Battery status detection methods, apparatus, equipment, storage media, and software products

Abstract

This application provides a battery state detection method, apparatus, device, storage medium, and program product. The method includes: monitoring the expansion force during battery operation to obtain a measured value of the battery's expansion force; estimating different types of expansion forces based on the measured expansion force values ​​to obtain a first expansion force and a second expansion force; the first expansion force is the expansion force generated by the increase in internal gas pressure, and the second expansion force is the expansion force generated by the increase in the thickness of the internal electrode plates during battery operation; and detecting and issuing warnings for battery anomalies based on the first and second expansion forces. In this embodiment, by decomposing the measured expansion force values ​​to obtain the first and second expansion forces, more accurate battery anomaly analysis can be obtained, reducing the possibility of false or missed detections of battery anomalies, improving the accuracy and reliability of battery anomaly type detection, and ensuring battery safety.

Description

Technical Field

[0001] This invention relates to the field of battery management technology, and in particular to a battery state detection method, apparatus, device, storage medium, and program product. Background Technology

[0002] As the core component of energy storage and power systems, the performance and safety status of batteries directly determine the reliability and service life of the system. Therefore, it is necessary to monitor and manage the status of batteries during operation.

[0003] Existing battery management solutions typically rely on parameters such as voltage, current, and temperature to assess battery status and detect anomalies. However, these parameters are relatively slow to characterize battery status, and they often represent the overall performance of the battery. Therefore, such solutions struggle to detect potential abnormal states in a timely and accurate manner, leading to low accuracy in battery status detection and instances of misjudgment or missed detection of battery anomalies, thus posing battery safety risks. Summary of the Invention

[0004] This invention provides a battery state detection method, apparatus, device, storage medium, and program product to solve the problem that it is difficult to detect different abnormal states that may occur in the battery in a timely and accurate manner during battery operation, resulting in low accuracy of battery state detection and causing battery safety risks.

[0005] In a first aspect, embodiments of this application provide a battery state detection method, including:

[0006] Monitor the expansion force during battery operation to obtain the battery's expansion force measurement value;

[0007] Based on the measured expansion force values, the expansion forces of different types of batteries are estimated to obtain the first expansion force and the second expansion force of the battery. The first expansion force is the expansion force generated by the increase of gas pressure inside the battery, and the second expansion force is the expansion force generated by the increase of the thickness of the internal electrode during battery operation.

[0008] Based on the battery's first and second expansion forces, abnormal battery types are detected and warnings are issued.

[0009] In this embodiment, by monitoring the expansion force during battery operation, the structural stress changes of the battery during operation can be dynamically reflected through the expansion force parameter, thereby achieving timely and accurate battery status assessment and monitoring. Furthermore, during the monitoring of the battery's expansion force measurement value, by decomposing the battery's expansion force measurement value into different types of expansion forces, it is possible to distinguish between the first expansion force generated by the increase in internal gas pressure and the second expansion force generated by the increase in electrode thickness. This provides a more accurate basis for battery anomaly analysis. Based on the first and second expansion forces, battery anomaly types can be identified, detected, and warned. This can clearly identify state anomalies caused by different types of reasons such as side reactions and electrode expansion and thickening, reducing the possibility of misjudgment or missed detection of battery anomalies, improving the accuracy and reliability of battery anomaly type detection, thereby reducing the probability of battery failure and safety accidents, and ensuring battery safety.

[0010] In one embodiment, based on the measured expansion force values, the expansion forces of different types of batteries are estimated to obtain the first and second expansion forces of the battery. This includes: if the battery's state is determined to be abnormal based on the expansion force measurements, the expansion forces of different types of batteries are estimated based on the measured expansion force values ​​to obtain the first and second expansion forces of the battery. In this solution, before decomposing the expansion forces, anomaly judgment is quickly performed using the measured expansion force values, which also reduces unnecessary data processing under normal operating conditions, thereby improving the overall detection efficiency.

[0011] In one embodiment, based on the measured expansion force values, the expansion forces of different types of batteries are estimated to obtain the first and second expansion forces of the battery. This includes: determining the target expansion force ratio of the battery based on the number of battery cycles, from pre-calibrated expansion force ratio data. The expansion force ratio data is calibrated based on actual battery measurement data and includes the ratio values ​​of different types of expansion forces corresponding to batteries with different cycle numbers during operation; and estimating the expansion forces of different types of batteries based on the measured expansion force values ​​and the target expansion force ratio to obtain the first and second expansion forces of the battery. In this solution, by introducing the key factor of cycle number, the expansion force decomposition process can dynamically adapt to the battery's usage stage, thereby improving the accuracy of the estimation of the first and second expansion forces throughout the entire life cycle.

[0012] In one embodiment, the expansion force ratio data is calibrated as follows:

[0013] Using the simulated expansion force data of the battery casing as the expansion force benchmark, the measured expansion force data of the battery under test at different cycle numbers are classified to obtain the first expansion force and the second expansion force of the battery under test at different cycle numbers;

[0014] Based on the first and second expansion forces of the battery under test at different cycles, the proportion of the first and second expansion forces at different cycles is determined to generate expansion force proportion data.

[0015] The measured expansion force data was obtained by running the battery under test for different number of cycles, while the simulated expansion force data was obtained by simulating the battery operating conditions of the battery casing. The battery casing is the casing structure of the battery under test after removing the internal electrode components and electrolyte.

[0016] This solution simulates the operating conditions of an empty battery casing, effectively mimicking the effect of internal gas pressure on the casing. This yields simulated data on the expansion force generated purely by the interaction between the casing and internal gas pressure. Real-world operating conditions are then measured on actual batteries to obtain measured data on the overall battery expansion force caused by the combined effects of internal gas and electrode thickness. This simulated expansion force data is then used as a benchmark for expansion force breakdown and proportion calibration, improving the accuracy of the expansion force proportion data and providing accurate data for subsequent battery expansion force decomposition and anomaly detection.

[0017] In one embodiment, using simulated expansion force data of the battery casing as the expansion force benchmark, the measured expansion force data of the battery under test at different cycle numbers are classified to obtain the first expansion force and the second expansion force of the battery under test at different cycle numbers, including:

[0018] The measured data of the expansion force of the battery under test at different cycles are obtained. The measured data of the expansion force includes the large surface expansion force and the end face expansion force of the battery under test at the corresponding cycle number. The large surface expansion force is the expansion force on the side of the battery cell corresponding to the electrode winding direction, and the end face expansion force is the expansion force on the end face of the battery perpendicular to the electrode winding direction.

[0019] Obtain the expansion force simulation data of the battery casing, which includes the large-area expansion force and end-face expansion force of the battery casing under different inflation pressures;

[0020] The end-face expansion force in the measured expansion force data and the end-face expansion force in the expansion force simulation data are aligned. Based on the large-area expansion force in the expansion force simulation data, the large-area expansion force in the measured expansion force data is decomposed to obtain the first expansion force and the second expansion force of the battery under test at different cycles.

[0021] In this scheme, two types of expansion forces, namely large-area expansion force and end-face expansion force, are measured separately during the test. The end-face expansion force in the measured expansion force data and the simulated expansion force data are used as alignment benchmarks to classify the expansion forces. This allows for more accurate elimination of the overall pressure effect when decomposing the expansion forces, thus making the decomposition of expansion forces more refined.

[0022] In one embodiment, based on the first and second expansion forces of the battery under test at different cycle numbers, the ratio of the first and second expansion forces at different cycle numbers is determined to generate expansion force ratio data, including:

[0023] Based on the first and second expansion forces of the battery under test at different cycles, determine the proportion of the first expansion force and the proportion of the second expansion force at different cycles.

[0024] The performance of the battery under test is verified based on the proportion of the first expansion force and the proportion of the second expansion force under different cycles.

[0025] If the performance qualification verification result of the battery under test is qualified, the proportion of the first expansion force and the proportion of the second expansion force of the battery under test under different cycles will be output as expansion force proportion data.

[0026] In this solution, performance qualification verification is performed before outputting the expansion force ratio data. This ensures that the data used for calibration comes only from batteries with normal performance and that meet design requirements. It reduces the deviation in expansion force ratio caused by using data from batteries with defects or early anomalies, and ensures the accuracy and reliability of the calibration data.

[0027] In one embodiment, the abnormality type detection and early warning of the battery are performed based on the first expansion force and the second expansion force of the battery, including:

[0028] Based on the first and second expansion forces of the battery, the abnormal state of the battery is classified and identified to determine the abnormal type of the battery. The abnormal type is used to indicate the abnormal state of the battery.

[0029] Based on the type of battery anomaly, an anomaly warning message is generated, which is used to warn of abnormal battery conditions.

[0030] In this solution, the specific abnormal situation of the battery can be distinguished by the specific abnormality type. This overcomes the shortcomings of related solutions that only judge that there is an overall abnormality but cannot explain the specific source of the problem. It can also more accurately distinguish between normal fluctuations and real abnormalities, thereby reducing false alarms and missed alarms.

[0031] In one embodiment, abnormal states of the battery are classified and identified based on a first expansion force and a second expansion force to determine the abnormal type of the battery. This includes: obtaining the number of battery cycles; classifying and identifying abnormal states of the battery based on the first expansion force, the second expansion force, and the number of battery cycles to determine the abnormal type of the battery. This reduces the identification bias caused by using the same threshold or judgment logic at different cycle stages, enhances the adaptability of abnormal identification to different life stages, and makes abnormal classification more accurate.

[0032] In one embodiment, abnormal battery states are classified and identified based on a first expansion force, a second expansion force, and the battery cycle count to determine the abnormal battery type. This includes: when the battery cycle count is within a first interval, analyzing the abnormal battery state based on the magnitude of the first expansion force to determine the abnormal battery type; and when the battery cycle count is within a second interval, analyzing the abnormal battery state based on the magnitude of the second expansion force to determine the abnormal battery type, where the minimum value of the second interval is greater than the maximum value of the first interval. By dividing the cycle count into intervals and focusing on different expansion force types in different intervals, targeted anomaly detection can be performed for typical risks of the battery at different stages.

[0033] In one embodiment, when the battery's cycle count is within a first range, the abnormal state of the battery is analyzed based on the magnitude of the first expansion force to determine the type of battery abnormality. This includes: if the battery's cycle count is within the first range and the first expansion force is greater than a first preset value, determining the battery abnormality type as abnormal internal gas production; if the battery's cycle count is within the first range and the first expansion force is less than a second preset value, determining the battery abnormality type as pre-tightening force or electrolyte abnormality, where the first preset value is greater than the second preset value. By setting upper and lower thresholds for the first expansion force during the early cycling stage of the battery, a refined distinction is achieved between abnormal gas production, pre-tightening force, or electrolyte abnormalities, improving the accuracy of abnormality detection and the targeted nature of early warning.

[0034] In one embodiment, when the battery's cycle count is within a second range, the abnormal state of the battery is analyzed based on the magnitude of the second expansion force to determine the type of battery abnormality. This includes: if the battery's cycle count is within the second range and the second expansion force is greater than a third preset value, determining the battery abnormality type as electrode thickness abnormality; if the battery's cycle count is within the second range and the first expansion force is less than a fourth preset value, determining the battery abnormality type as insufficient electrode expansion space, where the third preset value is greater than the fourth preset value. By setting upper and lower thresholds for the second expansion force in the later stages of the battery's lifespan, refined identification of electrode thickness abnormalities and insufficient electrode expansion space is achieved, thereby improving the accuracy of mid-to-late-stage failure mechanism localization and the targeted nature of abnormality warnings.

[0035] Secondly, embodiments of this application provide a battery state detection device, including:

[0036] The monitoring module is used to monitor the expansion force during battery operation in order to obtain the measured value of the battery's expansion force.

[0037] The estimation module is used to estimate the expansion force of different types of batteries based on the expansion force measurement value, and obtain the first expansion force and the second expansion force of the battery; the first expansion force is the expansion force generated by the increase of gas pressure inside the battery, and the second expansion force is the expansion force generated by the increase of the thickness of the internal electrode during battery operation.

[0038] The detection module is used to detect and warn of abnormal battery types based on the battery's first and second expansion forces.

[0039] Thirdly, embodiments of this application provide an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the above-described XXXX method.

[0040] Fourthly, embodiments of this application provide a readable storage medium storing a computer program that, when executed by a processor, implements the steps of the battery state detection method described above.

[0041] Fifthly, embodiments of this application provide a computer program product, which includes a computer program that, when run, causes the aforementioned battery state detection method to be executed. Attached Figure Description

[0042] To more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings used in the description of the embodiments of the present invention will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0043] Figure 1 This is a schematic diagram of the structure of a battery management system in one embodiment of the present invention;

[0044] Figure 2 This is a schematic flowchart of a battery state detection method according to an embodiment of the present invention;

[0045] Figure 3 This is another schematic flowchart of the battery state detection method in one embodiment of the present invention;

[0046] Figure 4 yes Figure 2A schematic diagram of the implementation process of step S20;

[0047] Figure 5 This is a schematic diagram illustrating the process of obtaining expansion force ratio data in one embodiment of the present invention;

[0048] Figure 6 yes Figure 5 A schematic diagram of the implementation process of step S01;

[0049] Figure 7 This is a schematic diagram of a battery structure in one embodiment of the present invention;

[0050] Figure 8 This is a curve of the expansion force of the battery under test at different cycles in one embodiment of the present invention;

[0051] Figure 9 This is a graph showing the expansion force curves of the battery casing under different inflation pressures in one embodiment of the present invention.

[0052] Figure 10 yes Figure 2 or Figure 3 A schematic diagram of the implementation process of step S30;

[0053] Figure 11 yes Figure 1 A schematic diagram of a battery status detection device;

[0054] Figure 12 This is a schematic diagram of the structure of an electronic device according to an embodiment of the present invention. Detailed Implementation

[0055] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] It should be understood that, when used in this specification and the appended claims, the term "comprising" indicates the presence of the described features, integrals, steps, operations, elements, and / or components, but does not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components, and / or collections thereof. It should also be understood that, as used in this specification and the appended claims, the term "and / or" refers to any combination of one or more of the associated listed items and all possible combinations, and includes such combinations.

[0057] Furthermore, in the description of this invention and the appended claims, the terms "first," "second," "third," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0058] References to "one embodiment" or "some embodiments" as described in this specification mean that one or more embodiments of the invention include a specific feature, structure, or characteristic described in connection with that embodiment. Therefore, the phrases "in one embodiment," "in some embodiments," "in other embodiments," "in still other embodiments," etc., appearing in different parts of this specification do not necessarily refer to the same embodiment, but rather mean "one or more, but not all, embodiments," unless otherwise specifically emphasized. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless otherwise specifically emphasized.

[0059] It should be understood that the sequence number of each step in the following embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0060] To illustrate the technical solution of the present invention, specific embodiments are described below.

[0061] The battery mentioned in the embodiments of this application can refer to a single battery cell, or it can refer to a single physical module comprising one or more battery cells to provide higher voltage and capacity. For example, the battery mentioned in the embodiments of this application may include battery devices such as battery modules or battery packs. The battery generally includes a housing for encapsulating one or more battery cells, and a pouch cell.

[0062] In this application embodiment, the battery cell may include lithium-ion secondary batteries, lithium-ion primary batteries, lithium-sulfur batteries, sodium-lithium-ion batteries, sodium-ion batteries, or magnesium-ion batteries, etc., and this application embodiment is not limited to these. The battery cell may be cylindrical, flat, cuboid, or other shapes, etc., and this application embodiment is not limited to these. Battery cells are generally divided into three types according to the packaging method: cylindrical battery cells, cuboid / square battery cells, and pouch battery cells, and this is not limited to these.

[0063] As a core component of energy storage and power systems, the performance and safety status of batteries directly determine the reliability and lifespan of the system. Current battery management solutions typically rely on parameters such as voltage, current, and temperature to assess battery status and detect anomalies. However, these parameters are relatively lagging in characterizing battery status, and they often represent the overall performance of the battery, making it difficult to detect potential abnormal states in a timely and accurate manner. This leads to low accuracy in battery status detection, resulting in misjudgments or missed detections of battery anomalies, thus posing battery safety risks.

[0064] For example, parameters such as voltage, current, and temperature are not sensitive enough to changes in the internal structural stress of a battery during use, resulting in response lag and ambiguous judgments in battery anomaly detection, leading to low accuracy. In the early stages of battery anomalies, fluctuations in parameters such as voltage or temperature are small, making it difficult to reflect potential risks in a timely manner. Furthermore, relying solely on overall parameters for state detection cannot distinguish between different types of anomalies within the battery. For instance, gas generation caused by electrolyte decomposition and mechanical expansion due to electrode volume changes often exhibit similar external characteristics under traditional monitoring methods, easily leading to misjudgments or missed detections, thus reducing the accuracy and reliability of battery state monitoring.

[0065] To address the aforementioned issues, this application provides a battery state detection method, apparatus, device, storage medium, and program product. This method monitors the expansion force during battery operation to obtain measured expansion force values. Based on these values, it estimates different types of expansion forces, yielding a first expansion force and a second expansion force. The first expansion force is generated by the increase in internal gas pressure, while the second expansion force is generated by the increase in the thickness of the internal electrode sheets during battery operation. By using the first and second expansion forces, the method detects and provides early warnings for battery anomaly types, improving the accuracy and reliability of anomaly detection. Furthermore, by monitoring the expansion force during battery operation, the expansion force parameters dynamically reflect changes in the battery's structural stress during operation, enabling timely and accurate battery state assessment and monitoring. Furthermore, during the monitoring of battery expansion force measurements, by decomposing the battery expansion force measurements into different types of expansion forces, it is possible to distinguish between the first expansion force generated by the increase in internal gas pressure and the second expansion force generated by the increase in electrode thickness. This provides a more accurate basis for battery anomaly analysis. Based on the first and second expansion forces, battery anomaly types can be identified, detected, and warned. This can clearly identify state anomalies caused by different types of reasons, such as side reactions and electrode expansion and thickening, reducing the possibility of misjudgment or missed detection of battery anomalies. This improves the accuracy and reliability of battery anomaly type detection, thereby reducing the probability of battery failure and safety accidents and ensuring battery safety.

[0066] The battery state detection method provided in this embodiment of the invention can be applied to, for example... Figure 1 The battery management system shown includes a battery and a battery state detection device. The battery is equipped with an expansion force sensor to measure the battery's expansion force, thus obtaining the expansion force measurement value during operation. The battery expansion force sensor communicates with the battery state detection device via a network.

[0067] A battery state monitoring device can monitor the expansion force of a battery during operation using an expansion force sensor to obtain measured values. Then, based on these measurements, the device can estimate different types of expansion forces, yielding a first expansion force and a second expansion force. The first expansion force is generated by the increase in internal gas pressure, while the second expansion force is generated by the increase in the thickness of the internal electrode plates during battery operation. Finally, the device can detect and issue warnings about battery anomalies based on these first and second expansion forces.

[0068] In this embodiment, by monitoring the expansion force during battery operation, the structural stress changes of the battery during operation can be dynamically reflected through the expansion force parameter, thereby achieving timely and accurate battery status assessment and monitoring. Furthermore, during the monitoring of the battery's expansion force measurement value, by decomposing the battery's expansion force measurement value into different types of expansion forces, it is possible to distinguish between the first expansion force generated by the increase in internal gas pressure and the second expansion force generated by the increase in electrode thickness. This provides a more accurate basis for battery anomaly analysis. Based on the first and second expansion forces, battery anomaly types can be identified, detected, and warned. This can clearly identify state anomalies caused by different types of reasons such as side reactions and electrode expansion and thickening, reducing the possibility of misjudgment or missed detection of battery anomalies, improving the accuracy and reliability of battery anomaly type detection, thereby reducing the probability of battery failure and safety accidents, and ensuring battery safety.

[0069] In one embodiment, the battery management system further includes a terminal device. This terminal device sends a status detection command to the battery status detection device to trigger the device to execute the aforementioned battery status detection process and obtain a battery anomaly type detection result. Furthermore, after detecting the battery anomaly type, the battery status detection device can send an anomaly warning message including the anomaly type to the terminal device to provide a battery anomaly warning. The terminal device is also used to receive the anomaly warning message sent by the battery status detection device to promptly alert relevant personnel to abnormal battery conditions, enabling them to be aware of the situation and take appropriate battery control measures.

[0070] In other words, when there is a need for battery status detection, relevant personnel can send a status detection command to the battery status detection device via a terminal device. Upon receiving the command, the battery status detection device controls the expansion force sensor to monitor the battery's expansion force, thereby executing the aforementioned battery status detection process, obtaining and storing the battery's anomaly type. In other embodiments, the battery status detection device can also detect the battery status in real time after the battery starts operating. After obtaining the battery's anomaly type, it sends an anomaly warning message, including the obtained anomaly type, to the relevant personnel's terminal device, enabling them to promptly understand the abnormal battery status and take corresponding measures.

[0071] The battery status detection device can also be a terminal device, which may include, but is not limited to, various personal computers, laptops, smartphones, tablets and portable wearable devices.

[0072] In one embodiment, such as Figure 2 As shown, a battery state detection method is provided, which is applied to... Figure 1Taking the battery status detection device as an example, the following steps are included:

[0073] S10: Monitor the expansion force during battery operation to obtain the battery expansion force measurement value.

[0074] During battery operation, such as charging or discharging, the battery state detection device detects the battery's expansion force using an expansion force sensor to obtain expansion force measurements at different times during battery operation. These expansion force measurements, acquired by the expansion force sensor, characterize the overall expansion force of the battery.

[0075] The expansion force sensor can be installed on at least one of the following: the surface of a battery cell, the end plate (such as the end plate of a battery assembly), the heat insulation pad between battery cells, or the insulating cover. When multiple expansion force sensors are installed on the battery, the maximum value among the expansion force values ​​simultaneously collected by the multiple sensors can be used as the measured expansion force value of the battery.

[0076] S20: Based on the measured expansion force value, estimate the expansion force of different types of batteries to obtain the first expansion force and the second expansion force of the battery.

[0077] After obtaining the measured value of the battery's expansion force, the battery state detection device can estimate the expansion force of different types of batteries based on the measured value, thus obtaining the battery's first expansion force and second expansion force. For example, a pre-calibrated expansion force ratio can be obtained; this ratio is obtained by calibrating the measured expansion force of the battery during actual operation; this ratio can be the proportion of the first or second expansion force relative to the overall expansion force of the battery. Then, by multiplying the measured expansion force value by the pre-calibrated expansion force ratio, the battery's first and second expansion forces can be estimated.

[0078] The first expansion force (i.e., soft expansion force) refers to the expansion force generated when the electrolyte decomposes and undergoes side reactions during battery cycling, leading to the gradual accumulation of gas inside the battery cells, increasing the internal gas pressure, and acting on the surface of the battery cells. In other words, the first expansion force is the expansion force generated by the increase in internal gas pressure of the battery.

[0079] The second expansion force (i.e., hard expansion force) refers to the expansion force acting on the surface (e.g., the large surface area) of the battery cell caused by structural changes such as lattice volume changes, particle fracture, and SEI film thickening during charging and discharging due to lithium insertion / extraction. This increase in electrode thickness results in an increase in the electrode's own thickness. In other words, the second expansion force is the expansion force generated by the increase in the thickness of the internal electrode during battery operation. The large surface area of ​​the battery cell refers to the side of the battery cell corresponding to the electrode winding direction, typically the larger surface area among the multiple surfaces of the battery cell.

[0080] S30: Based on the first and second expansion forces of the battery, perform abnormality detection and early warning for the battery.

[0081] After obtaining the first and second expansion forces of the battery—that is, the first expansion force generated by the increase in internal gas pressure and the second expansion force generated by the increase in thickness due to the charging and discharging of the electrode plates—the battery state detection device can perform anomaly type detection on the battery based on these forces to determine the anomaly type of the current abnormal state and issue an anomaly warning based on this type. This anomaly type indicates the abnormal state of the battery.

[0082] For example, after obtaining the first expansion force and the second expansion force of the battery, it can be determined whether the first expansion force and the second expansion force are greater than the corresponding threshold. If either the first expansion force or the second expansion force is greater than the corresponding threshold, it is determined that an abnormality has been detected in the state of the battery, and further, based on the magnitude of the first expansion force, the second expansion force and the corresponding threshold, the abnormality type of the abnormal state can be analyzed.

[0083] The anomaly type determined based on the first expansion force differs from the anomaly type determined based on the second expansion force. For example, if the first expansion force exceeds the corresponding threshold, the battery anomaly type might be abnormal internal gas production (e.g., excessive internal gas production exceeding the allowable range) or electrolyte anomaly (e.g., insufficient electrolyte filling in the cell). If the first expansion force exceeds the corresponding threshold, the battery anomaly type might be abnormal electrode thickness, such as excessively rapid electrode thickening.

[0084] Different types of anomalies correspond to different potential failure mechanisms and risks. This embodiment classifies and identifies different types of abnormal battery states based on the first expansion force and the second expansion force. By identifying the specific anomaly type, it is possible to distinguish whether the current battery anomaly is caused by an abnormal increase in internal gas pressure (abnormal first expansion force), an abnormal expansion of the electrode structure (abnormal second expansion force), or both. This overcomes the shortcomings of using expansion force measurements to determine anomalies, which can only output the existence of anomalies but cannot explain the specific source of the problem.

[0085] In this embodiment, by monitoring the expansion force during battery operation, the structural stress changes of the battery during operation can be dynamically reflected through the expansion force parameter, thereby achieving timely and accurate battery status assessment and monitoring. During the monitoring of the battery's expansion force measurement, different types of expansion force are decomposed to distinguish the first expansion force generated by the increase in internal gas pressure. This provides a more accurate basis for battery anomaly analysis. Furthermore, based on the first and second expansion forces, battery anomaly types can be identified, detected, and warned. This clarifies the state anomalies caused by different types of reasons, such as side reactions and electrode expansion and thickening, reducing the possibility of misjudgments or omissions in battery anomaly detection, improving the accuracy and reliability of battery anomaly type detection, thereby reducing the probability of battery failure and safety accidents, and ensuring battery safety.

[0086] In one embodiment, such as Figure 3 As shown, Figure 2 In step S20, which involves estimating the expansion forces of different types of batteries based on the measured expansion force values ​​to obtain the first and second expansion forces of the battery, the specific steps include the following:

[0087] S201: If the battery condition is determined to be abnormal based on the expansion force measurement value, the expansion force of different types of batteries is estimated based on the expansion force measurement value to obtain the first expansion force and the second expansion force of the battery.

[0088] The battery state monitoring device monitors the expansion force of the battery during operation to obtain the measured value of the expansion force. After obtaining the measured value, the device can first determine whether there is any abnormality in the battery's state. If an abnormality is determined based on the measured value, the device estimates different types of expansion forces to obtain the first and second expansion forces. Then, based on the first and second expansion forces, the device detects and issues warnings regarding the type of battery abnormality.

[0089] The method of determining battery anomalies based on expansion force measurements includes: determining an anomaly when the expansion force measurement meets preset anomaly conditions. For example, if the expansion force measurement is greater than the calibrated expansion force threshold, the rate of change of the expansion force is greater than a preset rate of change, and the duration is greater than a preset duration, then the expansion force measurement meets the preset anomaly conditions. By judging battery anomalies through three dimensions—expansion force measurement, rate of change, and duration—the accuracy of battery state detection is improved.

[0090] In other embodiments, the expansion force measurement value may be determined to meet a preset abnormal condition if the measured expansion force value is greater than the calibrated expansion force threshold and the duration is greater than a preset duration. Alternatively, the expansion force measurement value may be determined to meet a preset abnormal condition if the rate of change of the expansion force measurement is greater than a preset rate of change and the duration is greater than a preset duration.

[0091] In this embodiment, the expansion force during battery operation is monitored. After obtaining the measured expansion force value, it can be determined whether the battery state is abnormal based on the expansion force measurement value. If the battery state is determined to be abnormal based on the expansion force measurement value, different types of expansion forces of the battery are estimated based on the expansion force measurement value to obtain the first expansion force and the second expansion force of the battery. Therefore, the battery abnormality type detection and early warning are performed based on the first expansion force and the second expansion force. By adding an abnormal state judgment step before the expansion force type decomposition, and estimating different types of expansion forces only when an abnormal state of the battery is determined, on the one hand, abnormality judgment can be quickly made based on the actual expansion force value, and on the other hand, unnecessary data processing under normal operating conditions is reduced, thereby improving the overall detection efficiency and reducing the consumption of computing resources and system energy. On the other hand, anomaly detection is first performed by measuring the expansion force to ensure that subsequent expansion force decomposition of different types is only performed on batteries with safety risks. This forms a step-by-step detection mechanism of anomaly detection → type decomposition → anomaly warning. This can quickly check the overall state of the battery, reduce misjudgments caused by anomaly detection based on a single expansion force, and further clarify the source and type of abnormal state, thus improving the accuracy and relevance of anomaly detection results.

[0092] In one embodiment, such as Figure 4 As shown, the step "estimate the expansion force of different types of batteries based on the expansion force measurement value to obtain the first expansion force and the second expansion force of the battery" mentioned in the foregoing embodiment specifically includes the following steps:

[0093] S21: Based on the number of battery cycles, determine the target expansion force ratio of the battery from the pre-calibrated expansion force ratio data.

[0094] The expansion force ratio data is obtained by calibration based on actual battery test data. The actual battery test data determines the first and second expansion forces of the battery during operation at different cycle numbers, and then determines the ratio of the first and second expansion forces of the stored battery at different cycle numbers. That is, this expansion force ratio data includes the ratio of different types of expansion forces corresponding to batteries at different cycle numbers during operation.

[0095] That is, each cycle number or each cycle number interval in the expansion force ratio data corresponds to a set of expansion force ratio values, which includes the ratio value of the first expansion force and the ratio value of the second expansion force. In other embodiments, each cycle number or each cycle number interval in the expansion force ratio data may also correspond to a specified expansion force ratio value, which may be the ratio value of the first expansion force or the ratio value of the second expansion force.

[0096] After obtaining the battery's expansion force measurement value, or after determining that the battery's state is abnormal based on the expansion force measurement value, the battery state detection device can obtain the current number of cycles of the battery and match the current number of cycles of the battery with the number of cycles in the pre-calibrated expansion force ratio data. The expansion force ratio value corresponding to the matched number of cycles is determined as the target expansion force ratio of the battery.

[0097] The battery cycle count refers to the number of times the battery has undergone a complete charge and discharge process. It is calculated as follows: when the battery has accumulated 100% of its power consumption after one or more charge or discharge cycles, it is considered to have completed one cycle, which means the cycle count is increased by 1.

[0098] S22: Based on the measured expansion force value and the target expansion force ratio, the expansion force of different types of batteries is estimated to obtain the first expansion force and the second expansion force of the battery.

[0099] After determining the target expansion force ratio of the battery, the battery state detection device can estimate the expansion force of different types of batteries based on the expansion force measurement value and the target expansion force ratio, and obtain the first expansion force and the second expansion force of the battery.

[0100] For example, the target expansion force percentage may include a percentage value of a first expansion force and / or a percentage value of a second expansion force. When the target expansion force percentage includes a percentage value of the first expansion force, the battery state detection device can multiply the measured expansion force value by the percentage value of the first expansion force to obtain the first expansion force of the battery, and subtract the first expansion force from the measured expansion force value to obtain the second expansion force of the battery. When the target expansion force percentage includes a percentage value of the second expansion force, the battery state detection device can multiply the measured expansion force value by the percentage value of the second expansion force to obtain the second expansion force of the battery, and subtract the second expansion force from the measured expansion force value to obtain the first expansion force of the battery.

[0101] In this embodiment, the expansion force ratio data comes from the measured expansion force of the battery at different cycle numbers. After calibration, standardized reference data is formed. By matching the real-time measured expansion force with the pre-calibrated ratio data, the random errors caused by single measurement and prediction can be avoided. Based on the historical large sample pattern, stable and reliable expansion force decomposition is achieved, which improves the accuracy of the first expansion force and the second expansion force.

[0102] Furthermore, the internal aging mechanism and expansion performance of batteries differ significantly at different cycle counts: electrode volume expansion is more pronounced in the early cycle stage, while the proportion of gas generated by side reactions gradually increases in the middle and later cycle stages. If the impact of cycle count is not considered and the overall expansion force is directly decomposed, it can easily lead to inaccurate determination of the expansion force type. This solution introduces the key factor of cycle count, enabling the expansion force decomposition process to dynamically adapt to the battery's usage stage, thereby improving the accuracy of the prediction of the first and second expansion forces throughout the entire lifespan.

[0103] In one embodiment, step S21, which involves determining the target expansion force ratio of the battery based on the battery's cycle count from the expansion force ratio data, specifically includes the following steps:

[0104] S211: Obtain pre-calibrated expansion force ratio data, which includes the ratio of different types of expansion force corresponding to batteries with different cycle counts and under different operating conditions.

[0105] After obtaining the battery's expansion force measurement value, or after determining that the battery's state is abnormal based on the expansion force measurement value, the battery state detection device can acquire the battery's current cycle count and operating state, and obtain pre-calibrated expansion force percentage data. The operating state includes charging and discharging states.

[0106] The expansion force percentage data includes the percentage of different types of expansion force corresponding to batteries with different cycle counts under different operating states. That is, the expansion force percentage data includes the percentage of different types of expansion force of batteries with different cycle counts under charging conditions, and the percentage of different types of expansion force of batteries with different cycle counts under charging conditions. The percentage of different types of expansion force includes the percentage of the first expansion force and the percentage of the second expansion force.

[0107] Among them, each cycle number or each cycle number range in the expansion force ratio data corresponds to a set of expansion force ratio values. This set of expansion force ratio values ​​includes the ratio values ​​of the first expansion force and the second expansion force corresponding to the charging state, as well as the ratio values ​​of the first expansion force and the second expansion force corresponding to the discharging state.

[0108] S212: Match the current operating state and cycle count of the battery with the data in the expansion force ratio data, and determine the ratio of different types of expansion force as the target expansion force ratio of the battery.

[0109] After acquiring the pre-calibrated expansion force ratio data, the battery state detection device can match the battery's current operating state and cycle count with the operating state and cycle count in the expansion force ratio data. The expansion force ratio value corresponding to the matched operating state and cycle count is determined as the battery's target expansion force ratio. This target expansion force ratio may include the ratio value of a first expansion force and / or the ratio value of a second expansion force.

[0110] It's important to understand that the contributions of internal electrode volume expansion and gas generation differ significantly during charging and discharging. For example, side reactions are more active during charging, potentially increasing the proportion of the first expansion force, while the second expansion force, caused by electrode volume changes, contributes more during discharging. Abnormal battery behavior is often related to its actual operating conditions; for instance, overcharging is more likely to cause gaseous side reactions, while over-discharging is more likely to damage the electrodes.

[0111] In this embodiment, by combining the battery cycle count with the operating state, the proportions of the first and second expansion forces under different battery operating conditions can be more accurately distinguished. The differences in proportions caused by ignoring differences in operating conditions are briefly explained, thus improving the accuracy of the expansion force proportion data. Furthermore, based on the actual battery cycle count and operating state, a more accurate target expansion force proportion can be determined, making the decomposition of soft and hard expansion forces (i.e., the first and second expansion forces) more refined and more closely aligned with actual operating conditions. This significantly improves the accuracy and targeting of battery anomaly detection and early warning.

[0112] In one embodiment, before estimating the expansion force of different types of batteries based on the expansion force measurement value, pre-calibrated expansion force ratio data can be obtained to determine the target expansion force ratio of the battery based on the battery cycle number in the pre-calibrated expansion force ratio data, and then the expansion force of different types of batteries can be estimated based on the expansion force measurement value and the target expansion force ratio.

[0113] Among them, such as Figure 5 As shown, the expansion force ratio data is obtained by calibration in the following way:

[0114] S01: Using the simulated expansion force data of the battery casing as the expansion force benchmark, the measured expansion force data of the battery under test at different cycle numbers are classified to obtain the first expansion force and the second expansion force of the battery under test at different cycle numbers.

[0115] The battery state detection device can first acquire the measured data of the expansion force of the battery under test at different cycles, as well as the simulated data of the expansion force of the battery casing.

[0116] The measured expansion force data was obtained by conducting cycle tests on the battery under test for different numbers of cycles. The battery under test was a real, complete battery including the casing, electrode assembly (i.e., the core), and electrolyte. By performing charge and discharge tests on the battery under test for each cycle and measuring the expansion force during the test, the measured expansion force data of the battery under test at different cycle numbers can be obtained.

[0117] The battery casing refers to the structure of the battery under test after removing the internal electrode components and electrolyte. The expansion force simulation data is obtained by measuring the battery casing under simulated battery operating conditions. The battery casing is simulated under different simulated operating conditions using a controlled testing device to obtain the expansion force of the battery casing under different simulated conditions, thus obtaining the battery casing's expansion force simulation data.

[0118] For example, a testing device can be controlled to perform inflation tests on the battery casing at different pressures. By varying the inflation pressure, the effect of internal gas on the battery casing during actual battery operation can be simulated, and the expansion force of the battery casing during different inflation processes can be tested. This yields simulated expansion force data of the battery casing under different simulated operating conditions. By measuring the actual expansion force values ​​during the simulation process, the accuracy of the expansion force simulation data can be improved. In other embodiments, battery operating condition simulation can also be performed in other ways. For example, a simulation model can be established based on the battery, and then the battery operating conditions can be simulated based on the simulation model to obtain simulated expansion force data of the battery casing under different simulated operating conditions.

[0119] Since the battery casing does not include the electrodes, the simulated expansion force data obtained after simulating battery operation conditions may not include the expansion force caused by the increased thickness of the electrodes during battery operation (i.e., the second expansion force). In other words, the simulated expansion force data only represents the first expansion force (i.e., the soft expansion force) caused by the increase in internal gas. Therefore,

[0120] After acquiring the measured expansion force data of the battery under test at different cycle counts and the simulated expansion force data of the battery casing, the battery state detection device can use the simulated expansion force data of the battery casing as the expansion force benchmark to classify the expansion force of the battery under test at different cycle counts and obtain the first expansion force and the second expansion force of the battery under test at different cycle counts.

[0121] For example, the expansion force simulation data of the battery casing includes the expansion force of the battery casing under simulated operating conditions. The simulated operating conditions in the expansion force simulation data can be correlated with the number of cycles. Then, the expansion force of the battery casing under different simulated operating conditions can be directly used as the first expansion force under different number of cycles. By subtracting the expansion force under the corresponding simulated operating conditions from the measured expansion force data of the battery under test under different number of cycles, the second expansion force of the battery under test under different number of cycles can be obtained.

[0122] S02: Based on the first expansion force and the second expansion force of the battery under test at different cycles, determine the ratio of the first expansion force and the second expansion force at different cycles to generate expansion force ratio data.

[0123] After obtaining the first and second expansion forces of the battery under test at different cycle counts, the battery state detection device can determine the proportion of the first and second expansion forces at different cycle counts to generate expansion force proportion data. That is, for each cycle count, the ratio of the first expansion force to the total expansion force (i.e., the sum of the first and second expansion forces) can be determined to obtain the proportion of the first expansion force, and the ratio of the second expansion force to the total expansion force can be determined to obtain the proportion of the second expansion force. Then, the proportions of the first expansion force at different cycle counts and the proportion of the second expansion force at the same cycle count are output as expansion force proportion data.

[0124] In this embodiment, by simulating the operating conditions of the empty battery casing, the effect of internal gas pressure on the casing can be effectively simulated, obtaining simulated data on the expansion force generated purely by the interaction between the casing and internal gas pressure. Then, actual operating conditions are measured on a real battery (the battery under test) to obtain measured data on the overall battery expansion force caused by the combined effects of internal gas and electrode thickness. This simulated expansion force data is then used as a benchmark and compared and classified with measured expansion force data from a real battery at different cycle counts. This allows for accurate separation of the first expansion force caused by gas pressure and the second expansion force caused by electrode volume changes, achieving a reliable decomposition of the first and second expansion forces. Furthermore, the first and second expansion forces corresponding to different cycle counts are calibrated to obtain their respective proportions, forming expansion force proportion data. This data accurately reflects the evolution of the battery's expansion force contribution from electrode expansion and gas pressure throughout its entire lifespan, improving the accuracy of the expansion force proportion data and providing accurate data for subsequent battery expansion force decomposition and anomaly detection.

[0125] In one embodiment, such as Figure 6As shown, in step S01, the expansion force is classified based on the simulated expansion force data of the battery casing at different cycle counts to obtain the first and second expansion forces of the battery at different cycle counts. This specifically includes the following steps:

[0126] S011: Obtain the measured data of the expansion force of the battery under test at different cycles.

[0127] The battery state monitoring device can acquire measured data of the expansion force of the battery under test at different cycle counts. This measured data includes the large-area expansion force and the end-face expansion force of the battery under test at the corresponding cycle count. The large-area expansion force is the expansion force on the side of the battery cell corresponding to the electrode winding direction (i.e., the large surface of the battery); the end-face expansion force is the expansion force on the battery end face perpendicular to the electrode winding direction, that is, the expansion force on the battery end face perpendicular to the large surface of the battery.

[0128] In other words, the battery under test can be charged and discharged at different cycles to test the large-area expansion force and end-face expansion force of the battery during the current operation process, thereby obtaining the large-area expansion force and end-face expansion force of the battery under test at different cycles, that is, obtaining the measured data of the expansion force of the battery under test at different cycles.

[0129] Among them, such as Figure 7 As shown, the large surface of the battery under test is the side surface of the battery corresponding to the electrode winding direction, and the end surface of the battery under test is a plane perpendicular to the large surface of the battery. The end surface includes the first end surface where the battery end cap is located, and the bottom surface corresponding to the first end surface, i.e., the second end surface.

[0130] The large-area expansion force can be collected by an expansion force sensor installed on the large surface of the battery under test; the end-face expansion force can be collected by an expansion force sensor installed on the end face of the battery under test. However, considering that the first end face has a corresponding interface structure, the sensor placement is limited, and the presence of the interface structure may cause expansion force deviation, an expansion force sensor can be installed on the second end face of the battery bottom, opposite the battery port, to measure the end-face expansion force of the battery under test.

[0131] Taking a pre-assembled battery as an example, the surface expansion force and end-face expansion force (such as bottom expansion force) of the battery under different cycles were tested. The obtained measured expansion force data can be shown as follows: Figure 8 As shown. Figure 8 The curves of the large-area expansion force and end-face expansion force of the battery under test at different cycle numbers are shown. Figure 8 The horizontal axis represents the number of cycles, and the vertical axis represents the expansion force (in N).

[0132] In other embodiments, the measured expansion force data at different cycle counts include the large-area expansion force and end-face expansion force of the battery under test corresponding to different operating states at different cycle counts; the battery's operating states include charging state and discharging state. That is, the measured expansion force data includes the large-area expansion force and end-face expansion force of the battery under test corresponding to the charging state at different cycle counts, and the large-area expansion force and end-face expansion force of the battery under test corresponding to the discharging state at the corresponding cycle counts.

[0133] S012: Obtain simulation data of the expansion force of the battery casing.

[0134] Simultaneously, the battery state detection device can acquire simulated data of the battery casing's expansion force. This simulated expansion force data includes the large-area expansion force and end-face expansion force of the battery casing under different inflation pressures. The process of acquiring the simulated expansion force data of the battery casing is as follows: multiple inflation pressures can be pre-calibrated, the testing device is controlled to inflate the battery casing to the calibrated inflation pressure, and the large-area expansion force and end-face expansion force of the battery casing under that inflation pressure are measured, thereby obtaining the large-area expansion force and end-face expansion force of the battery casing under different inflation pressures, that is, obtaining the simulated expansion force data of the battery casing.

[0135] Among them, with regard to Figure 8 Taking the battery casing of the battery under test as an example, the large-area expansion force and end-face expansion force (such as bottom expansion force) of the battery casing under different inflation pressures were tested. The obtained expansion force simulation data can be shown as follows: Figure 9 As shown. Figure 9 The curves of the large-area expansion force and end-face expansion force of the battery casing under different inflation pressures are shown. Figure 9 The horizontal axis represents the inflation pressure (in kPa), and the vertical axis represents the expansion force (in N).

[0136] S013: Align the end-face expansion force in the measured expansion force data with the end-face expansion force in the expansion force simulation data, and then, based on the large-area expansion force in the expansion force simulation data, decompose the large-area expansion force in the measured expansion force data to obtain the first expansion force and the second expansion force of the battery under test at different cycle numbers.

[0137] During actual battery operation, the expansion of the battery electrodes mainly affects the large-area direction, while the internal gas pressure is reflected in both the large-area and end-face directions. That is, the end-face expansion force is primarily influenced by gas pressure, with minimal interference from electrode expansion, while the large-area expansion force is affected by both electrode expansion and internal gas pressure. By simulating battery operation through the battery casing, the measured end-face and large-area expansion forces are only affected by the internal gas pressure. By aligning the measured expansion force data with the simulated expansion force data, and then decomposing the measured large-area expansion force based on the simulated data, the first and second expansion forces of the tested battery at different cycle numbers can be obtained—a simple and convenient method.

[0138] Specifically, the battery state detection device can find end-face expansion forces with the same value in the simulated expansion force data of the battery casing and the measured expansion force data of the battery under test. Based on each end-face expansion force, it determines the large-area expansion force (and inflation pressure) of the battery casing corresponding to that end-face expansion force, as well as the large-area expansion force and cycle number of the battery under test corresponding to that end-face expansion force, and forms an expansion force data group. By traversing all the end-face expansion forces, multiple expansion force data groups are obtained.

[0139] Then, for each expansion force data set, the end-face expansion force at the specified number of cycles within that set is taken as the first expansion force of the battery under test at that number of cycles. Subtracting this first expansion force from the large-area expansion force of the battery under test yields the second expansion force at that number of cycles. This provides the first and second expansion forces of the battery under test at that number of cycles (and the corresponding inflation pressure). By iterating through all expansion force data sets, the first and second expansion forces of the battery under test at different number of cycles are obtained, along with the inflation pressure at different number of cycles. Furthermore, based on the first and second expansion forces of the battery under test at different number of cycles, the percentage values ​​of the first and second expansion forces at different number of cycles are determined, thus obtaining the expansion force percentage data.

[0140] Among them, with Figure 8 The measured data of the expansion force of the battery under test, and Figure 9 Taking the expansion force simulation data of the battery casing as an example, the end face expansion force in the measured expansion force data and the expansion force simulation data is aligned. The resulting multiple expansion force data groups and the ratio of the first expansion force and the second expansion force can be shown in Table 1 below.

[0141] Table 1

[0142]

[0143] In this embodiment, the measured data of the expansion force of the battery under test, the simulated data of the expansion force of the battery casing, and the determined second expansion force and the proportion of each expansion force are all exemplary descriptions. In other embodiments, the corresponding data of the battery under test and the corresponding battery casing with different structural designs can also be other data, which will not be elaborated here.

[0144] In this embodiment, by measuring both large-area expansion force and end-face expansion force during the testing process, and using the end-face expansion force from both the measured and simulated expansion force data as an alignment benchmark for expansion force classification, the overall pressure effect can be more accurately eliminated during expansion force decomposition, resulting in more refined expansion force breakdown. Furthermore, using the end-face expansion force as the alignment benchmark ensures that expansion forces from different sources are decomposed within the same reference frame, thereby reducing deviations caused by differences in actual battery structures. This makes the identification of different expansion forces more consistent with the actual battery structure mechanism, improving the accuracy and stability of expansion force breakdown.

[0145] Because the battery may be in different operating states within the same number of cycles, it may be in a charging state or a discharging state. During the charging or discharging process, the discharge and charging processes of the electrodes are different, and the changes in battery expansion force are not the same, which may lead to changes in the proportion of the first expansion force or the second expansion force.

[0146] Therefore, to further improve the accuracy of the expansion force ratio data, in other embodiments, measured expansion force data of the battery under test at different cycle counts can be obtained. This measured expansion force data at different cycle counts includes measured expansion force data corresponding to different operating states at different cycle counts. Then, using the simulated expansion force data of the battery casing as the expansion force benchmark, the measured expansion force data of the battery under test at different cycle counts is classified to obtain the first expansion force and the second expansion force corresponding to different operating states of the battery under test at different cycle counts. Furthermore, based on the first and second expansion forces corresponding to different operating states of the battery under test at different cycle counts, the ratio values ​​of the first and second expansion forces corresponding to different operating states at each cycle count are determined, thus outputting the expansion force ratio data. The specific determination process is described above and will not be repeated here. It can be seen that the expansion force ratio data can include the ratio value of the first expansion force corresponding to different operating states at different cycle counts, and the ratio value of the second expansion force corresponding to different operating states at different cycle counts. Subsequently, based on the battery's cycle count and actual operating conditions, a more accurate target expansion force ratio can be determined, thereby improving the accuracy of the target expansion force ratio and thus enhancing the accuracy of the estimated first and second expansion forces.

[0147] In one embodiment, step S02, which involves determining the ratio of the first expansion force and the second expansion force at different cycle counts based on the first expansion force and the second expansion force of the battery under test at different cycle counts, to generate expansion force ratio data, specifically includes the following steps:

[0148] S021: Based on the first expansion force and the second expansion force of the battery under test at different cycles, determine the proportion of the first expansion force and the proportion of the second expansion force at different cycles.

[0149] For example, for the first and second expansion forces under a certain number of cycles, the sum of the first and second expansion forces can be determined as the total expansion force under that number of cycles; then, the ratio of the first expansion force to the total expansion force is determined to obtain the proportion of the first expansion force under that number of cycles, and the ratio of the second expansion force to the total expansion force is determined to obtain the proportion of the second expansion force under that number of cycles; by iterating through all the number of cycles, the proportions of the first and second expansion forces under different number of cycles can be obtained.

[0150] S022: Verify the performance qualification of the battery under test based on the proportion of the first expansion force and the proportion of the second expansion force under different cycle numbers.

[0151] After determining the proportions of the first and second expansion forces at different cycle counts, the performance of the battery under test can be verified based on these proportions to determine whether the electrodes, electrolyte, casing, battery assembly preload, and casing group margin of the battery under test meet the corresponding performance requirements. The casing group margin refers to the gap between the electrode assembly and the casing during battery assembly.

[0152] Throughout the battery's entire lifespan, the proportions of the first and second expansion forces differ across different cycle count ranges. The performance qualification of the battery under test can be directly verified based on the proportions of the first and second expansion forces, to determine whether the current battery meets the requirements.

[0153] For example, the battery's lifespan can be divided into intervals based on the number of cycles, into a first interval (e.g., 0-3000 cycles) and a second interval (i.e., the interval greater than 3000 cycles). The maximum value in the first interval is less than the minimum value in the second interval.

[0154] It's important to understand that to ensure battery performance and safety, when a qualified battery's cycle life is in the first range (e.g., 0-3000 cycles), the electrolyte content is relatively high, and the amount of gas generated inside the battery is also relatively large. Therefore, in this first range, the proportion of the battery's primary expansion force is relatively high, approximately 40%-50%. Meanwhile, the performance of the internal electrode plates is excellent, and the increase in thickness is not significant, making abnormalities in the secondary expansion force (i.e., hard expansion force) less likely. When the battery's cycle life is in the second range (e.g., greater than 3000 cycles), the electrolyte content is low or may even be completely depleted. The rate of gas generation inside the battery decreases significantly, resulting in a lower primary expansion force. Meanwhile, the internal electrode plates continue to thicken, causing the proportion of the secondary expansion force to increase, potentially reaching 65%-70% towards the end of the battery's lifespan.

[0155] Therefore, if the number of cycles tested on the battery under test falls within the first range, and the percentage of the first expansion force falls within the first percentage range (e.g., 40%-50%), the battery under test can be determined to have passed the performance qualification verification. If the number of cycles tested on the battery under test falls within the second range, and the percentage of the second expansion force falls within the second percentage range (e.g., 40%-50%), the battery under test can be determined to have passed the performance qualification verification.

[0156] If the number of cycles tested on the battery is within the first range, and the percentage of the first expansion force is greater than the maximum value of the first range, it indicates that the internal gas production of the battery is too high. This may be due to excessively vigorous internal side reactions causing abnormal internal gas production. The performance qualification verification result of the battery is determined to be unqualified, and it is recommended to optimize the electrolyte and electrode formulation to reduce the occurrence of internal side reactions, thereby optimizing the structure and performance of the battery. If the percentage of the first expansion force is less than the minimum value of the first range, it indicates that the internal gas production of the battery is insufficient or too low. This may be due to excessive pre-tightening force in the battery's internal structure assembly or insufficient electrolyte. The performance qualification verification result of the battery is determined to be unqualified, and it is recommended to optimize the pre-tightening force of the structural clamps and the electrolyte to increase the pre-tightening force and / or increase the electrolyte injection volume.

[0157] If the percentage of the second expansion force is greater than the maximum value of the second percentage range when the number of cycles tested by the battery is within the second range, it indicates that the electrode thickness inside the battery is too rapid, which may lead to electrode cracking or even breakage, potentially causing fire or explosion. In this case, the performance qualification verification result of the battery under test is determined to be unqualified, and it is suggested to optimize the group margin of the electrode assembly of the battery under test, such as reducing the number of winding layers of the electrode assembly to reduce electrode cracking or even breakage caused by insufficient margin due to excessively rapid electrode thickness inside the battery, thereby optimizing the structure and performance of the battery under test. If the percentage of the second expansion force is less than the minimum value of the second percentage range, it indicates that the electrode expansion space is insufficient, and the group margin of the electrode assembly inside the battery may be too low. In this case, the performance qualification verification result of the battery under test is determined to be unqualified, and it is suggested to optimize the group margin of the electrode assembly when it is installed in the casing, such as increasing the group margin when the electrode assembly is installed in the casing to increase the expansion space of the electrode assembly, thereby optimizing the structure and performance of the battery under test.

[0158] S023: If the performance qualification verification result of the battery under test is qualified, output the proportion of the first expansion force and the proportion of the second expansion force of the battery under test under different cycles as expansion force proportion data.

[0159] If the performance qualification verification result of the battery under test is qualified, the battery state detection device can output the proportion of the first expansion force and the proportion of the second expansion force of the battery under test under different cycles as expansion force proportion data.

[0160] In this embodiment, based on the first and second expansion forces of the battery under test at different cycle counts, the proportion of the first expansion force and the proportion of the second expansion force at different cycle counts are determined. Based on these proportions, the battery under test undergoes performance qualification verification. If the performance qualification verification result is satisfactory, the proportions of the first and second expansion forces at different cycle counts are output as expansion force proportion data. By performing performance qualification verification before outputting the expansion force proportion data, it is ensured that the data used for calibration comes only from batteries with normal performance and meeting design requirements. This reduces the deviation in expansion force proportion caused by using data from batteries with defects or early anomalies, ensuring the accuracy and reliability of the calibration data, thereby significantly improving the accuracy of the expansion force proportion data in lifetime prediction, anomaly detection, and quality control.

[0161] In one embodiment, the measured expansion force data and the end-face expansion force in the simulated expansion force data are aligned. Based on the large-area expansion force in the simulated expansion force data, the large-area expansion force in the measured expansion force data is decomposed to obtain the first and second expansion forces of the battery under test at different cycle numbers, as well as the charging pressure at different cycle numbers. Correspondingly, in step S022, that is, based on the proportion of the first expansion force and the proportion of the second expansion force at different cycle numbers, the performance qualification verification of the battery under test is performed, which also includes the following steps:

[0162] The performance qualification of the battery under test was verified based on the proportion of the first expansion force and the proportion of the second expansion force under different cycles, as well as the inflation pressure under different cycles.

[0163] The process of verifying the performance of the battery under test by determining the proportion of the first expansion force and the proportion of the second expansion force under different cycles is described above, and the specific process will not be repeated here.

[0164] The performance qualification verification of the battery under test is performed based on the charging pressure at different cycle counts. This includes determining the maximum target pressure value that the battery under test may reach during operation, based on the charging pressure at different cycle counts. This maximum target pressure value can be the charging pressure of the last cycle among different cycle counts, or the maximum value of the charging pressure of the last few cycles among different cycle counts. Then, the maximum simulated air pressure value of the battery under test is obtained through structural simulation. If the maximum simulated air pressure value of the battery under test obtained from the simulation is less than or equal to the maximum target pressure value, it indicates that the current structural design strength of the battery under test is insufficient and may not be able to withstand the maximum target pressure value, resulting in issues such as explosion-proof valve leakage and weld cracking. In this case, the performance qualification verification of the battery under test is determined to be unqualified, indicating that the structural strength of the battery under test is insufficient. The structure of the battery under test can be redesigned to ensure that the internal air pressure value that the structural strength of the battery under test can withstand is greater than the maximum target pressure value.

[0165] In this embodiment, by aligning the measured expansion force data with the end-face expansion force in the simulated expansion force data, expansion force classification is performed. This allows for the acquisition of not only the first and second expansion forces at different cycle counts, but also the inflation pressure at different cycle counts, as shown in Table 1 above. During the battery design phase, this method can be used to quickly obtain the inflation pressure of the battery under test at different cycle counts. Based on the inflation pressure of the battery under test at different cycle counts, performance qualification verification based on internal air pressure can be performed, thereby optimizing the structural design of the battery under test based on the verification results.

[0166] It's important to understand that during the battery design phase, to ensure battery structural strength and thus lifespan, it's necessary to obtain the internal pressure of the battery under test during operation. This internal pressure is then used for battery life prediction and structural optimization. However, the internal pressure of a battery cannot be directly measured. In some embodiments, the battery under test can be modified to facilitate pressure measurement. For example, a pressure sensor can be connected to the electrolyte inlet of an unsealed battery under test, and the unsealed battery can be controlled to collect its internal pressure via the sensor. However, in this approach, the battery under test is unsealed, and modifications to its structure are required for testing. This results in a significant difference between the battery testing conditions and the actual operating conditions, leading to a large discrepancy between the collected pressure values ​​and the battery's true pressure. Consequently, the obtained internal pressure values ​​are inaccurate, making it difficult to effectively determine battery structural optimization. Furthermore, in this internal pressure test, the unsealed battery under test may experience leakage, and there are multiple joints between the battery and the pressure sensor. The long-term reliability of these joints cannot be guaranteed, leading to test failure and inaccurate internal pressure values. In addition, this type of test solution requires a harsh testing environment (high-temperature testing), extensive preparation, and a long testing cycle (e.g., an average duration of >1 year). The extremely harsh environment makes it impossible to obtain timely and accurate internal pressure values ​​for the battery under test, severely impacting battery development efficiency and effectiveness.

[0167] In this embodiment, by aligning the measured expansion force data with the end-face expansion force in the simulated expansion force data for expansion force classification, not only can the first and second expansion forces at different cycle counts be obtained, but also the inflation pressure at different cycle counts. This effectively improves the reliability and accuracy of the pressure test, resulting in a more accurate product life prediction model and more precise life prediction, thus effectively improving the reliability of the product's lifespan. Secondly, by using the inflation pressure at different cycle counts, the maximum pressure value that the battery under test can achieve under actual operating conditions (i.e., the maximum target pressure value) can be obtained. This guides the structural strength design of the battery product to exceed the determined maximum pressure value, ensuring that the explosion-proof valve does not leak, welds do not crack, etc., thereby improving the efficiency and effectiveness of battery development and ensuring battery operational safety.

[0168] In one embodiment, such as Figure 10 As shown, step S30, which involves detecting and issuing an alarm for abnormal battery types based on the first and second expansion forces, specifically includes the following steps:

[0169] S31: Based on the first and second expansion forces of the battery, classify and identify the abnormal state of the battery to determine the abnormal type of the battery.

[0170] After determining the first and second expansion forces of the battery, the battery state detection device can classify and identify the abnormal state of the battery based on these forces to determine the type of abnormality. This type of abnormality indicates the specific abnormal state of the battery.

[0171] For example, corresponding expansion force ranges can be set for the first expansion force and the second expansion force respectively. Each expansion force range corresponds to an abnormality type. Then, the expansion force range in which the first expansion force and the second expansion force are located can be determined, thereby identifying the abnormality type corresponding to the expansion force range as the abnormality type of the battery. This is simple and convenient.

[0172] In other embodiments, the first and second expansion forces of the battery at different times can be obtained to generate first and second expansion force curves. Key feature parameters of the two curves, such as rise rate, fluctuation amplitude, and peak time point, can then be extracted. The extracted feature parameters are matched with pre-established anomaly type data to identify the category of the battery's abnormal state, thus determining the battery's anomaly type, such as internal gas generation anomaly, electrode expansion anomaly (thickness anomaly), or insufficient expansion space. Furthermore, the identified anomaly type can be further confirmed by combining the battery's cycle count, charge / discharge rate, temperature, and other operating conditions. The anomaly type confirmed through this secondary confirmation is then determined as the current anomaly type of the battery, improving the accuracy of battery anomaly type identification.

[0173] S32: Generate abnormal warning information for the battery based on the abnormal type of the battery. The abnormal warning information is used to provide early warning of abnormal battery conditions.

[0174] After determining the type of battery malfunction, the battery status detection device can generate an malfunction warning message containing the malfunction type, which is used to warn of abnormal battery conditions.

[0175] For example, a battery status detection device can determine the abnormal risk level of the current abnormal state based on the abnormal type of the battery, and output the abnormal type, abnormal risk level, and the corresponding expansion force measurement value, first expansion force and second expansion force when the abnormal battery status is detected as abnormal warning information for the battery, so that relevant personnel can take corresponding measures in a timely manner based on the information in the abnormal warning information.

[0176] In other embodiments, the battery state detection device can also determine the possible causes of the abnormality type of the battery, as well as the countermeasures to resolve or address the abnormality of the battery state of that type, and output the abnormality type, abnormality risk level, abnormality cause, and corresponding countermeasures, as well as the expansion force measurement value, first expansion force and second expansion force corresponding to the detection of the abnormality of the battery state, as abnormality warning information for the battery, so that relevant personnel can promptly confirm the battery abnormality and corresponding measures based on the information in the abnormality warning information.

[0177] Upon receiving a confirmation instruction from relevant personnel, the battery status detection device can immediately execute the corresponding measures. If no response information is received from relevant personnel within a preset time period, that is, no confirmation instruction or cancellation instruction is received from relevant personnel, the battery status detection device can automatically execute the corresponding measures to ensure battery operation safety.

[0178] In this embodiment, abnormal battery states are classified and identified based on the battery's first and second expansion forces to determine the abnormality type. The abnormality type indicates the abnormal state of the battery. Different abnormality types correspond to different potential failure mechanisms and risks. By identifying the specific abnormality type, the specific abnormal situation and cause of the current battery anomaly can be distinguished. For example, is the anomaly caused by an abnormal increase in internal gas pressure (abnormal first expansion force), an abnormal expansion of the electrode structure (abnormal second expansion force), or both? This overcomes the shortcomings of related solutions that only identify the existence of an anomaly without specifying the source of the problem. It also more accurately distinguishes between normal fluctuations and true anomalies, thereby reducing false alarms and missed alarms. Furthermore, based on the battery's abnormality type, abnormality warning information is generated to provide early warning of abnormal battery states. This allows users or the battery management system to determine the relevant cause of the anomaly early on, enabling differentiated protection measures. This not only reduces the risk of safety accidents but also allows for life-extending measures under different failure modes, thereby improving the overall battery life and reliability.

[0179] In one embodiment, step S31, which involves classifying and identifying the abnormal state of the battery based on the first and second expansion forces to determine the type of battery abnormality, specifically includes the following steps:

[0180] S311: Obtain the battery cycle count;

[0181] S312: Based on the first expansion force and the second expansion force, as well as the number of battery cycles, classify and identify the abnormal state of the battery to determine the abnormal type of the battery.

[0182] While determining the first and second expansion forces of the battery, the battery state detection device can also obtain the current number of battery cycles. Then, based on the first and second expansion forces and the number of battery cycles, it can classify and identify abnormal battery states to determine the type of abnormality.

[0183] For example, different first expansion force thresholds and second expansion force thresholds can be set for different number of cycles. Based on the two expansion force thresholds corresponding to the current number of cycles of the battery, the first expansion force and the second expansion force are judged to be abnormal respectively, so as to determine the abnormal type of the battery according to the magnitude of the two expansion forces and the corresponding thresholds.

[0184] It is important to understand that the expansion force characteristics of a battery differ at different stages of its lifespan. For example, the contribution ratio of the first and second expansion forces varies across different cycle count ranges, and the possible causes of anomalies also differ. In this embodiment, abnormal battery states are classified and identified based on the first and second expansion forces, as well as the battery's cycle count, to determine the type of battery anomaly. This reduces identification bias caused by using the same threshold or judgment logic at different stages, making the anomaly type identification more consistent with the battery's actual performance at different life stages. This enhances the adaptability of anomaly identification to different life stages, making anomaly classification more accurate and more in line with the evolutionary pattern of the battery's entire life cycle, thereby improving the reliability and practicality of the early warning system.

[0185] In one embodiment, step S312, which involves classifying and identifying the abnormal state of the battery based on the first expansion force, the second expansion force, and the number of battery cycles to determine the type of battery abnormality, specifically includes the following steps:

[0186] S3121: When the battery cycle count is within the first range, analyze the abnormal state of the battery based on the magnitude of the first expansion force to determine the type of battery abnormality.

[0187] Throughout the battery's lifespan, conventional batteries experience less capacity degradation in the early stages. That is, when the battery's cycle count is in the first range (e.g., 0-3000 cycles), the electrolyte content is relatively high, and the amount of gas generated inside the battery is also relatively large. Therefore, in the early stages of the battery's lifespan, the first expansion force (i.e., soft expansion force) accounts for a relatively high proportion, approximately 40%-50%. Meanwhile, the internal electrode performance is relatively good, and the thickness increase is not significant, making it less likely that the second expansion force (i.e., hard expansion force) will become abnormal. Therefore, when the battery's cycle count is in the first range, the second expansion force can be disregarded. Instead, the magnitude of the first expansion force can be used to analyze the battery's abnormal state to determine the type of abnormality. This reduces interference from the judgment of the second expansion force and lowers the data processing load and energy consumption of the battery state monitoring device.

[0188] For example, when the battery cycle count is in the first range, different expansion force ranges can be preset for the second expansion force. Different expansion force ranges correspond to different abnormality types. Then, based on the expansion force range where the estimated first expansion force is located, the corresponding abnormality type can be determined to obtain the abnormality type of the battery.

[0189] S3122: When the battery cycle count is in the second range, analyze the abnormal state of the battery based on the magnitude of the second expansion force to determine the type of battery abnormality.

[0190] The minimum value in the second interval is greater than the maximum value in the first interval.

[0191] Throughout the battery's lifespan, conventional batteries experience significant capacity degradation in the mid-to-late stages. Specifically, when the battery's cycle count falls within the second range (e.g., greater than 3000 cycles), electrolyte consumption is substantial, with low electrolyte levels or even complete depletion. This leads to a significant decrease in the rate of gas generation within the battery, resulting in a smaller initial expansion force. In the mid-to-late stages of the battery's lifespan, the internal electrode plates continuously thicken, causing the proportion of the second expansion force to increase, potentially reaching 65%-70% towards the end of the battery's life. Therefore, when the battery's cycle count is in the second range, the initial expansion force can be disregarded. Instead, the magnitude of the second expansion force can be used to analyze the battery's abnormal state and determine the type of abnormality. This reduces interference from the initial expansion force assessment and lowers the data processing load and energy consumption of the battery state monitoring device.

[0192] For example, when the battery cycle count is in the second range, different expansion force ranges can be preset for the second expansion force. Different expansion force ranges correspond to different abnormality types. Then, based on the estimated expansion force range in which the second expansion force is located, the corresponding abnormality type can be determined to obtain the abnormality type of the battery.

[0193] In this embodiment, when the battery's cycle count falls within a first interval, the abnormal state of the battery is analyzed based on the magnitude of the first expansion force to determine the type of battery anomaly. When the battery's cycle count falls within a second interval, the abnormal state of the battery is analyzed based on the magnitude of the second expansion force to determine the type of battery anomaly. The minimum value in the second interval is greater than the maximum value in the first interval. The expansion force characteristics of a battery differ at different stages of its lifespan, and the possible causes of anomalies also vary. If both the first and second expansion forces are relied upon simultaneously for anomaly type determination throughout the entire battery lifespan, it may lead to misjudgment due to the small change in the second expansion force in the early stages, or amplification of the first expansion force fluctuations in the later stages, interfering with the determination. This solution divides the cycle count into intervals and focuses on different expansion force types in different intervals, enabling targeted anomaly detection for typical risks at different stages of the battery. It reduces interference from expansion forces with smaller impact within corresponding intervals, improving the accuracy, specificity, and lifespan coverage of anomaly type identification.

[0194] In one embodiment, step S3121, where the battery's cycle count is within a first range, involves analyzing the battery's abnormal state based on the magnitude of the first expansion force to determine the type of battery abnormality. This specifically includes the following steps:

[0195] S31211: When the number of battery cycles is in the first range and the first expansion force is greater than the first preset value, the abnormality type of the battery is determined to be abnormal internal gas production.

[0196] The first interval can be a range of 0 to 3000 iterations.

[0197] When the battery's cycle count is in the first range and the first expansion force is greater than the first preset value, that is, when the battery's current cycle count is less than or equal to 3000 and it is in the early stage of the battery's life cycle, if the first expansion force (i.e. soft expansion force) is greater than the first preset value, it indicates that the amount of gas produced inside the battery is too large. It may be that the internal side reaction is too violent, causing abnormal internal gas production. At this time, the abnormality type of the battery can be determined to be abnormal internal gas production.

[0198] When excessive internal side reactions within a battery lead to excessive gas production, problems such as interface black spots may occur, potentially causing a rapid drop in battery capacity or even fire and explosion. Therefore, once the battery anomaly is identified as an abnormality in internal gas production, the battery status monitoring device can generate an anomaly warning message to indicate that excessive internal gas production poses a risk of rapid capacity loss or even fire and explosion. If the battery is currently in the structural design phase, this warning message can also prompt optimization of the electrolyte and electrode formulation to reduce the occurrence of internal side reactions.

[0199] S31212: When the number of battery cycles is in the first range and the first expansion force is less than the second preset value, determine that the abnormality type of the battery is pre-tightening force or electrolyte abnormality.

[0200] The first preset value is greater than the second preset value. The second preset value can also be equal to the first preset value.

[0201] When the battery's cycle count is in the first range and the first expansion force is less than the second preset value, that is, when the battery's current cycle count is less than or equal to 3000 and it is in the early stage of the battery's life cycle, if the first expansion force (i.e. soft expansion force) is less than the second preset value, it indicates that the amount of gas produced inside the battery is insufficient or too low. This may be caused by excessive pre-tightening force in the battery's internal structure assembly or insufficient electrolyte in the battery. At this time, the battery status detection device can determine that the abnormality of the battery is pre-tightening force or electrolyte abnormality.

[0202] When a battery has excessive preload or insufficient electrolyte, the ion migration efficiency within the battery is low, which may lead to a decrease in the battery's charging and discharging capacity and a reduction in battery life. This can in turn cause a decline in the performance of end products using the battery, such as slow charging, slow vehicle acceleration, and premature end of life.

[0203] Once the battery anomaly is determined to be either a preload or electrolyte anomaly, the battery status detection device can generate an anomaly warning message based on this anomaly type. This message indicates that the abnormality in the assembly preload or electrolyte of the battery's internal structure poses a risk to the battery's charge / discharge performance and lifespan. If the battery is currently in the structural design phase, this anomaly warning message can also prompt optimization of the battery's structural clamp preload and electrolyte, increasing the structural preload and / or increasing the electrolyte injection volume to ensure sufficient gas generation within the battery.

[0204] In this embodiment, when the battery's cycle count is within a first range and the first expansion force is greater than a first preset value, the battery's anomaly type is determined to be abnormal internal gas production. When the battery's cycle count is within the first range and the first expansion force is less than a second preset value, the battery's anomaly type is determined to be either pre-tightening force or electrolyte anomaly, where the first preset value is greater than the second preset value. By setting upper and lower thresholds for the first expansion force during the early cycling stage of the battery, a refined distinction is achieved between abnormal gas production, pre-tightening force, or electrolyte anomalies. This improves the accuracy of anomaly detection and the targeted nature of early warnings, and supports manufacturing quality feedback and operational safety management.

[0205] In one embodiment, step S3122, where the battery cycle count is within the second range, involves analyzing the abnormal state of the battery based on the magnitude of the second expansion force to determine the type of battery abnormality. This specifically includes the following steps:

[0206] S31221: When the number of battery cycles is in the second range and the second expansion force is greater than the third preset value, the abnormality type of the battery is determined to be abnormal electrode thickness.

[0207] The minimum value of the second interval can be greater than 3000 cycles, meaning the second interval can be an interval with more than 300 cycles.

[0208] If the battery's cycle count is in the second range and the second expansion force is greater than the third preset value, that is, if the battery's current cycle count is greater than 3000 and it is in the middle to late stage of the battery's life cycle, and the second expansion force (i.e. shadow expansion force) is greater than the third preset value, it may be due to the electrode thickness inside the battery being too fast. The abnormality type of the battery is determined to be abnormal electrode thickness.

[0209] If the electrode thickness increases too rapidly, it can lead to cracks or even breakage. These breakages can cause short circuits, potentially resulting in fires or explosions, posing a significant safety risk to the battery. Therefore, once the battery anomaly is identified as an abnormal electrode thickness, the battery state monitoring device can generate an anomaly warning message to indicate the risk of electrode failure or irreversible, accelerated expansion during cycling. If the battery is currently in the structural design phase, the anomaly warning message can also suggest improving the group margin when mounting the electrode assembly (including positive and negative electrodes, separator, and conductors) into the casing, such as by reducing the number of winding layers in the electrode assembly.

[0210] S31222: When the number of battery cycles is in the second range and the first expansion force is less than the fourth preset value, the abnormality type of the battery is determined to be insufficient electrode expansion space.

[0211] The third preset value is greater than the fourth preset value. The fourth preset value can also be equal to the third preset value.

[0212] If the battery's cycle count is in the second range and the second expansion force is less than the fourth preset value, that is, if the battery's current cycle count is greater than 3000 and it is in the middle to late stage of the battery's life cycle, the second expansion force being less than the fourth preset value may be due to the low group margin of the electrode assembly inside the battery, that is, the space between the electrode assembly and the casing is small. In this case, the abnormality type of the battery is determined to be insufficient electrode expansion space.

[0213] When there is insufficient space for electrode expansion, continued expansion of the electrodes can easily compress the casing, posing a risk of casing deformation or failure. Therefore, after determining that the battery anomaly is due to insufficient electrode expansion space, the battery state monitoring device can generate an anomaly warning message based on this anomaly type to indicate insufficient electrode expansion space and the risk of casing deformation or failure. If the battery is currently in the battery structure design stage, the anomaly warning message can also indicate that the electrode assembly's packing margin is too low, the internal space utilization efficiency of the battery is unreasonable (the casing space is not optimally allocated, and some potential capacity cannot be utilized), and the energy density design of the battery structure is not optimal. This can increase the packing margin of the electrode assembly and improve the product's capacity.

[0214] In this embodiment, when the battery's cycle count is within the second range and the second expansion force is greater than the third preset value, the battery's anomaly type is determined to be abnormal electrode thickness. When the battery's cycle count is within the second range and the first expansion force is less than the fourth preset value, the battery's anomaly type is determined to be insufficient electrode expansion space, and the third preset value is greater than the fourth preset value. By setting upper and lower thresholds for the second expansion force in the mid-to-late stages of the battery's lifespan, refined identification of abnormal electrode thickness and insufficient electrode expansion space is achieved, thereby improving the accuracy of mid-to-late stage failure mechanism localization and the targeted nature of anomaly warnings, supporting battery operation management and structural design optimization.

[0215] It should be understood that the sequence number of each step in the above embodiments does not imply the order of execution. The execution order of each process should be determined by its function and internal logic, and should not constitute any limitation on the implementation process of the embodiments of the present invention.

[0216] In one embodiment, a battery state detection device is provided, which corresponds one-to-one with the battery state detection method described in the above embodiments. For example... Figure 11 As shown, the battery status detection device includes a monitoring module 111, a prediction module 112, and a detection module 113. Detailed descriptions of each functional module are as follows:

[0217] The monitoring module 111 is used to monitor the expansion force during battery operation in order to obtain the measured value of the battery's expansion force.

[0218] The estimation module 112 is used to estimate the expansion force of different types of batteries based on the expansion force measurement value, and obtain the first expansion force and the second expansion force of the battery; the first expansion force is the expansion force generated by the increase of gas pressure inside the battery, and the second expansion force is the expansion force generated by the increase of the thickness of the internal electrode during the operation of the battery.

[0219] The detection module 113 is used to detect and warn of abnormal battery types based on the first and second expansion forces of the battery.

[0220] In one embodiment, the estimation module 112 is specifically used to: when it is determined that the state of the battery is abnormal based on the expansion force measurement value, to estimate the expansion force of different types of the battery based on the expansion force measurement value, and to obtain the first expansion force and the second expansion force of the battery.

[0221] In one embodiment, the estimation module 112 is further configured to: determine the target expansion force ratio of the battery based on the number of battery cycles and from pre-calibrated expansion force ratio data, wherein the expansion force ratio data is calibrated based on the measured data of the battery and includes the ratio values ​​of different types of expansion forces corresponding to batteries with different number of cycles during operation; and estimate the expansion forces of different types of batteries based on the measured expansion force value and the target expansion force ratio to obtain the first expansion force and the second expansion force of the battery.

[0222] In one embodiment, the battery state detection device may further include a calibration module for calibrating expansion force ratio data. The calibration module is used to: classify the expansion force of the battery under test based on the simulated expansion force data of the battery casing at different cycle counts, thereby obtaining the first expansion force and the second expansion force of the battery under test at different cycle counts; and determine the ratio of the first expansion force and the second expansion force at different cycle counts based on the first expansion force and the second expansion force of the battery under test at different cycle counts, thereby generating expansion force ratio data. The actual expansion force data is obtained by performing operation tests on the battery under test at different cycle counts, and the simulated expansion force data is obtained by simulating the battery operating conditions of the battery casing. The battery casing is the casing structure of the battery under test after removing the internal electrode assembly and electrolyte.

[0223] In one embodiment, the calibration module is specifically used to: acquire measured expansion force data of the battery under test at different cycle counts, the measured expansion force data including the large-area expansion force and end-face expansion force of the battery under test at the corresponding cycle counts, the large-area expansion force being the expansion force on the side of the battery cell corresponding to the electrode winding direction, and the end-face expansion force being the expansion force on the end face of the battery perpendicular to the electrode winding direction; acquire simulated expansion force data of the battery casing, the simulated expansion force data including the large-area expansion force and end-face expansion force of the battery casing at different inflation pressures; align the measured expansion force data with the end-face expansion force in the simulated expansion force data, so as to decompose the large-area expansion force in the measured expansion force data based on the large-area expansion force in the simulated expansion force data, and obtain the first expansion force and the second expansion force of the battery under test at different cycle counts.

[0224] In one embodiment, the calibration module is further configured to: determine the proportion of the first expansion force and the proportion of the second expansion force under different cycle numbers based on the first expansion force and the second expansion force of the battery under test under different cycle numbers; perform performance qualification verification on the battery under test based on the proportion of the first expansion force and the proportion of the second expansion force under different cycle numbers; and output the proportion of the first expansion force and the proportion of the second expansion force of the battery under test under different cycle numbers as expansion force proportion data if the performance qualification verification result of the battery under test is qualified.

[0225] In one embodiment, the detection module 113 is specifically used to: classify and identify the abnormal state of the battery according to the first expansion force and the second expansion force of the battery to determine the abnormal type of the battery, the abnormal type being used to indicate the abnormal state of the battery; and generate abnormal warning information for the battery according to the abnormal type of the battery, the abnormal warning information being used to warn of abnormal state of the battery.

[0226] In one embodiment, the detection module 113 is further configured to: obtain the number of battery cycles; classify and identify abnormal states of the battery based on the first expansion force and the second expansion force, as well as the number of battery cycles, to determine the abnormal type of the battery.

[0227] In one embodiment, the detection module 113 is further configured to: when the number of battery cycles is in a first interval, analyze the abnormal state of the battery based on the magnitude of the first expansion force to determine the abnormal type of the battery; when the number of battery cycles is in a second interval, analyze the abnormal state of the battery based on the magnitude of the second expansion force to determine the abnormal type of the battery, wherein the minimum value of the second interval is greater than the maximum value of the first interval.

[0228] In one embodiment, the detection module 113 is further configured to: determine that the abnormality type of the battery is abnormal internal gas production when the battery cycle count is in a first range and the first expansion force is greater than a first preset value; determine that the abnormality type of the battery is abnormal pre-tightening force or electrolyte when the battery cycle count is in the first range and the first expansion force is less than a second preset value, wherein the first preset value is greater than the second preset value; determine that the abnormality type of the battery is abnormal electrode thickness when the battery cycle count is in the second range and the second expansion force is greater than a third preset value; and determine that the abnormality type of the battery is insufficient electrode expansion space when the battery cycle count is in the second range and the first expansion force is less than a fourth preset value, wherein the third preset value is greater than the fourth preset value.

[0229] It should be noted that the information interaction and execution process between the above-mentioned devices / units are based on the same concept as the method embodiments of this application. For details on their specific functions and technical effects, please refer to the method embodiments section, and they will not be repeated here.

[0230] Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the above-described division of functional units and modules is merely an example. In practical applications, the above functions can be assigned to different functional units and modules as needed, that is, the internal structure of the device can be divided into different functional units or modules to complete all or part of the functions described above. The functional units and modules in the embodiments can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated unit can be implemented in hardware or as a software functional unit. Furthermore, the specific names of the functional units and modules are only for easy differentiation and are not intended to limit the scope of protection of this application. The specific working process of the units and modules in the above system can be referred to the corresponding process in the foregoing method embodiments, and will not be repeated here.

[0231] This application also provides an electronic device, such as... Figure 12 As shown, the electronic device 12 includes: at least one processor 121, a memory 122, and a computer program 123 stored in the memory 122 and executable on the at least one processor 121. When the processor 121 executes the computer program 123, it implements the steps in any of the above method embodiments, or when the processor 121 executes the computer program 123, it implements the functions of each module / unit in the above device embodiments.

[0232] For example, the computer program 123 may be divided into one or more modules / units, which are stored in the memory 122 and executed by the processor 121 to complete this application. The one or more modules / units may be a series of computer program instruction segments capable of performing a specific function, which describe the execution process of the computer program 123 in the electronic device 12.

[0233] Those skilled in the art will understand that Figure 12 The electronic device described is merely an example and does not constitute a limitation on the electronic device. It may include more or fewer components than shown, or combine certain components, or different components. For example, the electronic device may also include input / output devices, network access devices, buses, etc.

[0234] The aforementioned processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor can be a microprocessor or any conventional processor.

[0235] The memory can be an internal storage unit of the electronic device, such as a hard drive or RAM. The memory can also be an external storage device of the electronic device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card. Furthermore, the memory can include both internal and external storage units of the electronic device.

[0236] This application also provides a readable storage medium storing a computer program that, when executed by a processor, implements the steps described in the various method embodiments above.

[0237] This application provides a computer program product that, when run on an electronic device, enables the electronic device to perform the steps described in the various method embodiments above.

[0238] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, all or part of the processes in the methods of the above embodiments of this application can be implemented by a computer program instructing related hardware. The computer program can be stored in a computer-readable storage medium, and when executed by a processor, it can implement the steps of the various method embodiments described above. The computer program includes computer program code, which can be in the form of source code, object code, executable files, or certain intermediate forms. The computer-readable medium can include at least: any entity or device capable of carrying computer program code to a photographing device / terminal device, a recording medium, a computer memory, a read-only memory (ROM), a random access memory (RAM), an electrical carrier signal, a telecommunication signal, and a software distribution medium. Examples include USB flash drives, portable hard drives, magnetic disks, or optical disks. In some jurisdictions, according to legislation and patent practice, computer-readable media cannot be electrical carrier signals or telecommunication signals.

[0239] In the above embodiments, the descriptions of each embodiment have different focuses. For parts that are not described in detail or recorded in a certain embodiment, please refer to the relevant descriptions of other embodiments.

[0240] Those skilled in the art will recognize that the units and algorithm steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0241] In the embodiments provided in this application, it should be understood that the disclosed apparatus / devices and methods can be implemented in other ways. For example, the apparatus / device embodiments described above are merely illustrative. For instance, the division of modules or units is only a logical functional division, and in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be through some interfaces; the indirect coupling or communication connection between apparatuses or units may be electrical, mechanical, or other forms.

[0242] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0243] The above-described embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A battery state detection method characterized by, The method comprises the following steps: monitoring the expansion force during the operation of the battery to obtain an expansion force measurement value of the battery; estimating different types of expansion force of the battery according to the expansion force measurement value to obtain a first expansion force and a second expansion force of the battery, which comprises the following steps: determining a target expansion force ratio of the battery in pre-calibrated expansion force ratio data according to the cycle number of the battery, wherein the expansion force ratio data is calibrated according to battery measured data, and the expansion force ratio data comprises the ratio values of different types of expansion force corresponding to the battery in the operation process under different cycle numbers; estimating different types of expansion force of the battery according to the expansion force measurement value and the target expansion force ratio to obtain a first expansion force and a second expansion force of the battery, wherein the first expansion force is the expansion force generated by the increase of the internal gas pressure of the battery, and the second expansion force is the expansion force generated by the increase of the internal pole thickness of the battery during the operation of the battery; detecting and warning the abnormal type of the battery according to the first expansion force and the second expansion force of the battery.

2. The battery state detection method according to claim 1, wherein The method comprises the following steps: in the case that the state of the battery determined according to the expansion force measurement value is abnormal, estimating different types of expansion force of the battery according to the expansion force measurement value to obtain a first expansion force and a second expansion force of the battery.

3. The battery state detection method according to claim 1, wherein The expansion force ratio data is calibrated in the following way: taking the expansion force simulation data of the battery shell as the expansion force reference, classifying the expansion force measured data of the battery under test under different cycle numbers to obtain the first expansion force and the second expansion force of the battery under test under different cycle numbers; determining the ratio values of the first expansion force and the second expansion force under different cycle numbers respectively to generate the expansion force ratio data according to the first expansion force and the second expansion force of the battery under test under different cycle numbers; wherein the expansion force measured data is obtained by running the battery under test under different cycle numbers, the expansion force simulation data is measured after simulating the battery operation condition of the battery shell, and the battery shell is the shell structure of the battery under test after removing the internal pole assembly and the electrolyte.

4. The battery state detection method according to claim 3, wherein The method comprises the following steps: obtaining the expansion force measured data of the battery under test under different cycle numbers, wherein the expansion force measured data comprises the large surface expansion force and the end surface expansion force of the battery under test under the corresponding cycle number, the large surface expansion force is the expansion force of the side surface of the battery monomer corresponding to the winding direction of the pole piece, and the end surface expansion force is the expansion force of the end surface of the battery perpendicular to the winding direction of the pole piece; Obtaining expansion force simulation data of the battery shell, the expansion force simulation data including large face expansion forces and end face expansion forces of the battery shell under different inflation pressures; Performing end face expansion force alignment processing on the expansion force measured data and the end face expansion forces in the expansion force simulation data, to split the large face expansion forces in the expansion force measured data based on the large face expansion forces in the expansion force simulation data, to obtain first expansion forces and second expansion forces of the battery under test under different cycle numbers.

5. The battery state detection method according to claim 4, wherein The first expansion force and the second expansion force of the battery under test under different cycle numbers are determined respectively to generate the expansion force ratio data, including: According to the first expansion force and the second expansion force of the battery under test under different cycle numbers, the ratio of the first expansion force and the ratio of the second expansion force under different cycle numbers are determined; According to the ratio of the first expansion force and the ratio of the second expansion force under different cycle numbers, the performance qualification of the battery under test is verified; In the case that the performance qualification of the battery under test is qualified, the ratio of the first expansion force and the ratio of the second expansion force of the battery under test under different cycle numbers are output as the expansion force ratio data.

6. The battery state detection method according to any one of claims 1 to 5, characterized by, According to the first expansion force and the second expansion force of the battery, the abnormal type detection and early warning of the battery are performed, including: According to the first expansion force and the second expansion force of the battery, the abnormal state of the battery is classified and identified to determine the abnormal type of the battery, the abnormal type being used to indicate the abnormal state of the battery; According to the abnormal type of the battery, the abnormal early warning information of the battery is generated, which is used to early warn the abnormal state of the battery.

7. The battery state detection method according to claim 6, wherein According to the first expansion force and the second expansion force of the battery, the abnormal state of the battery is classified and identified to determine the abnormal type of the battery, including: Obtaining the cycle number of the battery; According to the first expansion force and the second expansion force, and the cycle number of the battery, the abnormal state of the battery is classified and identified to determine the abnormal type of the battery.

8. The battery state detection method according to claim 7, wherein According to the first expansion force and the second expansion force, and the cycle number of the battery, the abnormal state of the battery is classified and identified to determine the abnormal type of the battery, including: In the case that the cycle number of the battery is in a first interval, the abnormal state of the battery is analyzed according to the size of the first expansion force to determine the abnormal type of the battery; In the case that the cycle number of the battery is in a second interval, the abnormal state of the battery is analyzed according to the size of the second expansion force to determine the abnormal type of the battery, the minimum value of the second interval being greater than the maximum value of the first interval.

9. The battery state detection method according to claim 8, wherein In the case that the cycle number of the battery is in a first interval, the abnormal state of the battery is analyzed according to the size of the first expansion force to determine the abnormal type of the battery, including: In a case where the cycle number of the battery is in a first interval and the first expansion force is greater than a first preset value, it is determined that the abnormal type of the battery is an abnormality in internal gas production of the battery. In a case where the cycle number of the battery is in a first interval and the first expansion force is less than a second preset value, it is determined that the abnormal type of the battery is a pre-tightening force or electrolyte abnormality, the first preset value being greater than the second preset value.

10. The battery state detection method according to claim 8, wherein In a case where the cycle number of the battery is in a second interval, the abnormal state of the battery is analyzed according to the size of the second expansion force, so as to determine the abnormal type of the battery, comprising: In a case where the cycle number of the battery is in a second interval and the second expansion force is greater than a third preset value, it is determined that the abnormal type of the battery is an abnormality in thickness of the pole piece. In a case where the cycle number of the battery is in a second interval and the first expansion force is less than a fourth preset value, it is determined that the abnormal type of the battery is an insufficient expansion space of the pole piece, the third preset value being greater than the fourth preset value.

11. A battery state detecting device characterized by comprising: Comprising: A monitoring module configured to monitor an expansion force in a running process of a battery, so as to obtain an expansion force measurement value of the battery; A pre-estimating module configured to pre-estimate different types of expansion forces of the battery according to the expansion force measurement value, so as to obtain a first expansion force and a second expansion force of the battery, comprising: determining a target expansion force ratio of the battery in pre-labeled expansion force ratio data according to a cycle number of the battery, the expansion force ratio data being labeled according to battery actual measurement data, the expansion force ratio data comprising ratio values of different types of expansion forces corresponding to the battery in a running process at different cycle numbers; pre-estimating the different types of expansion forces of the battery according to the expansion force measurement value and the target expansion force ratio, so as to obtain the first expansion force and the second expansion force of the battery; the first expansion force being an expansion force generated by an internal gas pressure rise of the battery, and the second expansion force being an expansion force generated by an internal pole piece thickness increase of the battery in a working process; A detecting module configured to detect an abnormal type of the battery and give a warning according to the first expansion force and the second expansion force of the battery.

12. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, The processor executes the computer program to implement the steps of the battery state detection method according to any one of claims 1 to 10.

13. A readable storage medium, the readable storage medium storing a computer program, characterized in that, The computer program is executed by the processor to implement the steps of the battery state detection method according to any one of claims 1 to 10.

14. A computer program product comprising a computer program, characterized in that, The computer program is executed to cause the battery state detection method according to any one of claims 1 to 10 to be executed.

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