Power battery lithium precipitation anomaly detection method

Abstract

The invention relates to a power battery lithium precipitation anomaly detection method, a power battery lithium precipitation anomaly detection device and a computer readable storage medium. The power battery lithium precipitation anomaly detection method comprises the following steps: S1, performing multiple rounds of first working condition tests on a power battery cycle; s2, after multiple rounds of first working condition tests are completed, one round or multiple rounds of second working condition tests are carried out on the power battery, the second working condition tests comprise a charging section, a standing section and a discharging section, and in the second working condition tests, multiple second battery parameters of the power battery are measured; and S3, lithium precipitation abnormity of the power battery is determined according to comparison between the measured value of the battery parameter in the second plurality of battery parameters and a preset threshold value of the battery parameter, and the charge-discharge rate of the first working condition test is larger than that of the second working condition test.

Description

Technical Field

[0001] The present disclosure relates to the field of batteries, and in particular to a method for detecting abnormal lithium deposition in a power battery, a device for detecting abnormal lithium deposition in a power battery, and a computer-readable storage medium. Background Art

[0002] During the production, assembly and use of power batteries, various defects may occur inside the battery cells. For example, during the charge and discharge cycle of lithium-ion batteries, lithium ions may not be able to be normally embedded or deintercalated between the positive and negative electrodes. The Li+ that cannot be embedded in the negative electrode can only obtain electrons on the surface of the negative electrode, thus forming a silvery-white metallic lithium element, that is, lithium ions are precipitated on the surface of the negative electrode. The lithium precipitation phenomenon will accelerate the attenuation of the battery cell life, have a serious impact on the performance of the battery cell, and even create safety hazards. However, conventional detection methods of power battery production lines are difficult to identify defects inside power batteries, and the disassembly inspection method may have problems such as complex disassembly work, high cost, slow inspection results, and battery cell damage. Summary of the invention

[0003] In view of the above problems, the present disclosure aims to provide a method for detecting abnormal lithium deposition in a power battery, a device for detecting abnormal lithium deposition in a power battery, and a computer-readable storage medium.

[0004] According to a first aspect of the present disclosure, a method for detecting abnormal lithium deposition in a power battery is provided, comprising the following steps: S1: performing multiple rounds of first operating condition tests on the power battery; S2: after completing multiple rounds of first operating condition tests, performing one or more rounds of second operating condition tests on the power battery, wherein the second operating condition test includes a charging section, a static section, and a discharging section, and wherein, in the second operating condition test, a second plurality of battery parameters of the power battery are measured; and S3: determining the abnormal lithium deposition of the power battery based on a comparison between a measured value of a battery parameter among the second plurality of battery parameters and a predetermined threshold value of the battery parameter, wherein the charge and discharge rate of the first operating condition test is greater than the charge and discharge rate of the second operating condition test.

[0005] According to the method for detecting abnormal lithium deposition in a power battery in an embodiment of the present disclosure, wherein a first operating condition test includes a charging section, a static section, and a discharging section, and wherein, in the first operating condition test, a first plurality of battery parameters of the power battery are measured, the method further includes: determining the abnormal lithium deposition of the power battery based on comparison of the measured value of a battery parameter in the first plurality of battery parameters with a predetermined threshold value of the battery parameter.

[0006] According to the method for detecting abnormal lithium deposition in a power battery in an embodiment of the present disclosure, the number of rounds of the first operating condition test is greater than 100 rounds, the charge and discharge rate is greater than 5C, and the charge and discharge rate of the second operating condition test is 1C.

[0007] According to the method for detecting abnormal lithium deposition in a power battery in an embodiment of the present disclosure, wherein the second plurality of battery parameters includes a ratio of discharge capacity to charge capacity, step S3 further includes: if the ratio of discharge capacity to charge capacity is less than a predetermined ratio of discharge capacity to charge capacity, determining that the power battery has abnormal lithium deposition.

[0008] According to the method for detecting abnormal lithium deposition in a power battery in an embodiment of the present disclosure, wherein the second plurality of battery parameters include a voltage differential value, step S3 further includes: if the voltage differential value between the last second of the charging segment and the first second of the start of the static segment is greater than a predetermined voltage differential value, then determining that the power battery has abnormal lithium deposition.

[0009] According to the method for detecting abnormal lithium deposition in a power battery in an embodiment of the present disclosure, wherein the second plurality of battery parameters include a voltage differential value, step S3 further includes: if the voltage differential value between the last second of the charging segment and the first second of the start of the static segment deviates from the predetermined voltage differential value by a first deviation threshold in a predetermined number of rounds of second operating condition tests, then it is determined that the power battery has abnormal lithium deposition.

[0010] According to the method for detecting abnormal lithium deposition in a power battery in an embodiment of the present disclosure, wherein the second plurality of battery parameters include a voltage platform value, step S3 further includes: if the voltage platform value deviates from a predetermined voltage platform value by a second deviation threshold value in one or more rounds of second operating condition tests, determining that the power battery has abnormal lithium deposition.

[0011] According to the method for detecting abnormal lithium plating in power batteries in an embodiment of the present disclosure, the form of the battery includes one or more of the following: soft-pack battery, square-shell battery, cylindrical battery, the positive electrode material of the battery includes one or more of the following: nickel cobalt manganese oxide positive electrode material, nickel cobalt aluminum oxide lithium positive electrode material, lithium manganese oxide positive electrode material, lithium cobalt oxide positive electrode material, lithium iron phosphate positive electrode material, and the negative electrode material of the battery includes one or more of the following: graphite negative electrode material, silicon oxide negative electrode material, silicon-carbon composite negative electrode material, lithium titanate negative electrode material, lithium metal negative electrode material, and nano negative electrode material.

[0012] According to a second aspect of the present disclosure, a power battery lithium deposition abnormality detection device is provided, the power battery lithium deposition abnormality detection device comprising a memory and a processor, the memory storing instructions, and when the instructions are executed by the processor, the method described in any of the aforementioned embodiments is implemented.

[0013] According to a third aspect of the present disclosure, a computer-readable storage medium is provided. The computer-readable storage medium stores instructions, and when the instructions are executed by a processor, the method described in any of the above embodiments is implemented.

[0014] The present disclosure provides a non-destructive testing method that combines multiple rounds of operating condition testing with multiple battery parameter analysis, which can efficiently identify lithium plating in power batteries. By analyzing parameters such as voltage platform value, voltage differential, and charge / discharge capacity ratio, the battery health status can be monitored in real time without disassembling the battery, providing early warning and significantly improving the safety and service life of the battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] The above and other objects and advantages of the present disclosure will become more fully apparent from the following detailed description taken in conjunction with the accompanying drawings, wherein the same or similar elements are denoted by the same reference numerals.

[0016] Figure 1 A schematic flow chart of a method 100 for detecting abnormal lithium deposition in a power battery according to some embodiments is shown. DETAILED DESCRIPTION

[0017] The description of the following specific embodiments is merely exemplary in nature and is not intended to limit the disclosed technology or the application and use of the disclosed technology. In addition, it is not intended to be bound by any express or implied theory presented in the aforementioned technical field, background technology or the following specific embodiments.

[0018] In the following detailed description of the embodiments, many specific details are set forth in order to provide a more thorough understanding of the disclosed technology. However, it is apparent to one of ordinary skill in the art that the disclosed technology can be practiced without these specific details. In other instances, well-known features are not described in detail to avoid unnecessarily complicating the description.

[0019] Terms such as “comprise” and “include” indicate that in addition to the units and steps directly and explicitly stated in the specification, the technical solution of the present disclosure does not exclude the situation where it has other units and steps that are not directly or explicitly stated.

[0020] Hereinafter, various exemplary embodiments according to the present disclosure will be described in detail with reference to the accompanying drawings.

[0021] Figure 1 The flowchart of the power battery lithium deposition abnormality detection method 100 according to some embodiments is shown. The power battery lithium deposition abnormality detection method 100 disclosed in the present invention may include the following steps:

[0022] In step S1, the power battery is cycled for multiple rounds of the first operating condition test. The first operating condition test can, for example, simulate the working condition of the battery under high load to accelerate the aging process of the battery, especially in the case of high rate charge and discharge. The charge and discharge rate of this step is usually set to be greater than the charge and discharge rate of the second operating condition test (for example, a charge and discharge test is performed at a high rate of 5C or more) to ensure that the performance of the battery under extreme load is fully evaluated. In this process, multiple parameters of the battery (such as voltage, current, temperature, capacity, etc.) will be monitored and recorded in real time. Through multiple rounds of high rate tests, the performance changes of the battery in different charge and discharge cycles can be obtained, providing data support for subsequent lithium analysis anomaly detection. For example, a 5Ah power type ternary lithium-ion battery cell can be used, and the charge and discharge rate is set to 10C for the first operating condition test. The charging time and discharge time of each cycle will be significantly shortened, thereby quickly generating higher heat. This process can not only simulate the temperature rise of the battery under extreme load, but also accelerate the internal aging of the battery, which is convenient for determining the impact of high rate charge and discharge on battery internal resistance, capacity, temperature and other performance indicators.

[0023] In step S2, after completing multiple rounds of the first operating condition test, one or more rounds of the second operating condition test are performed on the power battery, wherein the second operating condition test includes a charging section, a static section, and a discharging section, and wherein, in the second operating condition test, a second plurality of battery parameters of the power battery are measured. After completing multiple rounds of the first operating condition test, step S2 is entered to start one or more rounds of the second operating condition test. The second operating condition test may be to evaluate the battery at a more conventional charge and discharge rate (e.g., 1C). Unlike the first operating condition test, the charge and discharge rate of the second operating condition test is relatively low, simulating the performance of the battery under normal use conditions. The test includes a charging section, a static section, and a discharging section. During the charging process, parameters such as battery voltage and current will be recorded; the static section helps to observe the voltage changes of the battery in the uncharged and discharged states; in the discharge section, the discharge capacity and voltage changes of the battery will be recorded in detail. These parameters are used for comparison with a predetermined threshold in the subsequent step S3 to determine whether lithium precipitation occurs. For example, in the second working condition test, after the battery is charged to 4.2V (full charge), it is left to stand for one hour and then discharged to 2.8V at 1C. During this period, the voltage, current, capacity and other parameters of the battery during the charging and discharging process are monitored to determine whether the battery is normal. By comparing with the data recorded in the first working condition test, the health status of the battery is analyzed.

[0024] In step S3, the lithium plating anomaly of the power battery is determined based on the comparison of the measured value of the battery parameter in the second plurality of battery parameters with the predetermined threshold value of the battery parameter. Among them, the charge and discharge rate of the first operating condition test is greater than the charge and discharge rate of the second operating condition test. Step S3 can be used to determine abnormal changes in battery parameters, such as the ratio of discharge capacity to charging capacity. If the ratio is significantly lower than the predetermined standard (such as lower than 0.9), it may indicate that the active lithium inside the battery is lost, resulting in the inability to fully release the battery capacity, and lithium plating may occur. Another example is the voltage difference: calculate the voltage difference between the last second of the charging segment and the first second of the static segment. If the voltage difference value increases significantly, it may be a manifestation of abnormal polarization inside the battery, and it may also be related to lithium plating. It can be understood that the lithium plating anomaly or the possibility of the existence of lithium plating anomaly can be determined by measuring and comparing any battery parameters related to the lithium plating anomaly.

[0025] Through the above-mentioned test method, the present disclosure can realize the effective detection of the lithium deposition phenomenon of the battery. Through the combination of multiple rounds of high-rate tests and conventional tests, the performance of the battery under different working conditions can be more comprehensively evaluated, and potential lithium deposition problems can be discovered in time. Specifically, through the comprehensive analysis of multiple parameters (such as the ratio of discharge capacity to charging capacity, voltage difference, voltage platform, etc.) during the battery charging and discharging process, it is possible to accurately determine whether the battery has lithium deposition. In addition, there is no need to disassemble the battery, so non-destructive testing can be achieved, avoiding the destructive operation in the traditional method, while saving detection time and cost. At the same time, the method is suitable for different types of power batteries (such as soft-pack batteries, square shell batteries, cylindrical batteries, etc.) and batteries with different positive and negative electrode materials, and has strong applicability and universality. Through the timely detection of lithium deposition anomalies, the battery life decay and safety hazards can be effectively predicted, providing a decision-making basis for the battery management system, thereby improving the safety and reliability of the battery.

[0026] In some examples, the method disclosed herein can be applied to batteries with various types of electrolytes, including but not limited to liquid electrolytes, solid-liquid mixed electrolytes, and all-solid electrolytes, to meet the detection requirements of different types of power batteries. In addition, the applicable battery cell states cover 0% SOC to 100% SOC, that is, detection can be performed from fully discharged to fully charged states, so the method disclosed herein has wide applicability.

[0027] In other examples, the method disclosed in the present invention is applicable to the battery cell test temperature range of -40°C to 60°C, and reliable lithium plating detection can still be achieved under extreme environments. However, the detection can be completed under normal temperature conditions, without the need for additional configuration of high or low temperature environments, which greatly simplifies the testing process and reduces costs. At the same time, the applicable battery cell test current range is 0A to 1000A, and the charge and discharge rate can be adjusted according to the battery cell capacity. In capacity testing, 1C constant current and small current constant voltage are usually used for charging and discharging to ensure the accuracy and comparability of the test results.

[0028] In some other examples, the battery cell test conditions applicable to the method of the present disclosure include but are not limited to international standard conditions, such as PRC 06 and US 06, to simulate various load conditions and working environments of the battery in actual use. In addition, the test cycle data of the operating conditions can cover the range of 0 to 30,000 cycles. As the number of cycles increases, the aging degree of the battery cell gradually increases, and the lithium precipitation phenomenon becomes more obvious. Through long-term testing, the trend of battery performance changes can be accurately captured, providing comprehensive diagnostic information.

[0029] In some other examples, the method disclosed in the present invention determines whether there is lithium precipitation in the battery cell by analyzing the collected parameters, including but not limited to temperature, voltage, current, capacity, power and direct current internal resistance (DCR). The analysis and calculation of these parameters involve multiple indicators, such as pressure difference, charge and discharge efficiency, voltage platform, etc. The analysis method includes but is not limited to correlation analysis, correspondence analysis, regression analysis and variance analysis, combined with statistics and mathematical models to ensure the accuracy of the test results. In addition, the method disclosed in the present invention can also perform in-depth processing on the test data, including but not limited to obtaining the change curve, calculating the average value, standard deviation, variance and obtaining the first derivative and the second derivative, and comprehensively evaluating the change characteristics of the battery parameters. Through the systematic analysis of these data, it is possible to identify the following anomalies, including but not limited to: abnormal change of pressure difference with the number of cycles, abnormal pressure drop curve of the static section, abnormal time proportion of the constant voltage section, abnormal charging voltage platform, and abnormal discharge start voltage. These anomalies can reflect the lithium precipitation or other performance problems inside the battery, and provide an important basis for battery performance optimization and safety management.

[0030] In some embodiments, the first operating condition test includes a charging section, a static section, and a discharge section, and wherein, in the first operating condition test, a first plurality of battery parameters of the power battery are measured, and the method further includes: determining the lithium deposition anomaly of the power battery according to the comparison of the measured value of the battery parameter in the first plurality of battery parameters with the predetermined threshold value of the battery parameter. In the first operating condition test, the battery is tested at a high rate of charge and discharge, the purpose of which is to simulate the performance of the battery under extreme working conditions. Specifically, the charge and discharge rate used in the first operating condition test is usually greater than the rate of the second operating condition test (for example, a higher rate such as 5C, 10C is used). Through rapid charging and discharging, the battery will experience a large temperature rise in a short time and induce changes in the internal electrochemical reaction. During the test process, it includes a charging section, a static section, and a discharge section: in the charging section, the battery is charged by a large current and its temperature change is monitored to ensure that the battery does not overheat under high load; in the static section, the battery is static after charging to observe the changes in the voltage and internal resistance of the battery and evaluate whether polarization occurs; in the discharge section, the battery is discharged at a higher rate, and the battery discharge capacity, voltage fluctuation and other data are recorded. By comparing these parameters with predetermined thresholds, such as the ratio of discharge capacity to charge capacity, voltage difference, etc., it is possible to determine whether lithium plating or other abnormal phenomena occur in the battery. In this way, the safety, performance and potential problems of the battery under high load can be more effectively evaluated.

[0031] In some embodiments, the number of rounds of the first working condition test is greater than 100 rounds, the charge and discharge rate is greater than 5C, and the charge and discharge rate of the second working condition test is 1C. In this way, the battery can be rigorously tested through multiple rounds of high-rate charge and discharge to accelerate the aging process of the battery, especially under high load conditions, to simulate the performance of the battery in an extreme working environment. Each round of high-rate charge and discharge operation will quickly cause the heat of the battery to increase, promote the electrochemical reaction inside the battery, and thus quickly reveal potential problems of the battery under high load, such as excessive temperature, capacity decay or lithium precipitation. By performing more than 100 rounds (for example, 1000 rounds) of high-rate tests, the performance data of the battery under multiple rounds of extreme working conditions can be fully accumulated to provide data support for the subsequent judgment of lithium precipitation anomalies. In the second working condition test, the charge and discharge rate is set to 1C, which is a relatively standard and conventional charge and discharge rate, which is often used for battery evaluation under normal working conditions. The second working condition test usually includes a charging section, a static section, and a discharge section, with the purpose of performing performance testing under relatively mild load conditions. By using a 1C charge and discharge rate, it is possible to simulate the working state of the battery in actual applications, such as daily use in electric vehicles or power tools. Unlike the high rate of the first operating condition test, the second operating condition test can provide a more accurate assessment of the stability, efficiency, and whether lithium plating occurs under normal conditions of use. In this way, the high rate and large number of rounds of the first operating condition test can ensure the performance of the battery under extreme conditions, while the second operating condition test provides a comprehensive assessment of the battery under normal conditions of use. The combination of the two can more accurately judge the health of the battery and whether there are safety hazards such as lithium plating.

[0032] In some embodiments, the second plurality of battery parameters includes a ratio of discharge capacity to charge capacity, and step S3 further includes: if the ratio of discharge capacity to charge capacity is less than a predetermined ratio of discharge capacity to charge capacity, then determining that the power battery is abnormally lithium-precipitated. This ratio reflects the relationship between the energy actually stored and released by the battery during the charge and discharge process and its theoretical maximum capacity. Specifically, the charge and discharge capacity ratio (D / C efficiency) of the battery is an important health indicator that can help assess whether the battery has performance degradation during the charge and discharge process, especially when lithium precipitation occurs. The lithium precipitation phenomenon can cause the charge and discharge efficiency of the battery to be significantly reduced, thereby showing that the ratio of discharge capacity to charge capacity is lower than a predetermined standard value. Generally, if this ratio is significantly lower than 1 (for example, lower than 0.9), this may indicate that lithium precipitation has occurred inside the battery, that is, lithium metal is precipitated on the surface of the negative electrode of the battery, and cannot effectively participate in the charge and discharge reaction of the battery, resulting in capacity loss. The lithium precipitation phenomenon not only causes the effective capacity of the battery to decrease, but also may increase the internal resistance of the battery, affect its energy output efficiency, and increase the safety hazards of the battery, such as thermal runaway or fire. Therefore, by detecting the ratio of discharge capacity to charge capacity, it is possible to effectively identify whether lithium plating occurs in the battery and provide early warning to avoid battery failure or safety problems. This method is simple and easy to use. It does not require disassembling the battery and can be performed through conventional charge and discharge tests. Therefore, it has the advantages of being efficient and non-destructive. Through this technology, effective detection can be performed before lithium plating occurs in the battery, thereby improving the safety and reliability of the battery.

[0033] In some embodiments, the second plurality of battery parameters include voltage differential values, and step S3 further includes: if the voltage differential value between the last second of the charging segment and the first second of the static segment is greater than a predetermined voltage differential value, then the lithium deposition of the power battery is determined to be abnormal. This parameter is used to detect the polarization of the battery, and then determine whether lithium deposition occurs. In step S3, the polarization state of the battery can be determined by measuring the voltage differential value between the last second of the charging segment and the first second of the static segment. Under normal circumstances, the voltage change of the battery at the end of charging and the beginning of static should be relatively stable, and the differential value should be within a small range. For example, in a healthy battery, the voltage differential may be stable at around 10mV. However, when lithium deposition occurs in the battery, the electrochemical interface of the battery is unstable, resulting in a significant increase in the voltage differential value, which is usually due to the deposition of lithium metal on the surface of the negative electrode, resulting in uneven distribution of current inside the battery. If the measured differential value exceeds a predetermined threshold (for example, more than 12mV or higher), it can be determined that lithium deposition may occur in the battery. Through this detection step, potential performance degradation or safety hazards can be discovered in time before lithium deposition occurs in the battery. In this way, it is possible to efficiently and non-destructively determine whether the battery has a lithium plating problem without relying on disassembly of the battery, thereby improving the safety and reliability of the battery during use.

[0034] In some embodiments, the second plurality of battery parameters include voltage differential values, and step S3 further includes: if the voltage differential value between the last second of the charging segment and the first second of the static segment deviates from the predetermined voltage differential value by a first deviation threshold value in the second operating condition test of the predetermined number of rounds, then the lithium deposition abnormality of the power battery is determined. This parameter is also used to analyze whether there is polarization phenomenon in the battery during charging and static process, so as to help determine whether the battery has lithium deposition abnormality. In step S3, the voltage differential value between the last second of the charging segment and the first second of the static segment is further calculated and compared with the predetermined voltage differential value. If in the second operating condition test of the predetermined number of rounds (for example, 3 rounds), the voltage differential value deviates from the predetermined voltage differential value in each round of the test and exceeds the first deviation threshold value, it can be determined that the battery has lithium deposition. Under normal circumstances, the voltage change of the battery at the end of charging and the beginning of static should be relatively stable, and the voltage differential value is usually maintained within a fixed range (for example, 10mV). However, when lithium deposition occurs inside the battery, lithium metal may be deposited on the surface of the negative electrode, resulting in an unstable electrochemical interface of the battery and uneven current distribution, which causes a significant deviation in the voltage differential value (for example, a deviation of 10mV and exceeding the first deviation threshold of 1mV, that is, less than 9mV or greater than 11mV). If this deviation persists and exceeds the set threshold, it indicates that lithium deposition may occur in the battery, affecting its performance and safety. Through this method, early detection of abnormal lithium deposition in the battery can be achieved, effectively improving the safety of the battery during use, while avoiding performance degradation caused by lithium deposition.

[0035] In some embodiments, the second plurality of battery parameters include voltage platform values, and step S3 further includes: if the voltage platform value deviates from the predetermined voltage platform value by a second deviation threshold value in one or more rounds of the second operating condition test, the lithium deposition of the power battery is determined to be abnormal. This parameter can be used, for example, to evaluate the stability of the battery during the charging and discharging process and the health of the battery material. The voltage platform refers to the area where the voltage of the battery is stable during the charging or discharging process, which is usually determined by the chemical materials and electrochemical interface of the battery. In step S3, the voltage platform value is further analyzed and compared with the predetermined voltage platform value. If the voltage platform value deviates from the predetermined voltage platform value in one or more rounds of the second operating condition test, and this deviation exceeds the set second deviation threshold, it can be determined that the battery has lithium deposition. Under normal circumstances, the voltage platform of the battery should be stable at a fixed voltage value (e.g., 3.75V), but when lithium deposition occurs inside the battery, the electrochemical interface of the battery may change, resulting in a significant fluctuation or decrease in the voltage platform of the battery (e.g., deviating from 3.75V and exceeding the second deviation threshold of 0.3V, i.e., less than 3.45mV or greater than 4.05mV). Abnormal battery materials will affect the stability of the voltage platform, thereby affecting the battery's charge and discharge efficiency and performance. By monitoring the changes in the voltage platform value, lithium plating can be detected in time, and potential battery failures can be warned in advance. In this way, the safety of the battery can be effectively improved, and the battery performance degradation and safety risks caused by lithium plating can be avoided.

[0036] In some examples, the power batteries involved in the present disclosure are in various forms, including but not limited to soft-pack batteries, square-shell batteries and cylindrical batteries. Soft-pack batteries are widely used in electric vehicles and portable electronic devices due to their lightweight design and flexible shape adaptability; square-shell batteries have high energy density and good mechanical stability, and are suitable for large energy storage systems and electric vehicles; cylindrical batteries are common in power tools and small electric vehicles due to their standardized size and mature production process. The selection of battery positive electrode materials is also very rich, including but not limited to nickel cobalt manganese oxide (ternary) positive electrode materials, which have high energy density and good cycle performance; nickel cobalt aluminum oxide (ternary) positive electrode materials, which are suitable for high power output occasions; lithium manganese oxide positive electrode materials, which have low cost and good safety; lithium cobalt oxide positive electrode materials, which are mainly used in consumer electronics products and have high energy density; lithium iron phosphate positive electrode materials, which have excellent safety and long life characteristics; in addition, modified materials doped with transition metal elements can also be used to further optimize electrochemical performance. Battery negative electrode materials are also diverse, including but not limited to graphite negative electrode materials, which have good stability and low cost; silicon oxide negative electrode materials, which provide higher specific capacity; silicon-carbon composite negative electrode materials, which combine the high capacity of silicon and the stable performance of carbon; lithium titanate negative electrode materials, which have excellent cycle stability and fast charge and discharge capabilities; lithium metal negative electrode materials, which have extremely high energy density; nano-negative electrode materials, which use nanotechnology to increase the surface area and reaction activity of materials, thereby improving the overall performance of the battery. The disclosed solution can effectively identify and detect various defects inside the battery cell, such as poor welding, pole piece tearing, diaphragm folding and lithium precipitation, for different battery forms and material combinations, thereby ensuring the stability and safety of the battery and improving the reliability and service life of the overall system.

[0037] In other embodiments, the power battery lithium deposition anomaly detection method improves the accuracy and sensitivity of detection by setting different weights for different battery parameters. That is, the method may further include: each battery parameter of a plurality of battery parameters has a different weight, and the score of the power battery for lithium deposition anomaly detection is determined according to the difference between each battery parameter and the corresponding predetermined threshold value of the battery parameter and the weight of each battery parameter, and the score is compared with the predetermined score, and the predetermined score can be a comprehensive score determined according to the empirical value. Specifically, when setting the multi-parameter weight model, the key battery parameters related to lithium deposition are first selected, such as the voltage platform value, the voltage differential value, and the ratio of the discharge capacity to the charging capacity. By combining historical data and experimental results, the correlation between each parameter and the lithium deposition phenomenon is calculated, and a weight is assigned to each parameter according to the correlation coefficient or the feature importance score. For example, for the voltage platform value, the weight can be set to 0.4, the weight can be set to 0.35 for the voltage differential value, and the weight can be set to 0.25 for the ratio of the discharge capacity to the charging capacity. In actual testing, multi-parameter data of each round of cycle testing is collected, and the deviation value (degree of difference, such as the percentage above or below the predetermined threshold) of each parameter is multiplied by the corresponding weight to finally obtain a comprehensive abnormality score. This score can be compared with a preset threshold (for example, when the score is greater than 0.7, it is judged to be abnormal) to determine whether there is lithium precipitation. For example, assuming that the voltage platform value deviation of a certain test is 0.15, the voltage difference deviation is 0.1, and the ratio deviation of the discharge capacity to the charging capacity is 0.05, the comprehensive score is 0.4×0.15+0.35×0.1+0.25×0.05=0.0975. If the score is lower than the set threshold (for example, 0.1), it is determined that the battery has no lithium precipitation abnormality. This method can take into account a variety of battery parameters, improve the adaptability to different types of batteries and test conditions, accurately identify the lithium precipitation phenomenon, and enhance the sensitivity and reliability of detection.

[0038] According to another aspect of the present disclosure, a power battery lithium deposition abnormality detection device is provided, which includes a memory and a processor, the memory stores instructions, and when the instructions are executed by the processor, any one of the battery defect detection methods 100 based on the charging process as described above is implemented.

[0039] According to another aspect of the present disclosure, a computer-readable storage medium is provided, in which instructions are stored. When the instructions are executed by a processor, the processor executes any one of the power battery lithium deposition abnormality detection methods 100 described above. The computer-readable medium referred to in the present disclosure includes various types of computer storage media, which can be any available medium that can be accessed by a general-purpose or special-purpose computer. For example, the computer-readable medium can include RAM, ROM, EPROM, EEPROM, etc. 2PROM, register, hard disk, removable disk, CD-ROM or other optical disk storage, disk storage or other magnetic storage device, or can be used to carry or store the desired program code unit with instruction or data structure form and can be accessed by general or special computer, or any other temporary or non-temporary medium of general or special processor. As used herein, the disk usually copies data magnetically, while the dish uses laser to optically copy data. The above combination should also be included in the protection scope of computer-readable medium. Exemplary storage medium is coupled to the processor so that the processor can read and write information from / to the storage medium. In an alternative solution, the storage medium can be integrated into the processor. The processor and the storage medium can reside in the ASIC. The ASIC can reside in the user terminal. In an alternative solution, the processor and the storage medium can reside in the user terminal (e.g., test, diagnosis, detection equipment) as discrete components.

[0040] The above are only specific embodiments of the present disclosure, but the protection scope of the present disclosure is not limited thereto. Those skilled in the art can think of other feasible changes or substitutions based on the technical scope disclosed in the present disclosure, and such changes or substitutions are all included in the protection scope of the present disclosure. In the absence of conflict, the embodiments of the present disclosure and the features in the embodiments can also be combined with each other. The protection scope of the present disclosure shall be based on the records of the claims.

Claims

1. A method for detecting abnormal lithium deposition in a power battery, characterized in that: The method comprises the following steps: S1: performing multiple rounds of first operating condition tests on the power battery; S2: after completing the multiple rounds of the first operating condition tests, performing one or more rounds of second operating condition tests on the power battery, wherein the second operating condition test includes a charging section, a rest section, and a discharging section, and wherein, in the second operating condition test, a second plurality of battery parameters of the power battery are measured; and S3: determining that the power battery has lithium deposition abnormality according to a comparison between a measured value of a battery parameter in the second plurality of battery parameters and a predetermined threshold value of the battery parameter, Among them, the charge and discharge rate of the first operating condition test is greater than the charge and discharge rate of the second operating condition test.

2. The method according to claim 1, characterized in that The first operating condition test includes a charging section, a static section, and a discharging section, and wherein, in the first operating condition test, a first plurality of battery parameters of the power battery are measured, and the method further includes: determining the lithium plating abnormality of the power battery based on comparison of the measured value of a battery parameter among the first plurality of battery parameters with a predetermined threshold value of the battery parameter.

3. The method according to claim 1, characterized in that The number of rounds of the multiple rounds of the first operating condition test is greater than 100 rounds, the charge and discharge rate is greater than 5C, and the charge and discharge rate of the second operating condition test is 1C.

4. The method according to claim 1, characterized in that The second plurality of battery parameters include a ratio of discharge capacity to charge capacity, and the step S3 further includes: if the ratio of discharge capacity to charge capacity is less than a predetermined ratio of discharge capacity to charge capacity, determining that lithium deposition of the power battery is abnormal.

5. The method according to claim 1, characterized in that The second plurality of battery parameters include voltage differential values, and the step S3 further includes: if the voltage differential value between the last second of the charging segment and the first second of the static segment is greater than a predetermined voltage differential value, determining that the power battery has lithium deposition abnormality.

6. The method according to claim 1, characterized in that The second plurality of battery parameters include voltage differential values, and step S3 further includes: if the voltage differential value between the last second of the charging segment and the first second of the start of the static segment deviates from the predetermined voltage differential value by a first deviation threshold in a predetermined number of second operating condition tests, then determining that the power battery has lithium plating abnormality.

7. The method according to claim 1, characterized in that The second plurality of battery parameters include a voltage platform value, and the step S3 further includes: if the voltage platform value deviates from a predetermined voltage platform value by a second deviation threshold value in the one or more rounds of the second operating condition test, determining that the power battery has lithium plating abnormality.

8. The method according to claim 1, characterized in that The form of the battery includes one or more of the following: soft-pack battery, square shell battery, cylindrical battery, the positive electrode material of the battery includes one or more of the following: nickel cobalt manganese oxide positive electrode material, nickel cobalt aluminum oxide lithium positive electrode material, lithium manganese oxide positive electrode material, lithium cobalt oxide positive electrode material, lithium iron phosphate positive electrode material, the negative electrode material of the battery includes one or more of the following: graphite negative electrode material, silicon oxide negative electrode material, silicon-carbon composite negative electrode material, lithium titanate negative electrode material, lithium metal negative electrode material, nano negative electrode material.

9. A power battery lithium deposition abnormality detection device, characterized in that: The power battery lithium deposition abnormality detection device includes a memory and a processor, the memory stores instructions, and when the instructions are executed by the processor, the method according to any one of claims 1-8 is implemented.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores instructions, which, when executed by a processor, implement the method according to any one of claims 1-8.

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