance value change characteristic of the resistance value time sequence data meets the preset liquid leakage judgment condition, a liquid leakage warning signal is generated for cell safety warning.

[0121] The liquid leakage warning signal carries the liquid leakage occurrence time of the to-be-tested cell, and the liquid leakage occurrence time of the to-be-tested cell is equal to the time point corresponding to the target change rate jump point.

[0122] For example, in the case where the resistance value change characteristic of the resistance value time sequence data meets the preset liquid leakage judgment condition, it is determined that there is a target change rate jump point in the resistance value change rate data corresponding to the resistance value time sequence data that meets the preset liquid leakage judgment condition; the time point corresponding to the target change rate jump point is determined as the time point of liquid leakage of the to-be-tested cell, i.e. the liquid leakage occurrence time of the to-be-tested cell, and then a liquid leakage warning signal is generated based on the liquid leakage occurrence time of the to-be-tested cell for cell safety warning.

[0123] In this embodiment, by determining the time point corresponding to the target change rate jump point as the time point of liquid leakage of the to-be-tested cell, i.e. the liquid leakage occurrence time of the to-be-tested cell, and generating a liquid leakage warning signal based on the liquid leakage occurrence time of the to-be-tested cell, high-timing and high-accuracy safety warning of the cell liquid leakage event is realized.

[0124] In one specific embodiment, referring to Figure 5 Taking a laboratory safety test scene as an example, the cell liquid leakage detection system comprises a cell clamp 1, a to-be-tested cell 2, an external wire 3, a collection clamp 4, a resistance value measurement unit 5, a data processing unit 6, and an alarm unit 7.

[0125] The electric core clamp 1 is used for simulating the actual working environment of a battery pack or a module, and provides necessary mechanical constraint force for the to-be-tested electric core 2 to suppress violent expansion or instantaneous explosion of the to-be-tested electric core 2 in the process of thermal runaway or internal short circuit. Different mechanical constraint forces will affect the internal electrode contact state and interface characteristics of the to-be-tested electric core 2, and then affect the resistance value measurement value of the electric core; the electric core clamp 1 ensures that the mechanical state of the to-be-tested electric core 2 in each safety test is consistent, so that the resistance value data obtained has good comparability. It should be noted that when the battery is subjected to mechanical misuse scenarios such as extrusion and falling in the electric core safety test, the electric core clamp 1 can also not be used.

[0126] The external wire 3 is used to connect the to-be-tested electric core 2 and the acquisition clamp 4 of the resistance value measurement unit 5; one end of the acquisition clamp 4 is fixedly connected with the lead-out wire of the resistance value measurement unit 5, and the other end is used to clamp the external wire 3.

[0127] The resistance value measurement unit 5 is used for collecting the electric core resistance value data of the to-be-tested electric core 2, and transmitting the electric core resistance value data to the data processing unit 6. It should be noted that the resistance value measurement unit 5 is arranged outside the preset safety distance from the to-be-tested electric core 2, so as to avoid being damaged when the electric core occurs abnormal events such as thermal runaway, fire or explosion, so as to ensure the continuous availability of the resistance value measurement unit 5 and the reliability of the test data.

[0128] The data processing unit 6 is used for executing the electric core leakage detection method to determine whether the to-be-tested electric core 2 leaks. If leakage occurs, a leakage warning signal is generated and sent to the alarm unit 7, and the alarm unit 7 emits a buzzing warning after receiving the leakage warning signal.

[0129] The following describes the electric core leakage detection method under different test conditions:

[0130] In example one, the target working condition is a high-temperature environment, the range of the preset change rate threshold is set to 2mΩ / s-7mΩ / s; the first preset time range in the preset time range before and after the time point of the candidate change rate jump point is set to 15 seconds, and the second preset time range is set to 5 seconds; and the preset change rate fluctuation range is set to 0mΩ / s-0.6mΩ / s.

[0131] The to-be-tested battery is connected with the resistance measurement unit, the data processing unit, and the alarm unit, and is placed in the environmental box. The safety test is performed by gradually increasing the temperature of the environmental box under room temperature of 25°C: from 25°C to 80°C for 8 hours, to 120°C for 2 hours, to 150°C for 2 hours, and to 200°C for 30 minutes. During the temperature increasing process, the resistance measurement unit continuously collects the total alternating current resistance (ACR) of the to-be-tested battery and the connecting line, and obtains the resistance time series data of the to-be-tested battery under different environmental temperatures. The data processing unit executes the battery leakage detection method recorded in the above embodiments, and obtains the resistance curve corresponding to the resistance time series data (as shown in Figure 6 and Figure 7 ) and the resistance change rate curve corresponding to the resistance change rate data (as shown in Figure 8 and Figure 9 ). As shown in Figure 7 , the resistance change of the to-be-tested battery presents a step jump phenomenon at the red circle. As shown in Figure 9 , it is determined by detection that the to-be-tested battery appears the target change rate jump point at the red box, that is, the leakage event occurs at the time point of the target change rate jump point. After detecting the target change rate jump point, the data processing unit generates a leakage warning signal (carrying the time point of the leakage occurrence, that is, the time point of the target change rate jump point) and sends it to the alarm unit, and the alarm unit issues a battery safety buzzer alarm. It should be noted that in the later stage of the test experiment, the temperature of the to-be-tested battery is high, and the state of the battery is overall rupture, fire and explosion, so the resistance and the resistance change rate of the battery are abnormally large.

[0132] In example two, the target working condition is overcharge condition; the range of the preset change rate threshold is set to 1 mΩ / s-7 mΩ / s; the first preset time range in the preset time range before and after the time point of the candidate change rate jump point is set to 15 seconds, and the second preset time range is set to 5 seconds; and the preset change rate fluctuation range is set to 0 mΩ / s-0.6 mΩ / s.

[0133] The normal full or less than full to-be-tested battery is connected with the resistance measurement unit, the data processing unit, and the alarm unit. During the charging process, the resistance measurement unit continuously collects the total alternating current resistance (ACR) of the to-be-tested battery and the connecting line, and obtains the resistance time series data of the to-be-tested battery under different charging stages. The data processing unit executes the battery leakage detection method recorded in the above embodiments, and obtains the resistance curve corresponding to the resistance time series data (as shown in Figure 10 ) and the resistance change rate curve corresponding to the resistance change rate data (as shown in Figure 11 ). It is determined by detection that the to-be-tested battery appears the target change rate jump point at Figure 11The target rate of change jump point appears in the red box (and...). Figure 10 (Corresponding to the red box), that is, a leakage event occurs at the time point corresponding to the target rate of change jump point; after detecting the target rate of change jump point, the data processing unit immediately generates a leakage warning signal (carrying the time of leakage occurrence, i.e., the time point corresponding to the target rate of change jump point) and sends it to the alarm unit, which then issues a cell safety buzzer alarm. It should be noted that... Figure 11 The positive (2.195mΩ / s) and negative (-1.164mΩ / s) values ​​of the resistance change rate at the red box are due to the high acquisition accuracy at the jump point. At this time, the sum of the positive (2.195mΩ / s) and negative (-1.164mΩ / s) values, 2.195-1.164=1.031mΩ / s, can be compared with the preset change rate threshold to determine the target change rate jump point.

[0134] Example 3: The target working condition is mechanical extrusion; the preset change rate threshold is set to a range of 0.6mΩ / s to 2mΩ / s; the first preset time range before and after the candidate change rate jump point is set to 15 seconds, and the second preset time range is set to 5 seconds; the preset change rate fluctuation range is set to 0mΩ / s to 0.6mΩ / s.

[0135] In mechanical abuse testing scenarios such as compression, the battery cell under test does not require constraint using a cell clamp; the battery cell under test is connected to a resistance measurement unit, a data processing unit, and an alarm unit. During the mechanical compression of the battery cell under test, the resistance measurement unit continuously collects the total AC impedance (ACR) of the battery cell under test and its connecting lines to obtain resistance timing data of the battery cell under test under different compression degrees; the data processing unit executes the cell leakage detection method described in the above embodiment to obtain the resistance curve corresponding to the resistance timing data (e.g., ...). Figure 12 As shown), and the resistance change rate curve corresponding to the resistance change rate data (as shown). Figure 13 (As shown). The test cell was determined to be in... Figure 13 The target rate of change jump point appears in the red box (and...). Figure 12 (Corresponding to the red box) This means that a leakage event occurs at the time point corresponding to the target rate of change jump. After detecting the target rate of change jump, the data processing unit immediately generates a leakage warning signal (carrying the time of leakage, i.e., the time point of the target rate of change jump) and sends it to the alarm unit, which then issues a cell safety buzzer alarm. It should be noted that the above-mentioned mechanical squeezing method can be achieved, but is not limited to, manual squeezing, automatic squeezing, etc., and is not specifically limited here.

[0136] Based on the above experiment, it can be concluded that the application can accurately and in real time detect the liquid leakage phenomenon of the battery cell during the safety test. Compared with the traditional technology, the application has higher detection sensitivity. Even when the electrolyte leaks slightly, the liquid leakage event can be identified in time through the dynamic characteristics of the resistance time series data and the resistance change rate. At the same time, the application has wide applicability and can be applied to high temperature, overcharge, mechanical extrusion and other scenes. It does not depend on specific working conditions or complex sample databases and can be directly applied to battery cells of different chemical systems and structural types without additional calibration or model adaptation.

[0137] In one specific embodiment, the battery cell liquid leakage detection method comprises the following methods:

[0138] Step 1, real-time acquisition of resistance time series data of the battery cell under target working conditions.

[0139] Step 2, resistance change rate analysis of the resistance time series data to obtain resistance change rate data corresponding to the resistance time series data.

[0140] Step 3, change rate mutation anomaly detection of the resistance change rate data. If a candidate change rate jump point that meets the preset change rate mutation condition is detected in the resistance change rate data, the neighborhood resistance change rate sequence in the neighborhood of the candidate change rate jump point is determined.

[0141] Step 4, change rate fluctuation amplitude detection of the neighborhood resistance change rate sequence. If the change rate fluctuation amplitude of the neighborhood resistance change rate sequence does not exceed the preset change rate fluctuation range, the candidate change rate jump point is determined as the target change rate jump point, and the time point corresponding to the target change rate jump point is determined as the liquid leakage occurrence time of the battery cell.

[0142] Step 5, based on the liquid leakage occurrence time of the battery cell, a liquid leakage warning signal is generated and sent to the alarm unit for battery safety warning.

[0143] The above battery cell liquid leakage detection method, by real-time acquisition of resistance time series data of the battery cell under target working conditions, lays a foundation for realizing real-time tracking of resistance change characteristics. By detecting the resistance change characteristics of the resistance time series data, the battery cell is determined to have liquid leakage when the resistance change characteristics of the resistance time series data meet the preset liquid leakage judgment condition, effectively avoiding the problems of liquid leakage warning lag caused by dependence on offline lookup in traditional technology and insufficient judgment accuracy caused by incomplete working condition coverage, effectively improving the timeliness and accuracy of battery cell liquid leakage warning, so that potential faults can be found earlier and the safety of the battery system is ensured.

[0144] It should be understood that although the steps in the flowcharts involved in the embodiments described above are shown in sequence according to the arrows, these steps are not necessarily executed in the order indicated by the arrows. Unless otherwise specified herein, the execution of these steps is not strictly limited in sequence, and these steps can be executed in other orders. Moreover, at least some of the steps in the flowcharts involved in the embodiments described above can include multiple steps or multiple stages, which are not necessarily executed at the same time, but can be executed at different times, and the execution order of these steps or stages is not necessarily sequential, but can be alternately or alternately executed with at least part of other steps or steps or stages in other steps.

[0145] Based on the same inventive concept, the embodiments of the present application also provide a battery leakage detection system for implementing the battery leakage detection method described above. The implementation scheme for solving the problem provided by the system is similar to the implementation scheme described in the above method, so the specific limitations in one or more battery leakage detection system embodiments provided below can refer to the limitations of the battery leakage detection method described above, which will not be repeated here.

[0146] In one exemplary embodiment, as shown in Figure 14 A battery leakage detection system is provided, which includes a data processing unit, a resistance measurement unit, and an alarm unit; the data processing unit is connected with the resistance measurement unit and the alarm unit respectively; the resistance measurement unit is connected with the battery to be tested;

[0147] The resistance measurement unit is configured to collect resistance time series data of the battery to be tested under a target working condition in real time, and transmit the resistance time series data to the data processing unit;

[0148] The data processing unit is configured to execute the battery leakage detection method described in any of the above embodiments;

[0149] The alarm unit is configured to generate a battery safety warning according to the leakage early warning signal generated by the data processing unit.

[0150] The data processing unit can include, but is not limited to, a controller, which is not limited here.

[0151] In other embodiments, the data processing unit can also be configured to visually process the resistance time series data and the resistance change rate data corresponding to the resistance time series data, so as to intuitively observe the dynamic change trend and abnormal mutation characteristics of the resistance of the battery to be tested, thereby identifying potential leakage events in a timely manner and providing visual support for safety warning decisions.

[0152] The above battery leakage detection system lays a foundation for realizing real-time tracking of the resistance value change characteristic by acquiring resistance value time sequence data of the battery to be detected under the target working condition in real time, detects the resistance value change characteristic of the resistance value time sequence data, and determines that the battery to be detected has leakage in a case where the resistance value change characteristic of the resistance value time sequence data meets a preset leakage judgment condition, effectively avoiding problems such as leakage early warning lag caused by dependence on offline table lookup in the prior art and insufficient judgment accuracy caused by incomplete working condition coverage, effectively improving timeliness and accuracy of battery leakage early warning, and thus potential faults can be found earlier, and the safety of the battery system is ensured.

[0153] In an example embodiment, a computer device, which can be a server, is provided, and an internal structure diagram of the computer device can be as shown in Figure 15 The computer device includes a processor, a memory, an input / output interface (I / O) and a communication interface. The processor, the memory and the input / output interface are connected through a system bus, and the communication interface is connected to the system bus through the input / output interface. The processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system, a computer program and a database. The internal memory provides an environment for running of the operating system and the computer program in the non-volatile storage medium. The database of the computer device is configured to store battery leakage detection related data. The input / output interface of the computer device is configured to exchange information between the processor and external devices. The communication interface of the computer device is configured to communicate with terminals outside through network connection. The computer program is executed by the processor to implement a battery leakage detection method.

[0154] Those skilled in the art can understand that Figure 15 The structure shown in the above embodiment is only a block diagram of part of the structure related to the scheme of the present application, and does not constitute a limitation on the computer device to which the scheme of the present application is applied. Specifically, the computer device can include more or fewer components than those shown in the figure, or combine certain components, or have a different arrangement of components.

[0155] In an embodiment, a computer device is also provided, which includes a memory and a processor. The memory stores a computer program, and the processor implements the steps in the above method embodiments when executing the computer program.

[0156] In an embodiment, a computer readable storage medium is provided, which stores a computer program. The computer program is executed by a processor to implement the steps in the above method embodiments.

[0157] In an embodiment, a computer program product is provided, comprising a computer program which, when executed by a processor, implements the steps of any of the above method embodiments.

[0158] Those skilled in the art can understand that all or part of the processes in the above-mentioned embodiment methods can be completed by instructing related hardware through a computer program. The computer program can be stored in a non-volatile computer readable storage medium, and when executed, can include the processes of the above-mentioned method embodiments. Any reference to a memory, database or other medium used in the embodiments provided in the present application can include at least one of a non-volatile memory and a volatile memory. The non-volatile memory can include a read-only memory (ROM), a magnetic tape, a floppy disk, a flash memory, an optical storage, a high-density embedded non-volatile memory, a resistive random access memory (ReRAM), a magnetoresistive random access memory (MRAM), a ferroelectric random access memory (FRAM), a phase change memory (PCM), a graphene memory, etc. The volatile memory can include a random access memory (RAM) or an external cache memory, etc. As an illustration but not limitation, the RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc. The database involved in the embodiments provided in the present application can include at least one of a relational database and a non-relational database. The non-relational database can include a distributed database based on a block chain, etc., without being limited thereto. The processor involved in the embodiments provided in the present application can be a general processor, a central processing unit, a graphics processing unit, a digital signal processor, a programmable logic device, a data processing logic device based on quantum computing, an artificial intelligence (AI) processor, etc., without being limited thereto.

[0159] Any combination of the technical features of the above embodiments can be made. In order to make the description concise, all possible combinations of the technical features in the above embodiments are not described, however, as long as the combination of the technical features does not exist, it should be considered as the scope of the present application.

[0160] The above-described embodiments are merely illustrative of several embodiments of the present application, and the description is relatively specific and detailed, but should not be understood as a limitation on the scope of the patent. It should be noted that for those skilled in the art, without departing from the concept of the present application, a number of modifications and improvements can be made, which are all within the scope of the present application. Therefore, the scope of protection of the present application should be subject to the appended claims.

Claims

1. A method for detecting battery cell leakage, characterized in that, The method includes: Real-time acquisition of resistance time-series data of the battery cell under test under target operating conditions; the resistance time-series data includes the battery cell resistance values ​​corresponding to multiple consecutive time points; The resistance change characteristics of the resistance time series data are detected. If the resistance change characteristics of the resistance time series data meet the preset leakage judgment conditions, it is determined that the cell under test has leaked.

2. The method according to claim 1, characterized in that, The step of detecting the resistance change characteristics of the resistance timing data, and determining that the cell under test has leaked if the resistance change characteristics of the resistance timing data meet the preset leakage judgment conditions, includes: The resistance change rate analysis is performed on the resistance time series data to obtain the resistance change rate data corresponding to the resistance time series data; the resistance change rate data includes the resistance change rate corresponding to each of the remaining cell resistance values ​​in the resistance time series data except for the first cell resistance value. Anomaly detection is performed on the resistance change rate data. If a target change rate jump point that meets the preset leakage judgment condition is detected in the resistance change rate data, it is determined that the cell under test has leaked.

3. The method according to claim 2, characterized in that, The step of performing resistance change rate analysis on the resistance time series data to obtain the resistance change rate data corresponding to the resistance time series data includes: For each pair of adjacent cell resistance values ​​in the resistance value timing data, the resistance change rate corresponding to the target cell resistance value among the adjacent cell resistance values ​​is calculated based on the resistance difference and time interval. The target cell resistance value refers to the cell resistance value with a later time point among the adjacent cell resistance values. The resistance change rate corresponding to the resistance values ​​of multiple target cells is determined as the resistance change rate data corresponding to the resistance time series data.

4. The method according to claim 2, characterized in that, The step of anomaly detection of the resistance change rate data, wherein if a target change rate jump point satisfying a preset leakage judgment condition is detected in the resistance change rate data, it is determined that the cell under test has leaked, includes: The resistance change rate data is subjected to abrupt change rate anomaly detection. If a candidate change rate jump point that meets the preset change rate jump condition is detected in the resistance change rate data, then a neighborhood resistance change rate sequence in the neighborhood of the candidate change rate jump point is determined. The neighborhood resistance change rate sequence includes multiple resistance change rates within a preset time range before and after the time point of the candidate change rate jump point. The fluctuation amplitude of the rate of change of the neighborhood resistance value sequence is detected. If the fluctuation amplitude of the rate of change of the neighborhood resistance value sequence does not exceed the preset fluctuation range, the candidate rate of change jump point is determined as the target rate of change jump point. The time point corresponding to the target rate of change jump point is the time point when the cell under test leaks.

5. The method according to claim 4, characterized in that, The steps for determining candidate rate of change jump points that meet the preset rate of change abrupt change conditions include: Based on the magnitude relationship of the resistance change rate in the resistance change rate data, the local maximum point in the resistance change rate data is determined in chronological order; the resistance change rate corresponding to the local maximum point is the maximum resistance change rate within a preset neighborhood window centered on the time point where the local maximum point is located. The local maximum point where the first rate of change of resistance is greater than a preset rate of change threshold is identified as a candidate rate of change jump point that satisfies the preset rate of change abrupt change condition.

6. The method according to claim 5, characterized in that, The preset rate of change threshold ranges from 0.6 mΩ / s to 20 mΩ / s; The preset rate of change fluctuation range is 0 mΩ / s to 0.6 mΩ / s.

7. The method according to claim 1, characterized in that, The method further includes: If the resistance change characteristics of the resistance timing data meet the preset leakage judgment conditions, a leakage warning signal is generated to provide a cell safety warning.

8. A battery cell leakage detection system, characterized in that, The battery cell leakage detection system includes a data processing unit, a resistance measurement unit, and an alarm unit; the data processing unit is connected to both the resistance measurement unit and the alarm unit; the resistance measurement unit is connected to the battery cell under test. The resistance measurement unit is used to collect the resistance timing data of the cell under test in real time under the target operating conditions, and transmit the resistance timing data to the data processing unit. The data processing unit is used to execute the cell leakage detection method according to any one of claims 1 to 7; The alarm unit is used to provide a cell safety warning based on the leakage warning signal generated by the data processing unit.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, characterized in that, When the processor executes the computer program, it implements the steps of the method according to any one of claims 1 to 7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the steps of the method according to any one of claims 1 to 7.

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