Battery cell anomaly detection method, system, device and equipment

Abstract

The invention discloses a cell anomaly detection method, system, device and equipment, and the method comprises the steps: determining the positive voltage and negative voltage of a plurality of three-electrode cells in a battery pack through voltage monitoring; respectively determining positive electrode impedance data and negative electrode impedance data according to the positive electrode voltage and the negative electrode voltage of the three-electrode cell; and according to the anode impedance data and the cathode impedance data, carrying out anomaly detection on the anode and cathode impedance states of each three-electrode cell. According to the technical scheme provided by the invention, the positive and negative electrode impedance of the battery cell is accurately determined by monitoring the positive and negative electrode voltage of the three-electrode battery cell. Based on accurate analysis of positive and negative electrode impedance, leading reasons causing cell impedance increase are analyzed, and more accurate anomaly detection is carried out on the three-electrode cell. According to the technical scheme provided by the invention, the impedance increase and the abnormal source of the three-electrode battery cell can be accurately positioned, the potential risk can be accurately predicted, the use safety and stability of the three-electrode battery cell are remarkably improved, and the service life is prolonged.

Description

TECHNICAL FIELD

[0001] The present application relates to the field of battery, in particular to a battery cell abnormality detection method, system, device and equipment. BACKGROUND

[0002] In the field of battery today, battery impedance and impedance change are the core indicators of battery performance degradation and safety risk, and play a key role in the entire battery life cycle.

[0003] With the increase of use time and cycle number, the impedance of each battery cell inside the battery will gradually increase, resulting in a decrease in the power output capability of the overall battery and a decrease in the maximum available capacity, which seriously affects the performance and reliability of the battery. Through accurate detection and analysis of the impedance of each battery cell, early warning of abnormal battery cells can be achieved, and dynamic adjustment of charging and discharging strategies can be performed at the same time, improving the safety and prolonging the life of the battery.

[0004] The existing impedance detection method mostly measures the impedance of the whole battery cell, and the obtained impedance data can only reflect the comprehensive impedance state of the battery cell. This method can only make rough abnormality judgment and other processing analysis based on the overall impedance data. The charging and discharging power adjustment strategy made on this basis may not guarantee the effectiveness and applicability of the charging and discharging control processing based on the strategy due to not meeting the real internal state of the battery cell.

[0005] Therefore, how to realize more accurate abnormality detection for battery cells is an important problem to be solved at present. SUMMARY

[0006] The present application provides a battery cell abnormality detection method, system, device and equipment, which can accurately detect the abnormality of the battery cell.

[0007] In a first aspect, the present application provides a battery cell abnormality detection method, which comprises: monitoring the voltage of at least one three-electrode battery cell in the battery pack of an electric vehicle under different working conditions to determine the positive voltage and negative voltage of the at least one three-electrode battery cell; determining the positive impedance data of the at least one three-electrode battery cell according to the positive voltage, and determining the negative impedance data of the at least one three-electrode battery cell according to the negative voltage; performing abnormality detection on the positive and negative impedance states of the at least one three-electrode battery cell according to the positive and negative impedance data, the positive impedance outlier threshold and the negative impedance outlier threshold, wherein the positive impedance outlier threshold is determined according to the positive impedance data of all three-electrode battery cells in the battery pack, and the negative impedance outlier threshold is determined according to the negative impedance data of all three-electrode battery cells in the battery pack.

[0008] In the embodiment, the positive and negative electrode impedances of the battery cell can be accurately determined by monitoring the positive and negative electrode voltages of the three-electrode battery cell. Based on the positive and negative electrode impedances, the dominant cause of the impedance increase of the battery cell can be accurately analyzed, and more accurate abnormal detection can be performed on the three-electrode battery cell. Through the embodiment, the impedance increase and abnormal source of the three-electrode battery cell can be accurately located, the potential risks can be accurately predicted, the use safety and stability of the three-electrode battery cell can be significantly improved, and the service life can be prolonged.

[0009] In some embodiments, the voltage of at least one three-electrode battery cell in a battery pack carried by an electric vehicle under different working conditions is monitored to determine the positive and negative electrode voltages of the at least one three-electrode battery cell, including: Performing electrochemical impedance detection on the at least one three-electrode battery cell; Taking the positive electrode response voltage of the at least one three-electrode battery cell in the electrochemical impedance detection as the positive electrode voltage, and taking the negative electrode response voltage of the at least one three-electrode battery cell in the electrochemical impedance detection as the negative electrode voltage.

[0010] In the embodiment, the positive and negative electrode voltages and the positive and negative electrode impedances of the three-electrode battery cell can be determined by electrochemical impedance detection. Through the embodiment, the positive and negative electrode response voltages for subsequent determination of the impedance of the battery cell can be obtained, and practical data basis for subsequent processing can be provided. Based on the positive and negative electrode voltages, the overall impedance of the three-electrode battery cell can be effectively separated, and sufficient support can be provided for further refining the cause of the impedance increase of the three-electrode battery cell and abnormal detection.

[0011] In some embodiments, the positive electrode impedance data of the at least one three-electrode battery cell is determined according to the positive electrode voltage, and the negative electrode impedance data of the at least one three-electrode battery cell is determined according to the negative electrode voltage, including: The positive electrode impedance data of the at least one three-electrode battery cell is determined according to the positive electrode voltage and the excitation current of the electrochemical impedance detection, and the negative electrode impedance data of the at least one three-electrode battery cell is determined according to the negative electrode voltage and the excitation current. The impedance data includes at least one of charge transfer resistance, ohmic resistance, and solid electrolyte interface film resistance.

[0012] In the embodiment, the positive and negative electrode resistance data corresponding to the positive and negative electrodes can be accurately determined based on the positive and negative electrode response voltages of the three-electrode battery cell in the electrochemical impedance detection process. Through the embodiment, the positive and negative electrode impedance data can be efficiently and accurately determined, and real and effective data basis can be provided for subsequent abnormal detection process, which significantly improves the abnormal detection accuracy and efficiency of the three-electrode battery cell.

[0013] In some embodiments, the voltage of at least one three-electrode battery cell in a battery pack carried by an electric vehicle under different working conditions is monitored to determine the positive and negative electrode voltages of the at least one three-electrode battery cell, including: For at least one three-electrode cell under pulsed operating conditions, the potential of the positive electrode relative to the reference electrode is determined as the positive electrode voltage, and the potential of the negative electrode relative to the reference electrode is determined as the negative electrode voltage.

[0014] In this embodiment, the positive and negative voltages of a three-electrode battery cell under pulsed operating conditions can be determined. The determined voltage data can be used to determine the positive and negative impedance data, providing a solid data foundation. This embodiment enables real-time and efficient voltage monitoring, improving the accuracy and efficiency of anomaly detection in three-electrode batteries, enhancing battery cell safety, and extending battery cell lifespan.

[0015] In some embodiments, determining the positive impedance data of at least one three-electrode cell based on the positive electrode voltage, and determining the negative impedance data of at least one three-electrode cell based on the negative electrode voltage, includes: Based on the positive electrode voltage and pulse current, determine the positive electrode impedance data of at least one three-electrode cell, and based on the negative electrode voltage and pulse current, determine the negative electrode impedance data of at least one three-electrode cell.

[0016] In this embodiment, the positive and negative electrode impedance data of a three-electrode cell can be accurately and efficiently determined based on the pulse current under pulsed operating conditions and the monitored positive and negative electrode potentials. This embodiment enables precise separation and determination of the positive and negative electrode impedance data, providing an effective data foundation for subsequent anomaly detection processes, significantly improving anomaly detection accuracy, and offering strong timeliness, thus significantly improving the anomaly detection efficiency for three-electrode cells.

[0017] In some embodiments, anomaly detection is performed on the positive and negative impedance states of at least one three-electrode cell based on positive impedance data and negative impedance data, positive impedance outlier thresholds and negative impedance outlier thresholds, including: Based on the positive impedance outlier threshold and positive impedance data, positive impedance consistency detection is performed on at least one three-electrode cell to identify cells with abnormal positive impedance. Similarly, based on the negative impedance outlier threshold and negative impedance data, negative impedance consistency detection is performed on at least one three-electrode cell to identify cells with abnormal negative impedance.

[0018] In this embodiment, outlier thresholds can be dynamically set based on the positive and negative impedance data of the three-electrode cell, enabling adaptive threshold judgment and dynamic anomaly detection. This embodiment allows for precise detection of inconsistencies in the three-electrode cell based on positive and negative impedance data, significantly improving anomaly detection accuracy and detail compared to overall cell impedance, thus providing effective assistance for early warning and prevention of anomaly risks.

[0019] In some embodiments, determining a positive impedance outlier threshold based on the positive impedance data of all three-electrode cells in the battery pack, and determining a negative impedance outlier threshold based on the negative impedance data of all three-electrode cells in the battery pack, includes: Determine the mean and standard deviation of the positive impedance data, and determine the mean and standard deviation of the negative impedance data; The outlier threshold for positive impedance is determined based on the mean and standard deviation of positive impedance, and the outlier threshold for negative impedance is determined based on the mean and standard deviation of negative impedance.

[0020] In this embodiment, the impedance outlier threshold can be dynamically set based on the mean and standard deviation of the impedance data. Determining the dynamic threshold can effectively improve the adaptability of the overall cell anomaly detection method and expand its application scope. Anomaly judgment based on the outlier threshold can accurately analyze consistency anomalies among three-electrode cells, significantly improving anomaly detection accuracy, enabling early warning and repair of potential risks, and enhancing the safety of cell use.

[0021] In some embodiments, determining a positive impedance outlier threshold based on the positive impedance data of all three-electrode cells in the battery pack, and determining a negative impedance outlier threshold based on the negative impedance data of all three-electrode cells in the battery pack, includes: Determine the positive midpoint impedance data for the positive impedance data, and determine the negative midpoint impedance data for the negative impedance data; Based on the positive electrode median impedance data, the positive electrode impedance outlier threshold is determined, and based on the negative electrode median impedance data, the negative electrode impedance outlier threshold is determined.

[0022] In this embodiment, the outlier threshold can be dynamically set based on the median of multiple impedance data, effectively suppressing the impact of extreme outliers in the impedance data. This embodiment enables adaptive setting of the outlier threshold, providing an effective basis for subsequent anomaly detection in three-electrode cells, significantly improving anomaly detection accuracy and efficiency.

[0023] In some embodiments, voltage monitoring is performed on at least one three-electrode cell within the battery pack of an electric vehicle under different operating conditions to determine the positive and negative electrode voltages of at least one three-electrode cell, including: Multiple voltage monitoring sessions are performed on at least one three-electrode cell to determine multiple positive and multiple negative electrode voltages of the at least one three-electrode cell under multiple voltage monitoring sessions.

[0024] In this embodiment, voltage monitoring can be performed multiple times for each three-electrode cell, increasing the data volume and providing sufficient data support for subsequent anomaly detection processes targeting impedance growth rates. The significant increase in data volume enhances the accuracy and reliability of the overall anomaly detection process, further improving the safety of using the three-electrode cells.

[0025] In some embodiments, anomaly detection of the positive and negative impedance states of at least one three-electrode cell is performed based on positive and negative impedance data, including: Based on multiple positive impedance data of at least one three-electrode cell under multiple voltage monitoring, determine the positive impedance growth rate of at least one three-electrode cell, and based on multiple negative impedance data of at least one three-electrode cell under multiple voltage monitoring, determine the negative impedance growth rate of at least one three-electrode cell. Based on the positive impedance growth rate and a preset impedance growth rate threshold, at least one three-electrode cell is subjected to positive impedance growth rate anomaly detection to identify cells with abnormal positive impedance growth. Similarly, based on the negative impedance growth rate and a preset impedance growth rate threshold, at least one three-electrode cell is subjected to negative impedance growth rate anomaly detection to identify cells with abnormal negative impedance growth.

[0026] In this embodiment, the rate of increase in the positive and negative electrode impedance of the three electrodes can be accurately determined and anomalies detected based on the positive and negative electrode impedance data obtained from multiple voltage monitoring. Accurately identifying the dominant causes of impedance increase in the three-electrode cell significantly improves the processing accuracy and efficiency of impedance analysis and anomaly detection, providing a practical reference basis for subsequent adjustments to charging and discharging strategies and other operational processes.

[0027] In some embodiments, the method further includes: Based on multiple positive and negative impedance data of at least one three-electrode cell under multiple voltage monitoring, as well as the positive and negative impedance growth rates, the adjustment parameters for the charging and discharging power of the battery pack are determined.

[0028] In this embodiment, the charging and discharging power during actual use of the three-electrode battery cell can be dynamically adjusted based on the impedance data of the positive and negative electrodes and the impedance growth rate. Appropriately matched charging and discharging power can effectively improve the safety of the battery cell and extend its lifespan.

[0029] Secondly, embodiments of this application provide a battery management system, the system comprising: The sampling circuit is used to monitor the voltage of at least one three-electrode cell in the battery pack of an electric vehicle under different operating conditions, and to determine the positive and negative voltages of at least one three-electrode cell. The controller is configured to determine the positive impedance data of at least one three-electrode cell based on the positive electrode voltage, and to determine the negative impedance data of at least one three-electrode cell based on the negative electrode voltage; and to perform anomaly detection on the positive and negative impedance states of at least one three-electrode cell based on the positive and negative impedance data, the positive impedance outlier threshold, and the negative impedance outlier threshold, wherein the positive impedance outlier threshold is determined based on the positive impedance data of all three-electrode cells in the battery pack, and the negative impedance outlier threshold is determined based on the negative impedance data of all three-electrode cells in the battery pack.

[0030] Fourthly, embodiments of this application provide a battery device, including a battery and a battery management system as described in the third aspect.

[0031] Fifthly, embodiments of this application provide an electrical device, including the battery device as described in the fourth aspect.

[0032] In a sixth aspect, this application provides a computer storage medium storing computer program instructions, which, when executed by a processor, implement the cell anomaly detection method shown in any embodiment of the first aspect.

[0033] In a seventh aspect, embodiments of this application provide a computer program product, wherein instructions in the computer program product, when executed by a processor of an electronic device, cause the electronic device to perform the cell anomaly detection method shown in any embodiment of the first aspect.

[0034] The above description is only an overview of the technical solution of this application. In order to better understand the technical means of this application and to implement it in accordance with the contents of the specification, and to make the above and other objects, features and advantages of this application more obvious and understandable, the following are specific embodiments of this application. Attached Figure Description

[0035] The features, advantages, and technical effects of exemplary embodiments of this application will now be described with reference to the accompanying drawings.

[0036] Figure 1 This is one of the flowcharts illustrating a cell anomaly detection method provided in some embodiments of this application; Figure 2 A second schematic flowchart illustrating a cell anomaly detection method provided in some embodiments of this application; Figure 3 The third schematic flowchart illustrates a cell anomaly detection method provided in some embodiments of this application; Figure 4 The fourth schematic flowchart of a cell anomaly detection method provided in some embodiments of this application; Figure 5Fifth of a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application; Figure 6 A schematic flowchart of a cell anomaly detection method provided in some embodiments of this application is shown in Figure 6. Figure 7 This is the seventh flowchart illustrating a cell anomaly detection method provided in some embodiments of this application; Figure 8 This is the eighth flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 9 A flowchart of a cell anomaly detection method provided in some embodiments of this application is shown in Figure 9. Figure 10 The tenth schematic flowchart of a cell anomaly detection method provided in some embodiments of this application; Figure 11 Eleventh of a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application; Figure 12 The twelfth is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application; Figure 13 This application provides a schematic diagram of the structure of a battery management system according to some embodiments; Figure 14 This is a schematic diagram of the structure of an electronic device provided in some embodiments of this application.

[0037] The accompanying drawings are not necessarily drawn to scale. Detailed Implementation

[0038] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0039] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0040] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0041] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment mutually exclusive with other embodiments. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0042] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, or B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following associated objects have an "or" relationship. The term "multiple" refers to two or more (including two).

[0043] In the field of battery technology, impedance and its changes are key indicators reflecting battery performance degradation and safety risks, spanning the entire battery lifecycle. As the number of cycles increases and usage time accumulates, the impedance of each cell within the battery pack gradually increases, leading to a decrease in overall battery power output and maximum capacity, severely impacting overall battery performance and reliability.

[0044] Therefore, by accurately monitoring and analyzing the cell impedance, it is possible to precisely identify anomalies causing abnormal increases in cell impedance. Simultaneously, charging and discharging strategies can be dynamically adjusted, thereby improving battery safety and lifespan. Currently, common impedance detection methods primarily monitor the overall impedance of the cell. The impedance data obtained only provides a relatively macroscopic view of the cell's impedance state and cannot identify the true cause of impedance changes, such as whether the impedance increase is dominated by the positive or negative electrode.

[0045] Therefore, anomaly judgments and analyses based on the cell's complete impedance are often rather crude, which can lead to discrepancies between the test results and the actual causes of cell aging. Furthermore, charge / discharge control strategies developed based on this may fail to adequately address the actual impedance anomalies of the cells, making it difficult to guarantee their effectiveness and applicability, thus affecting battery safety.

[0046] To address the aforementioned technical problems, this application provides a method, system, apparatus, and device for detecting abnormalities in battery cells. The method includes: first, determining the positive and negative electrode voltages of multiple three-electrode cells within a battery pack through voltage monitoring; then, determining positive and negative electrode impedance data based on the positive and negative electrode voltages of the three-electrode cells; and finally, detecting abnormalities in the positive and negative electrode impedance states of each three-electrode cell based on the positive and negative electrode impedance data.

[0047] The technical solution provided in this application can accurately determine the positive and negative impedances of a three-electrode battery cell by monitoring the positive and negative electrode voltages. Based on the positive and negative electrode impedances, the dominant causes of impedance increase in the battery cell can be accurately analyzed, and more precise anomaly detection can be performed on the three-electrode battery cell. The technical solution provided in this application can accurately locate the impedance increase and anomaly sources of a three-electrode battery cell, accurately predict potential risks, significantly improve the safety and stability of the three-electrode battery cell, and extend its service life.

[0048] The execution entity used in the technical solutions provided in this application can be a battery management system (BMS) capable of monitoring the voltage of the three-electrode cells in the battery pack, or a terminal device capable of controlling the battery management system, such as a desktop computer or laptop computer, or a remote device, such as a server.

[0049] In addition, the execution entity used in the embodiments of this application can also be a software execution entity, such as a client or software program installed in a battery management system, terminal device, or server. The specific type of execution entity corresponding to the battery cell anomaly detection method, system, device, and equipment provided in the embodiments of this application is not strictly limited here; it can be flexibly selected and set according to the application scenario and actual needs.

[0050] It should be noted that the specific application scenarios corresponding to the battery cell anomaly detection methods, systems, devices and equipment provided in the embodiments of this application are not strictly limited. The battery cell anomaly detection methods, systems, devices and equipment provided in the embodiments of this application can be flexibly applied to various application scenarios that require three-electrode battery cell anomaly detection according to actual needs.

[0051] For example, in a scenario where periodic anomaly detection is performed on each of the three-electrode cells in an electric vehicle's onboard battery, the technical solution provided in this application can accurately determine the corresponding positive and negative impedance data by detecting the positive and negative voltages of each three-electrode cell under different operating conditions.

[0052] Then, based on the positive and negative impedance data, anomaly detection can be performed on the positive and negative impedance states of each three-electrode cell in the vehicle battery. This includes, but is not limited to, detection of the consistency of positive and negative impedance and detection of abnormal rates of increase in positive and negative impedance. The technical solution provided in this application can accurately determine the precise cause of the impedance increase in the three-electrode cell, significantly improving the precision of anomaly detection for the three-electrode cell, enabling early prediction of potential risks, and improving the safety of the cell and the vehicle battery.

[0053] It should be noted that the application scenarios described in the above embodiments of this application are for the purpose of more clearly illustrating the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions provided by the embodiments of this application. Those skilled in the art will understand that with the emergence of new application scenarios, the technical solutions provided by the embodiments of this application are also applicable to similar technical problems. The cell anomaly detection method, system, device, and equipment provided by the embodiments of this application can be applied to various application scenarios requiring three-electrode cell anomaly detection.

[0054] Figure 1 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 1 The diagram includes steps S110 and S130.

[0055] S110: Monitor the voltage of at least one three-electrode cell in the battery pack of an electric vehicle under different operating conditions, and determine the positive and negative voltages of at least one three-electrode cell.

[0056] In step S110, the cell anomaly detection method provided in this application embodiment can perform voltage monitoring on each three-electrode cell in the battery pack at least once, and monitor the positive and negative electrode voltages of each three-electrode cell.

[0057] Among them, the three-electrode cell is a special type of battery. Compared with the ordinary two-electrode cell, which only has a positive electrode and a negative electrode, the three-electrode cell has an additional reference electrode in addition to the positive and negative electrodes. This reference electrode can be used to measure the potential or voltage of the positive and negative electrodes.

[0058] The aforementioned methods for monitoring positive and negative electrode voltages can be flexibly selected based on actual needs and application scenarios. In some embodiments, electrochemical impedance spectroscopy (EIS) can be performed on each three-electrode cell in a battery pack that is in a static state and meets the testing environmental conditions. The positive and negative electrode response voltages during the testing process can be used as the positive and negative electrode voltages of the three-electrode cell, respectively. Based on the positive and negative electrode voltages, further positive and negative electrode impedance data can be determined, providing data support for subsequent anomaly detection processes.

[0059] In other embodiments, voltage detection can be performed on the three-electrode cell under pulsed operating conditions, and the potentials of the positive and negative electrodes relative to the reference electrode can be used as the positive and negative electrode voltages. Based on this type of positive and negative electrode voltage, the DC resistance of the positive and negative electrodes of the three-electrode cell under pulsed operating conditions can be determined as the positive and negative electrode impedance data, thereby providing data support for subsequent anomaly detection processes.

[0060] S120: Determine the positive impedance data of at least one three-electrode cell based on the positive voltage, and determine the negative impedance data of at least one three-electrode cell based on the negative voltage.

[0061] In step S120, the technical solution provided in this application embodiment can determine the corresponding positive electrode impedance data and negative electrode impedance data based on the positive electrode voltage and negative electrode voltage obtained by voltage monitoring of each three-electrode cell in the battery pack.

[0062] The specific impedance types corresponding to the positive and negative electrode impedance data can be flexibly selected according to the actual voltage monitoring method. In some embodiments, when detecting the positive and negative electrode voltages of a three-electrode cell by electrochemical impedance detection, the positive and negative electrode impedance data can represent the electrochemical impedances of the positive and negative electrodes of the three-electrode cell, respectively, including at least charge transfer resistance (Rct), solid electrolyte interphase resistance (Rsei), and ohmic resistance (RΩ).

[0063] In other embodiments, when monitoring the positive and negative voltages of a three-electrode cell under pulsed operating conditions, the direct current resistance (DCR) of the positive and negative electrodes can be calculated based on the positive and negative voltages and pulse current of the three-electrode cell, and used as the positive and negative impedance data of the three-electrode cell.

[0064] The positive and negative impedance data determined in step S120 can fully represent the influence of the positive and negative electrodes on the overall impedance of the three-electrode cell. This allows for more detailed and precise identification of the root causes affecting the overall impedance increase of the cell during subsequent anomaly detection based on the positive and negative impedance data, significantly improving the accuracy and precision of anomaly detection. This enables proactive prevention and handling of anomaly risks, thereby enhancing the safety of three-electrode cells in use.

[0065] S130: Based on the positive and negative impedance data, the positive impedance outlier threshold, and the negative impedance outlier threshold, perform anomaly detection on the positive and negative impedance states of at least one three-electrode cell.

[0066] In step S130, the technical solution provided in this application embodiment can perform more detailed and accurate anomaly detection on the positive and negative impedance states of each three-electrode cell based on the impedance data of the positive and negative electrodes of each three-electrode cell in the battery pack obtained through the above steps.

[0067] In some embodiments, based on the positive and negative electrode impedance data, the impedance consistency of each three-electrode cell in the battery pack can be accurately detected, and abnormal cells with positive or negative electrode impedance data that are significantly different from other cells can be identified.

[0068] In other embodiments, multiple voltage monitoring and determination of corresponding positive and negative electrode impedance data can be performed on each three-electrode cell. Based on the obtained impedance data, abnormal detection of the positive and negative electrode impedance growth rate can be performed to accurately detect three-electrode cells in the battery pack that have abnormal growth rates.

[0069] The above embodiments can accurately determine the positive and negative impedances of a three-electrode battery cell by monitoring the positive and negative electrode voltages. Based on the positive and negative electrode impedances, the dominant causes leading to impedance increases in the cell can be accurately analyzed, and further, more precise anomaly detection can be performed on the positive and negative electrode impedance states of the three-electrode battery cell. This embodiment can accurately locate the sources of impedance increases and anomalies in three-electrode battery cells, accurately predict potential risks, significantly improve the safety and stability of three-electrode battery cells, and extend their service life.

[0070] Figure 2 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 2 As shown, step S110 in other embodiments is specified as steps S211 and S212 in this embodiment.

[0071] S211: Electrochemical impedance spectroscopy is performed on at least one three-electrode cell.

[0072] S212: The positive electrode response voltage of at least one three-electrode cell in electrochemical impedance detection is taken as the positive electrode voltage, and the negative electrode response voltage of at least one three-electrode cell in electrochemical impedance detection is taken as the negative electrode voltage.

[0073] In this embodiment, as shown in step S211, electrochemical impedance spectroscopy can be performed on each three-electrode cell in the battery pack that is in a static state and meets the detection environmental conditions. These detection environmental conditions include, but are not limited to, the battery pack's state of charge being at a preset state of charge, and the battery pack temperature being within a preset temperature range.

[0074] Specifically, in this embodiment, a small-amplitude sinusoidal current excitation is applied to the three-electrode cell, and the response voltages corresponding to the positive and negative electrodes of the three-electrode cell under constant current excitation are measured and recorded as the positive and negative electrode voltages obtained from voltage monitoring. In the subsequent determination of positive and negative electrode impedance data, electrochemical impedance spectra of the positive and negative electrodes can be constructed based on the positive and negative electrode voltages, which are essentially response voltages, thereby further determining the positive and negative electrode impedance data.

[0075] The above embodiment can determine the positive and negative electrode voltages and impedances of a three-electrode battery cell using electrochemical impedance spectroscopy. This embodiment provides the positive and negative electrode response voltages for subsequent impedance determination, offering a practical data foundation for later processing. Based on the positive and negative electrode voltages, the overall impedance of the three-electrode battery cell can be effectively separated, providing ample support for further detailed determination of the causes of impedance increases and anomaly detection.

[0076] Figure 3 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 3 As shown, step S120 in other embodiments is embodied as step S321 in this embodiment.

[0077] S321: Determine the positive electrode impedance data of at least one three-electrode cell based on the positive electrode voltage and the excitation current detected by electrochemical impedance, and determine the negative electrode impedance data of at least one three-electrode cell based on the negative electrode voltage and the excitation current.

[0078] As described in step S321, in this embodiment, the positive electrode electrochemical impedance spectrum and the negative electrode electrochemical impedance spectrum can be constructed based on the positive electrode voltage and negative electrode voltage obtained by voltage monitoring in step S212, and the excitation current applied to each three-electrode cell during the electrochemical impedance detection process.

[0079] Then, based on the constructed positive and negative electrochemical impedance spectra, the positive and negative electrochemical impedance data for the three-electrode cell can be determined respectively. The impedance data determined by electrochemical impedance detection may include, but is not limited to, charge transfer resistance, solid electrolyte interface film resistance, and ohmic resistance.

[0080] The above embodiment can accurately determine the resistance data corresponding to the positive and negative electrodes based on the response voltages of the positive and negative electrodes in a three-electrode cell during electrochemical impedance spectroscopy. This embodiment can efficiently and accurately determine the impedance data of the positive and negative electrodes, providing a real and effective data foundation for subsequent anomaly detection processes, and significantly improving the anomaly detection accuracy and efficiency of three-electrode cells.

[0081] Figure 4 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 4 As shown, step S110 in other embodiments is embodied as step S411 in this embodiment.

[0082] S411: For at least one three-electrode cell under pulsed operating conditions, determine the potential of the positive electrode relative to the reference electrode as the positive electrode voltage, and determine the potential of the negative electrode relative to the reference electrode as the negative electrode voltage.

[0083] As described in step S411, in addition to determining the positive and negative electrode voltages of the three-electrode cell by electrochemical impedance detection in steps S211 and S212, this embodiment can also monitor the voltage of the three-electrode cell under pulsed operating conditions. The potential of the positive electrode relative to the reference electrode in the three-electrode cell can be used as the positive electrode voltage obtained from voltage monitoring; similarly, the potential of the negative electrode relative to the reference electrode in the three-electrode cell can be used as the negative electrode voltage obtained from voltage monitoring.

[0084] The positive and negative voltages determined in step S411 can be used to determine the subsequent positive and negative impedance data. Specifically, the DC impedance data can be calculated for the positive and negative electrodes respectively based on the pulse current of the three-electrode cell under pulsed operating conditions, and used as the positive and negative impedance data.

[0085] The above embodiments enable precise monitoring of the positive and negative voltages of three-electrode cells under pulsed operating conditions. The determined voltage data can be used to determine the positive and negative impedance data, providing a solid data foundation. This embodiment achieves real-time and efficient voltage monitoring, improving the accuracy and efficiency of anomaly detection in three-electrode cells, enhancing cell safety, and extending cell lifespan.

[0086] Figure 5This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 5 As shown, step S120 in other embodiments is embodied as step S521 in this embodiment.

[0087] S521: Determine the positive impedance data of at least one three-electrode cell based on the positive voltage and pulse current, and determine the negative impedance data of at least one three-electrode cell based on the negative voltage and pulse current.

[0088] As described in step S521, in this embodiment, the positive and negative electrode voltages obtained from voltage monitoring of each three-electrode cell in step S411, and the pulse current of the three-electrode cell under pulsed operating conditions, can be used to calculate the DC resistance corresponding to the positive and negative electrodes, respectively, as the positive and negative electrode impedance data of the three-electrode cell. The positive and negative electrode impedance data can provide sufficient data support for subsequent anomaly detection processes of the three-electrode cell.

[0089] The above embodiments enable accurate and efficient determination of the positive and negative electrode impedance data of a three-electrode battery cell based on the pulse current under pulsed operating conditions and the monitored positive and negative electrode potentials. This embodiment accurately separates and determines the positive and negative electrode impedance data, providing a valid data foundation for subsequent anomaly detection processes, significantly improving anomaly detection accuracy, and offering strong timeliness, thus significantly enhancing the anomaly detection efficiency for three-electrode battery cells.

[0090] Figure 6 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 5 As shown, step S130 in other embodiments is embodied as step S631 in this embodiment.

[0091] S631: Based on the positive impedance outlier threshold and positive impedance data, perform positive impedance consistency detection on at least one three-electrode cell to identify cells with abnormal positive impedance; and based on the negative impedance outlier threshold and negative impedance data, perform negative impedance consistency detection on at least one three-electrode cell to identify cells with abnormal negative impedance.

[0092] The embodiments provided in this application can determine a positive impedance outlier threshold for detecting positive impedance anomalies based on the positive impedance data of all three-electrode cells in the battery pack. Similarly, a negative impedance outlier threshold can be determined based on the negative impedance data of all three-electrode cells for detecting negative impedance anomalies.

[0093] The specific method for determining the impedance outlier threshold for the positive and negative terminals can be flexibly selected according to actual needs and application scenarios. In some embodiments, the impedance outlier threshold can be dynamically set based on the mean and standard deviation of the impedance data. In other embodiments, the impedance outlier threshold can also be determined based on the median of the impedance data.

[0094] Then, as described in step S631, based on the determined positive impedance outlier threshold and the positive impedance data of each three-electrode cell, a positive impedance consistency test can be performed on each three-electrode cell to accurately detect cells with abnormal positive impedance that exceed the threshold range. Similarly, based on the determined negative impedance outlier threshold and the negative impedance data of each three-electrode cell, a negative impedance consistency test can be performed on each three-electrode cell to accurately detect cells with abnormal negative impedance that exceed the threshold range.

[0095] Based on this, accurate and effective detection of the positive and negative impedance consistency of each three-electrode cell within the battery pack can be achieved, effectively identifying cells with abnormal positive or negative impedance where impedance consistency is problematic. Furthermore, it allows for further anomaly type determination for these abnormal cells.

[0096] For example, based on the outlier degree of the positive electrode impedance data of a cell with abnormal positive electrode impedance, it can be determined that the corresponding three-electrode cell may have problems such as abnormal loss of positive electrode active material, abnormal changes in the positive electrode material structure, or poor contact. As another example, based on the outlier degree of the negative electrode impedance data of a cell with abnormal negative electrode impedance, it can be determined that the corresponding three-electrode cell may have problems such as abnormal lithium dendrite growth or even lithium plating, loss of negative electrode active material, or abnormal thickening of the negative electrode electrolyte interface film.

[0097] The above embodiments enable dynamic setting of outlier thresholds based on the positive and negative impedance data of three-electrode cells, achieving adaptive threshold judgment and dynamic anomaly detection. This embodiment allows for precise detection of consistency anomalies in three-electrode cells based on positive and negative impedance data, significantly improving anomaly detection accuracy and detail compared to overall cell impedance, thus providing effective assistance for early warning and prevention of anomaly risks.

[0098] Figure 7 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 7 As shown, in other embodiments, steps S731 and S732 are included before step S631.

[0099] S731: Determine the mean and standard deviation of the positive impedance data, and determine the mean and standard deviation of the negative impedance data.

[0100] S732: Determine the outlier threshold for positive impedance based on the mean and standard deviation of positive impedance, and determine the outlier threshold for negative impedance based on the mean and standard deviation of negative impedance.

[0101] As described in steps S731 and S732, in this embodiment, the outlier threshold for positive impedance can be determined based on the mean and standard deviation of the positive impedance corresponding to all three-electrode cells in the battery pack, and the outlier threshold for negative impedance can be determined based on the mean and standard deviation of the negative impedance. The outlier threshold determined based on the impedance mean and standard deviation can provide an anomaly judgment basis for the anomaly detection process in step S631 above, significantly improving the consistency detection accuracy for each three-electrode cell.

[0102] The process of determining the impedance outlier threshold is as follows: the impedance range consisting of the positive impedance mean plus or minus a preset multiple (e.g., 3 times, 2 times, etc.) and the positive impedance standard deviation is determined as the positive impedance outlier threshold. The negative impedance outlier threshold is determined in the same way, and the example will not be repeated here.

[0103] The above embodiments can dynamically set the impedance outlier threshold based on the mean and standard deviation of impedance data. Determining the dynamic threshold can effectively improve the adaptability of the overall cell anomaly detection method and expand its application scope. Anomaly judgment based on the outlier threshold can accurately analyze consistency anomalies among three-electrode cells, significantly improving anomaly detection accuracy, enabling early warning and remediation of potential risks, and enhancing cell safety.

[0104] Figure 8 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 8 As shown, in other embodiments, steps S831 and S832 are included before step S631.

[0105] S831: Determine the positive midpoint impedance data for the positive impedance data, and determine the negative midpoint impedance data for the negative impedance data.

[0106] S832: Determine the outlier threshold for positive impedance based on the positive median impedance data, and determine the outlier threshold for negative impedance based on the negative median impedance data.

[0107] In this application, it is considered that setting the impedance outlier threshold based solely on the impedance mean and standard deviation is easily affected by impedance data with a high degree of outlier, which reduces the authenticity and effectiveness of the threshold setting. For example, some impedance data with a high degree of outlier may significantly raise or lower the mean, while amplifying the standard deviation.

[0108] Based on this, as shown in steps S831 and S832 above, in this embodiment, the outlier thresholds of the impedance corresponding to the positive and negative electrodes can also be dynamically determined based on the median of the impedance data corresponding to all three-electrode cells in the battery pack.

[0109] Specifically, in some embodiments, based on the positive median impedance data, the two quartiles before and after the positive median impedance data can be determined among all positive impedance data, and the interquartile range (IQR) can be determined based on the two quartiles. Then, the impedance range formed by adding or subtracting a preset multiple (e.g., 1.5, 3, etc.) from the two quartiles in all positive impedance data can be used as the positive impedance outlier threshold, and the negative impedance outlier threshold is determined in the same way.

[0110] In addition to the interquartile range mentioned above, the median absolute deviation (MAD) of the positive impedance data can also be combined with the median impedance data to determine the outlier thresholds for the corresponding positive and negative impedances. In some embodiments, the impedance range formed by adding or subtracting a preset multiple from the median absolute deviation of the positive impedance data can be used as the positive impedance outlier threshold, and the same applies to the negative impedance outlier threshold.

[0111] Here, the median absolute deviation is the median of the absolute deviation between each data point (each positive impedance data point) and the median (positive median impedance data point). In other embodiments, for example, the percentile range or quartile coefficient of the positive impedance data can be selected and combined with the median impedance data to determine the impedance outlier threshold. This can be flexibly selected according to actual needs and application scenarios.

[0112] The above embodiments allow for dynamic setting of outlier thresholds based on the median of multiple impedance data points, effectively suppressing the impact of extreme outliers in the impedance data. This embodiment enables adaptive setting of the outlier threshold, providing a valid basis for subsequent anomaly detection in three-electrode cells, significantly improving anomaly detection accuracy and efficiency.

[0113] Figure 9 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 9 As shown, step S110 in other embodiments is embodied as step S911 in this embodiment.

[0114] S911: Perform multiple voltage monitoring on at least one three-electrode cell to determine multiple positive and multiple negative voltages of at least one three-electrode cell under multiple voltage monitoring.

[0115] As described in step S911, in this embodiment, the voltage of each three-electrode cell in the battery pack can be monitored multiple times according to a preset monitoring cycle to obtain the corresponding positive and negative electrode voltages under each voltage monitoring. The specific determination process can refer to the voltage monitoring method using electrochemical impedance spectroscopy in the above embodiment, or the voltage monitoring method for three-electrode cells under pulsed operating conditions.

[0116] The multiple positive and negative electrode voltages corresponding to each three-electrode cell can be used to detect cell inconsistencies within the battery pack in the above embodiments. Simultaneously, the rate of increase in positive or negative electrode impedance can be determined based on adjacent positive or negative electrode voltages. Therefore, based on the rate of increase in positive and negative electrode impedance, anomaly detection of impedance growth rate can be performed on each three-electrode cell within the battery pack.

[0117] The above embodiments allow for multiple voltage monitoring sessions for each three-electrode cell, increasing the data volume and providing ample data support for subsequent anomaly detection processes targeting impedance growth rates. This significant increase in data volume enhances the accuracy and reliability of the overall anomaly detection process, further improving the safety of three-electrode cells in use.

[0118] Figure 10 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 10 As shown, step S130 in other embodiments is specified as steps S1031 and S1032 in this embodiment.

[0119] S1031: Based on multiple positive impedance data of at least one three-electrode cell under multiple voltage monitoring, determine the positive impedance growth rate of at least one three-electrode cell, and based on multiple negative impedance data of at least one three-electrode cell under multiple voltage monitoring, determine the negative impedance growth rate of at least one three-electrode cell.

[0120] S1032: Based on the positive impedance growth rate and a preset impedance growth rate threshold, perform positive impedance growth rate anomaly detection on at least one three-electrode cell to identify cells with abnormal positive impedance growth; and based on the negative impedance growth rate and a preset impedance growth rate threshold, perform negative impedance growth rate anomaly detection on at least one three-electrode cell to identify cells with abnormal negative impedance growth.

[0121] As described in steps S1031 and S1032, in this embodiment, the positive impedance growth rate of each three-electrode cell can be calculated based on the multiple positive impedance data determined after multiple voltage monitoring of each three-electrode cell in the battery pack, and the negative impedance growth rate of each three-electrode cell can be calculated based on the multiple negative impedances.

[0122] Then, based on the positive and negative impedance growth rates, precise anomaly detection can be performed on the impedance growth rate of the three-electrode cell. Specifically, the relationship between the positive and negative impedance growth rates and a preset impedance growth rate threshold can be determined to identify whether the corresponding three-electrode cell is a normal cell, a cell with abnormal positive impedance growth, or a cell with abnormal negative impedance growth, or both simultaneously, thus achieving precise localization of impedance growth problems.

[0123] For example, consider the positive impedance growth rate. Suppose that after the processing described in the above embodiment, the positive impedance growth rate of a certain three-electrode cell in the battery pack exceeds a preset impedance growth rate threshold, while the negative impedance growth rate does not exceed the preset impedance growth rate threshold. In this case, it can be determined that the positive impedance growth rate of the three-electrode cell is significantly abnormal, and the three-electrode cell is a cell with abnormal positive impedance growth.

[0124] The above embodiments enable precise determination and anomaly detection of the impedance growth rate of the three electrodes based on the positive and negative electrode impedance data obtained from multiple voltage monitoring sessions. Accurate identification of the dominant causes of impedance growth in the three-electrode cell significantly improves the processing accuracy and efficiency of impedance analysis and anomaly detection, providing a practical reference basis for subsequent adjustments to charging and discharging strategies and other operational processes.

[0125] Figure 11 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 11 As shown, in other embodiments, step S1032 is followed by step S1131.

[0126] S1131: Based on multiple positive and negative impedance data of at least one three-electrode cell under multiple voltage monitoring, as well as the positive and negative impedance growth rates, determine the adjustment parameters of the battery pack's charging and discharging power.

[0127] As described in step S1131, in this embodiment, the charging and discharging power can be adaptively adjusted based on the positive impedance data and positive impedance growth rate determined after multiple voltage monitoring of each three-electrode cell in the battery pack, as well as the negative impedance data and negative impedance growth rate.

[0128] Specifically, for example, based on the positive and negative electrode impedance data obtained in the above embodiments, the three-electrode cells with the highest positive electrode impedance and the three-electrode cells with the highest negative electrode impedance within the entire battery pack can be identified. Based on the positive electrode impedance data of the three-electrode cell with the highest positive electrode impedance, the charging power of the battery pack can be adjusted accordingly. Similarly, based on the negative electrode impedance data of the three-electrode cell with the highest negative electrode impedance, the discharging power of the battery pack can be adjusted accordingly.

[0129] Simultaneously, based on the positive and negative impedance growth rates of each normal three-electrode cell, accurate predictions of future impedance growth can be made, allowing for the pre-determining of corresponding charge and discharge power adjustment strategies. This ensures that all cells within the battery pack can operate safely and stably, significantly improving the safety of the three-electrode cells and the overall battery pack, and effectively extending their service life.

[0130] The above embodiments enable dynamic adjustment of charging and discharging power during actual use of a three-electrode battery cell, based on the impedance data of its positive and negative electrodes and the impedance growth rate. Appropriately matched charging and discharging power can effectively improve the safety of the battery cell and extend its lifespan.

[0131] Figure 12 This is a flowchart illustrating a cell anomaly detection method provided in some embodiments of this application. Figure 12 As shown, it includes steps S1210 to S1250.

[0132] S1210: Perform voltage monitoring on each three-electrode cell in the battery pack at least once to determine the positive and negative electrode voltages.

[0133] S1220: Determine the positive impedance data corresponding to the positive electrode voltage and the negative impedance data corresponding to the negative electrode voltage for each voltage monitoring of the three-electrode cell.

[0134] S1230: Based on the positive and negative impedance data from each voltage monitoring, perform impedance consistency detection on the positive and negative electrodes of each three-electrode cell to identify cells with abnormal positive and negative impedance.

[0135] S1240: Based on the positive and negative impedance data from multiple voltage monitoring, determine the positive and negative impedance growth rates for each three-electrode cell.

[0136] S1250: Based on the positive impedance growth rate and the negative impedance growth rate, identify cells with abnormal positive impedance growth and cells with abnormal negative impedance growth.

[0137] As described in steps S1210 to S1250 above, the cell anomaly detection method provided in this application embodiment can accurately monitor the positive and negative electrode voltages of a three-electrode cell and determine the corresponding positive and negative electrode impedances. Based on the determined positive and negative electrode impedance data, two types of anomaly detection are performed: impedance consistency and impedance growth rate, significantly improving the accuracy and refinement of anomaly detection for three-electrode cells. The specific processing procedures and feasible embodiments corresponding to each step can be found in the corresponding content of the above embodiments, and will not be elaborated further here.

[0138] Based on the same inventive concept as the above-described cell anomaly detection method, this application also provides a battery management system for applying the above-described cell anomaly detection method. The battery management system provided in this application will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0139] Figure 13 This is a schematic diagram of a battery management system provided for some embodiments of this application. The battery management system 1300 includes: The sampling circuit 1310 is used to monitor the voltage of at least one three-electrode cell in the battery pack of an electric vehicle under different operating conditions, and to determine the positive and negative voltages of at least one three-electrode cell. The controller 1320 is configured to determine the positive impedance data of at least one three-electrode cell based on the positive electrode voltage, and to determine the negative impedance data of at least one three-electrode cell based on the negative electrode voltage; and to perform anomaly detection on the positive and negative impedance states of at least one three-electrode cell based on the positive and negative impedance data, the positive impedance outlier threshold, and the negative impedance outlier threshold, wherein the positive impedance outlier threshold is determined based on the positive impedance data of all three-electrode cells in the battery pack, and the negative impedance outlier threshold is determined based on the negative impedance data of all three-electrode cells in the battery pack.

[0140] In some embodiments, the sampling circuit 1310 includes: Electrochemical impedance spectroscopy was performed on at least one three-electrode cell. The positive electrode response voltage of at least one three-electrode cell in electrochemical impedance detection is taken as the positive electrode voltage, and the negative electrode response voltage of at least one three-electrode cell in electrochemical impedance detection is taken as the negative electrode voltage.

[0141] In some embodiments, the controller 1320 includes: Based on the positive electrode voltage and the excitation current detected by electrochemical impedance, determine the positive electrode impedance data of at least one three-electrode cell, and based on the negative electrode voltage and the excitation current, determine the negative electrode impedance data of at least one three-electrode cell. The impedance data includes at least one of charge transfer resistance, ohmic resistance, and solid electrolyte interface film resistance.

[0142] In some embodiments, the sampling circuit 1310 includes: For at least one three-electrode cell under pulsed operating conditions, the potential of the positive electrode relative to the reference electrode is determined as the positive electrode voltage, and the potential of the negative electrode relative to the reference electrode is determined as the negative electrode voltage.

[0143] In some embodiments, the controller 1320 includes: Based on the positive electrode voltage and pulse current, determine the positive electrode impedance data of at least one three-electrode cell, and based on the negative electrode voltage and pulse current, determine the negative electrode impedance data of at least one three-electrode cell.

[0144] In some embodiments, the controller 1320 includes: Based on the positive impedance outlier threshold and positive impedance data, positive impedance consistency detection is performed on at least one three-electrode cell to identify cells with abnormal positive impedance. Similarly, based on the negative impedance outlier threshold and negative impedance data, negative impedance consistency detection is performed on at least one three-electrode cell to identify cells with abnormal negative impedance.

[0145] In some embodiments, the controller 1320 includes: Determine the mean and standard deviation of the positive impedance data, and determine the mean and standard deviation of the negative impedance data; The outlier threshold for positive impedance is determined based on the mean and standard deviation of positive impedance, and the outlier threshold for negative impedance is determined based on the mean and standard deviation of negative impedance.

[0146] In some embodiments, the controller 1320 includes: Determine the positive midpoint impedance data for the positive impedance data, and determine the negative midpoint impedance data for the negative impedance data; Based on the positive electrode median impedance data, the positive electrode impedance outlier threshold is determined, and based on the negative electrode median impedance data, the negative electrode impedance outlier threshold is determined.

[0147] In some embodiments, the controller 1320 includes: Multiple voltage monitoring sessions are performed on at least one three-electrode cell to determine multiple positive and multiple negative electrode voltages of the at least one three-electrode cell under multiple voltage monitoring sessions.

[0148] In some embodiments, the controller 1320 includes: Based on multiple positive impedance data of at least one three-electrode cell under multiple voltage monitoring, determine the positive impedance growth rate of at least one three-electrode cell, and based on multiple negative impedance data of at least one three-electrode cell under multiple voltage monitoring, determine the negative impedance growth rate of at least one three-electrode cell. Based on the positive impedance growth rate and a preset impedance growth rate threshold, at least one three-electrode cell is subjected to positive impedance growth rate anomaly detection to identify cells with abnormal positive impedance growth. Similarly, based on the negative impedance growth rate and a preset impedance growth rate threshold, at least one three-electrode cell is subjected to negative impedance growth rate anomaly detection to identify cells with abnormal negative impedance growth.

[0149] In some embodiments, the controller 1320 includes: Based on multiple positive and negative impedance data of at least one three-electrode cell under multiple voltage monitoring, as well as the positive and negative impedance growth rates, the adjustment parameters for the charging and discharging power of the battery pack are determined.

[0150] The battery management system of this application is used to perform at least one of the following functions for individual battery cells: state monitoring, state analysis, charge / discharge control, safety protection, information management, thermal management, and high-voltage power distribution. In addition, the battery management system of this application can also perform the functions of a controller in an electrical device, such as a vehicle control unit (VCU) or a motor control unit (MCU), etc., and this application does not impose any limitations on this.

[0151] It should be noted that the battery management system in this application can be integrated as a controller into the battery device, such as into the battery pack or energy storage box. The battery management system in this application can also be integrated as a controller into electrical devices, such as in a vehicle or vehicle chassis. The battery management system in this application can also be integrated into the charging device as a controller, such as into the charging device or the battery swapping device. The battery management system in this application can also be deployed as control software on a server. The server can be a standalone physical server, a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides basic cloud computing services such as cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communication, middleware services, domain name services, security services, CDN (Content Delivery Network), and big data and artificial intelligence platforms, such as vehicle networking cloud, APP backend, etc.

[0152] Based on the same inventive concept, embodiments of this application also provide a battery device, including a battery and a battery management system as described in the above embodiments.

[0153] Based on the same inventive concept, this application also provides an electrical device, including the battery device as described in the above embodiments.

[0154] Figure 14 This is a schematic diagram of the structure of an electronic device provided in some embodiments of this application.

[0155] like Figure 14 As shown, the electronic device 1400 is a structural diagram of an exemplary hardware architecture of an electronic device that implements the cell anomaly detection method according to the embodiments of this application. This electronic device may refer to the electronic device in the embodiments of this application.

[0156] The electronic device 1400 may include a processor 1401 and a memory 1402 storing computer program instructions.

[0157] Specifically, the processor 1401 may include a central processing unit (CPU), an application-specific integrated circuit (ASIC), or one or more integrated circuits that can be configured to implement the embodiments of this application.

[0158] Memory 1402 may include mass storage for data or instructions. For example, and not limitingly, memory 1402 may include a hard disk drive (HDD), floppy disk drive, flash memory, optical disk, magneto-optical disk, magnetic tape, or Universal Serial Bus (USB) drive, or a combination of two or more of these. Where appropriate, memory 1402 may include removable or non-removable (or fixed) media. Where appropriate, memory 1402 may be internal or external to the integrated gateway disaster recovery device. In a particular embodiment, memory 1402 is non-volatile solid-state memory. In a particular embodiment, memory 1402 may include read-only memory (ROM), random access memory (RAM), disk storage media device, optical storage media device, flash memory device, electrical, optical, or other physical / tangible memory storage device. Therefore, typically, memory 1402 includes one or more tangible (non-transitory) computer-readable storage media (e.g., memory devices) encoded with software including computer-executable instructions, and when the software is executed (e.g., by one or more processors), it is operable to perform the operations described with reference to the method according to one aspect of this application.

[0159] The processor 1401 reads and executes computer program instructions stored in the memory 1402 to implement any of the cell anomaly detection methods in the above embodiments.

[0160] In one example, the electronic device may also include a communication interface 1403 and a bus 1404. Wherein, as... Figure 14 Figure 14 As shown, the processor 1401, memory 1402, and communication interface 1403 are connected through bus 1404 and complete communication with each other.

[0161] The communication interface 1403 is mainly used to realize communication between various modules, devices and / or equipment in the embodiments of this application.

[0162] Bus 1404 includes hardware, software, or both, that couples components of electronic device 1400 together. For example, and not limitingly, the bus may include Accelerated Graphics Port (AGP) or other graphics buses, Enhanced Industry Standard Architecture (EISA) buses, Front Side Bus (FSB), HyperTransport (HT) interconnects, Industry Standard Architecture (ISA) buses, Infinite Bandwidth Interconnects, Low Pin Count (LPC) buses, memory buses, Microchannel Architecture (MCA) buses, Peripheral Component Interconnect (PCI) buses, PCI-Express (PCI-X) buses, Serial Advanced Technology Attachment (SATA) buses, Video Electronics Standards Association Local (VLB) buses, or other suitable buses, or combinations of two or more of these. Where appropriate, bus 1404 may include one or more buses. Although specific buses are described and illustrated in embodiments of this application, any suitable bus or interconnect is contemplated herein.

[0163] The electronic device can perform the cell anomaly detection method of any of the embodiments in this application.

[0164] Furthermore, in conjunction with the cell anomaly detection methods in the above embodiments, this application embodiment can provide a computer storage medium for implementation. The computer storage medium stores computer program instructions; when these computer program instructions are executed by a processor, they implement any of the cell anomaly detection methods in the above embodiments.

[0165] This application also provides a chip, which includes a processor and a communication interface. The communication interface is coupled to the processor. The processor is used to run programs or instructions to implement the various processes of the above method embodiments and achieve the same technical effect. To avoid repetition, it will not be described again here.

[0166] It should be understood that the chip mentioned in the embodiments of this application may also be referred to as a system-on-a-chip, system chip, chip system, or system-on-a-chip, etc.

[0167] This application provides a computer program product stored in a readable storage medium. When executed by at least one processor, the program product can implement the various processes of the above method embodiments and achieve the same technical effects. To avoid repetition, further details are omitted here.

[0168] It should be clarified that this application is not limited to the specific configurations and processes described above and shown in the figures. For the sake of brevity, detailed descriptions of known methods are omitted here. In the above embodiments, several specific steps are described and shown as examples. However, the method process of this application is not limited to the specific steps described and shown. Those skilled in the art can make various changes, modifications, and additions, or change the order of steps, after understanding the spirit of this application.

[0169] The functional blocks shown in the above block diagram can be implemented as hardware, software, firmware, or a combination thereof. When implemented in hardware, they can be, for example, electronic circuits, application-specific integrated circuits (ASICs), appropriate firmware, plug-ins, function cards, etc. When implemented in software, the elements of this application are programs or code segments used to perform the required tasks. Programs or code segments can be stored on a machine-readable medium or transmitted over a transmission medium or communication link via data signals carried on a carrier wave. "Machine-readable medium" can include any medium capable of storing or transmitting information. Examples of machine-readable media include electronic circuits, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disks, CD-ROMs, optical disks, hard disks, fiber optic media, radio frequency (RF) links, etc. Code segments can be downloaded via computer networks such as the Internet, intranets, etc.

[0170] It should also be noted that the exemplary embodiments mentioned in this application describe methods or systems based on a series of steps or apparatus. However, this application is not limited to the order of the above steps; that is, the steps can be performed in the order mentioned in the embodiments, or in a different order, or several steps can be performed simultaneously.

[0171] The aspects of this application have been described above with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It should be understood that each block in the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing apparatus to produce a machine such that these instructions, executable via the processor of the computer or other programmable data processing apparatus, enable the implementation of the functions / actions specified in one or more blocks of the flowchart illustrations and / or block diagrams. Such a processor can be, but is not limited to, a general-purpose processor, a special-purpose processor, a special application processor, or a field-programmable logic circuit. It is also understood that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can also be implemented by dedicated hardware performing the specified functions or actions, or can be implemented by a combination of dedicated hardware and computer instructions.

[0172] Although this application has been described with reference to preferred embodiments, various modifications can be made thereto and components can be replaced with equivalents without departing from the scope of this application. In particular, the technical features mentioned in the various embodiments can be combined in any manner, provided there is no structural conflict. This application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method for detecting abnormalities in battery cells, characterized in that, The method includes: Voltage monitoring is performed on at least one three-electrode cell in the battery pack of an electric vehicle under different operating conditions to determine the positive and negative electrode voltages of the at least one three-electrode cell. Based on the positive electrode voltage, determine the positive electrode impedance data of the at least one three-electrode cell, and based on the negative electrode voltage, determine the negative electrode impedance data of the at least one three-electrode cell. Based on the positive and negative impedance data, the positive and negative impedance outlier thresholds, and the negative impedance outlier threshold, anomaly detection is performed on the positive and negative impedance states of at least one three-electrode cell. The positive impedance outlier threshold is determined based on the positive impedance data of all three-electrode cells in the battery pack, and the negative impedance outlier threshold is determined based on the negative impedance data of all three-electrode cells in the battery pack.

2. The method according to claim 1, characterized in that, Voltage monitoring of at least one three-electrode cell within the battery pack of an electric vehicle under different operating conditions, determining the positive and negative electrode voltages of the at least one three-electrode cell, including: Electrochemical impedance spectroscopy was performed on at least one three-electrode cell. The positive electrode response voltage of the at least one three-electrode cell in the electrochemical impedance detection is taken as the positive electrode voltage, and the negative electrode response voltage of the at least one three-electrode cell in the electrochemical impedance detection is taken as the negative electrode voltage.

3. The method according to claim 2, characterized in that, Determining the positive impedance data of the at least one three-electrode cell based on the positive electrode voltage, and determining the negative impedance data of the at least one three-electrode cell based on the negative electrode voltage, including: Based on the positive electrode voltage and the excitation current detected by the electrochemical impedance, the positive electrode impedance data of the at least one three-electrode cell is determined, and based on the negative electrode voltage and the excitation current, the negative electrode impedance data of the at least one three-electrode cell is determined. The impedance data includes at least one of charge transfer resistance, ohmic resistance, and solid electrolyte interface film resistance.

4. The method according to claim 1, characterized in that, Voltage monitoring of at least one three-electrode cell within the battery pack of an electric vehicle under different operating conditions, determining the positive and negative electrode voltages of the at least one three-electrode cell, including: For the at least one three-electrode cell under pulsed operating conditions, the potential of the positive electrode relative to the reference electrode is determined as the positive electrode voltage, and the potential of the negative electrode relative to the reference electrode is determined as the negative electrode voltage.

5. The method according to claim 4, characterized in that, Determining the positive impedance data of the at least one three-electrode cell based on the positive electrode voltage, and determining the negative impedance data of the at least one three-electrode cell based on the negative electrode voltage, including: Based on the positive electrode voltage and pulse current, the positive electrode impedance data of the at least one three-electrode cell is determined, and based on the negative electrode voltage and pulse current, the negative electrode impedance data of the at least one three-electrode cell is determined.

6. The method according to any one of claims 1-5, characterized in that, Based on the positive and negative impedance data, the positive impedance outlier threshold, and the negative impedance outlier threshold, anomaly detection is performed on the positive and negative impedance states of the at least one three-electrode cell, including: Based on the positive impedance outlier threshold and the positive impedance data, positive impedance consistency detection is performed on the at least one three-electrode cell to identify cells with abnormal positive impedance. Similarly, based on the negative impedance outlier threshold and the negative impedance data, negative impedance consistency detection is performed on the at least one three-electrode cell to identify cells with abnormal negative impedance.

7. The method according to any one of claims 1-5, characterized in that, The positive impedance outlier threshold is determined based on the positive impedance data of all three-electrode cells in the battery pack, and the negative impedance outlier threshold is determined based on the negative impedance data of all three-electrode cells in the battery pack, including: Determine the mean and standard deviation of the positive impedance data, and determine the mean and standard deviation of the negative impedance data; The positive impedance outlier threshold is determined based on the mean positive impedance and the standard deviation of the positive impedance, and the negative impedance outlier threshold is determined based on the mean negative impedance and the standard deviation of the negative impedance.

8. The method according to any one of claims 1-5, characterized in that, The positive impedance outlier threshold is determined based on the positive impedance data of all three-electrode cells in the battery pack, and the negative impedance outlier threshold is determined based on the negative impedance data of all three-electrode cells in the battery pack, including: Determine the positive median impedance data of the positive impedance data, and determine the negative median impedance data of the negative impedance data; Based on the positive electrode median impedance data, the positive electrode impedance outlier threshold is determined, and based on the negative electrode median impedance data, the negative electrode impedance outlier threshold is determined.

9. The method according to any one of claims 1-5, characterized in that, Voltage monitoring of at least one three-electrode cell within the battery pack of an electric vehicle under different operating conditions, determining the positive and negative electrode voltages of the at least one three-electrode cell, including: The voltage of the at least one three-electrode cell is monitored multiple times to determine the multiple positive and multiple negative voltages of the at least one three-electrode cell under multiple voltage monitoring.

10. The method according to claim 9, characterized in that, Based on the positive and negative impedance data, anomaly detection is performed on the positive and negative impedance states of the at least one three-electrode cell, including: Based on multiple positive impedance data of the at least one three-electrode cell under multiple voltage monitoring, the positive impedance growth rate of the at least one three-electrode cell is determined, and based on multiple negative impedance data of the at least one three-electrode cell under multiple voltage monitoring, the negative impedance growth rate of the at least one three-electrode cell is determined. Based on the positive impedance growth rate and the preset impedance growth rate threshold, the positive impedance growth rate of the at least one three-electrode cell is detected to be abnormal, and the positive impedance growth rate of the at least one three-electrode cell is detected to be abnormal, based on the negative impedance growth rate and the preset impedance growth rate threshold, and the negative impedance growth rate of the at least one three-electrode cell is detected to be abnormal, and the negative impedance growth rate of the at least one three-electrode cell is detected to be abnormal.

11. The method according to claim 10, characterized in that, The method further includes: Based on multiple positive and negative impedance data of the at least one three-electrode cell under multiple voltage monitoring, as well as the positive and negative impedance growth rates, the adjustment parameters for the charging and discharging power of the battery pack are determined.

12. A battery management system, characterized in that, The system includes: A sampling circuit is used to monitor the voltage of at least one three-electrode cell in the battery pack of an electric vehicle under different operating conditions, and to determine the positive and negative voltages of the at least one three-electrode cell. A controller is configured to determine the positive impedance data of the at least one three-electrode cell based on the positive voltage, and to determine the negative impedance data of the at least one three-electrode cell based on the negative voltage; and to perform anomaly detection on the positive and negative impedance states of the at least one three-electrode cell based on the positive impedance data and the negative impedance data, a positive impedance outlier threshold and a negative impedance outlier threshold, wherein the positive impedance outlier threshold is determined based on the positive impedance data of all three-electrode cells in the battery pack, and the negative impedance outlier threshold is determined based on the negative impedance data of all three-electrode cells in the battery pack.

13. A battery device, characterized in that, Includes a battery and a battery management system as described in claim 12.

14. An electrical appliance, characterized in that, Includes the battery device as described in claim 13.

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