Battery cell specification updating method, battery, battery pack, battery pack and electric vehicle

Abstract

The invention discloses a battery cell specification updating method, a battery, a battery pack, a battery pack and an electric vehicle, and relates to the technical field of batteries, the battery at least comprises a battery cell, and an expansion parameter value corresponding to a target specification adopted by the battery cell is within a preset safety expansion threshold value range. The expansion parameter value is determined by a battery cell analysis system in communication connection with the battery; the battery cell analysis system is used for processing the internal air pressure data through a preset soft expansion function to determine a soft expansion force component of the battery cell at each sampling moment, and determining a hard expansion force component based on the total expansion force data and the soft expansion force components; respectively aligning the soft and hard expansive force components with the synchronously acquired voltage and capacity curves on a time axis to obtain a multi-dimensional associated data set; and updating the specification parameter to which the target specification belongs according to the multi-dimensional associated data set and the target optimal value, thereby solving the problem of low analysis efficiency of the battery expansion behavior, and achieving the purpose of dynamically adjusting the specification parameter corresponding to the battery cell through the expansion analysis result.

Description

Technical Field

[0001] This application relates to the field of battery technology, and more specifically, to a method for updating cell specifications, a battery, a battery pack, a battery module, and an electric vehicle. Background Technology

[0002] As lithium batteries evolve towards higher energy density, faster charging rates, and novel chemical systems, they commonly suffer from severe cell expansion and gas generation issues. These problems lead to accelerated capacity decay, increased internal resistance, abnormal opening of safety valves, and even thermal runaway. Current technologies can only independently perform expansion force testing or internal pressure monitoring. The former cannot distinguish between hard expansion caused by electrode thickening and soft expansion caused by gas evolution, while the latter completely fails to reflect the deformation of solid components. The data from these two methods are fragmented and lack linkage, making it difficult to accurately pinpoint the root cause of failure and hindering data-driven design optimization. Furthermore, battery specifications are static design parameters, unable to be dynamically adjusted based on actual operating environments (such as temperature, rate, and cycle count) and internal expansion evolution behavior. This results in either redundant or insufficient safety margins, restricting further improvements in battery performance, lifespan, and reliability. Therefore, these technologies suffer from low efficiency in analyzing battery expansion behavior and an inability to dynamically adjust cell specifications based on analysis results to adapt to actual operating environments.

[0003] There is still no effective solution to the technical problems of low efficiency in analyzing battery expansion behavior and inability to dynamically adjust cell specifications based on analysis results to adapt to actual use environments in related technologies. Summary of the Invention

[0004] This application provides a method for updating battery cell specifications, a battery, a battery pack, a battery module, and an electric vehicle, to at least solve the technical problems in the related art, such as low efficiency in analyzing battery expansion behavior and the inability to dynamically adjust battery cell specification parameters based on analysis results to adapt to the actual use environment.

[0005] According to one embodiment of this application, a battery is provided, the battery including at least a cell, wherein the expansion parameter value corresponding to the target specification of the cell is within a preset safe expansion threshold range, wherein the expansion parameter value is determined by a cell analysis system communicatively connected to the battery; the cell analysis system is used to: collect total expansion force data and internal air pressure data of the cell during charging, discharging or storage; process the internal air pressure data through a preset soft expansion function to obtain the soft expansion force component of the cell at each sampling time, and determine the hard expansion force component corresponding to the cell based on the total expansion force data and the soft expansion force component; align the soft expansion force component and the hard expansion force component with the synchronously collected voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset; determine the target preferred value corresponding to the expansion parameter value based on the multidimensional correlation dataset and the battery's usage environment, and update the specification parameters to which the target specification belongs based on the target preferred value.

[0006] According to another embodiment of this application, a method for updating battery cell specifications is provided, applied to a battery cell analysis system communicatively connected to a battery. The method includes: acquiring total expansion force data and internal pressure data of the battery cell during charging, discharging, or storage; processing the internal pressure data using a preset soft expansion function to obtain the soft expansion force component of the battery cell at each sampling time, and determining the corresponding hard expansion force component of the battery cell based on the total expansion force data and the soft expansion force component; aligning the soft expansion force component and the hard expansion force component with synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset; determining a target preferred value corresponding to the expansion parameter value based on the multidimensional correlation dataset and the battery's usage environment, and updating the specification parameters to which the target specification belongs based on the target preferred value.

[0007] According to another embodiment of the present application, a battery pack is also provided, including at least two batteries of the above embodiments, each of which is electrically connected to the other.

[0008] According to another embodiment of the present application, a battery pack is also provided, including a housing and at least two battery packs of the above embodiments, each of the battery packs being disposed in the housing and electrically connected to each other.

[0009] According to yet another embodiment of the present application, an electric vehicle is also provided, including the battery pack of the above embodiment.

[0010] According to another aspect of the embodiments of this application, a computer-readable storage medium is also provided, wherein a computer program is stored in the computer program, which is configured to execute the above-described method for updating the battery cell specifications when running.

[0011] According to another aspect of the embodiments of this application, an electronic device is also provided, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the above-described method for updating battery cell specifications through the computer program.

[0012] According to another aspect of the embodiments of this application, a computer program product is also provided, including a computer program that, when executed by a processor, implements the above-described method for updating battery cell specifications.

[0013] In this embodiment, a battery configured such that the expansion parameter values ​​corresponding to the target specification of the battery cell are within a preset safe expansion threshold range is proposed. A battery cell analysis system, communicatively connected to the battery, determines the parameter values ​​of the detection parameters. The system then collects total expansion force data and internal pressure data of the battery cell during charging, discharging, or storage. A preset soft expansion function is used to process the internal pressure data to obtain the soft expansion force component of the battery cell at each sampling moment. Based on the total expansion force data and the soft expansion force component, the corresponding hard expansion force component of the battery cell is determined. The soft and hard expansion force components are aligned with synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset. Based on the multidimensional correlation dataset and the battery's usage environment, a target optimal value corresponding to the expansion parameter value is determined, and the specification parameters of the target specification are updated based on the target optimal value. Using the above technical solution, a battery cell analysis system, either built-in or external, is used to analyze the battery cell. Precise perception and proactive control of expansion behavior: First, the total expansion force and internal pressure data of the battery cell during charging, discharging, or storage are collected synchronously. A preset soft expansion function is used to convert the pressure signal into a soft expansion force component. Then, by subtracting the soft expansion force from the total expansion force, the hard expansion force component caused by solid deformation such as electrode thickening is decoupled. Subsequently, these two key mechanical components are precisely aligned with the synchronously collected voltage and capacity curves in the time dimension to construct a multi-dimensional correlation dataset covering mechanical, electrochemical, and environmental factors. Based on this, the dataset is comprehensively analyzed in conjunction with the actual battery usage environment to calculate the most suitable target value under the current operating conditions—the optimal expansion control target. This automatically triggers dynamic adjustments to the battery cell design specifications, thereby achieving control over battery expansion behavior in the early stages of battery manufacturing. This solves the technical problems of low efficiency in analyzing battery expansion behavior and the inability to dynamically adjust cell specifications based on analysis results to adapt to the actual usage environment, thus improving battery safety. Attached Figure Description

[0014] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0015] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, for those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0016] Figure 1 This is a flowchart of a method for updating battery cell specifications according to an embodiment of this application;

[0017] Figure 2 This is a schematic flowchart of an expansion analysis according to an embodiment of this application;

[0018] Figure 3 This is a schematic diagram of the architecture of a battery cell analysis system according to an embodiment of this application;

[0019] Figure 4 This is a test result of a storage soft expansion decomposition according to an embodiment of this application;

[0020] Figure 5 This is a test result of cyclic soft expansion decomposition according to an embodiment of this application;

[0021] Figure 6 This is a cell variation trend diagram of different buffer pads according to an embodiment of this application;

[0022] Figure 7 This is a graph showing the variation trend of battery cells with different preloads according to an embodiment of this application;

[0023] Figure 8 This is a diagram illustrating the soft and hard expansion of a battery cell according to an embodiment of this application;

[0024] Figure 9 This is a diagram illustrating the soft and hard expansion of a battery cell during charging and discharging, according to an embodiment of this application.

[0025] Figure 10 This is a structural block diagram of a battery according to an embodiment of this application. Detailed Implementation

[0026] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those of ordinary skill in the art without creative effort should fall within the scope of protection of the present application.

[0027] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0028] The following appropriately discloses an embodiment of a battery according to this application. However, unnecessary detailed descriptions may be omitted. For example, detailed descriptions of well-known matters and repetitive descriptions of practically identical structures may be omitted. This is to avoid making the following description unnecessarily lengthy and to facilitate understanding by those skilled in the art. Furthermore, the following description is provided to enable those skilled in the art to fully understand this application and is not intended to limit the subject matter of the claims.

[0029] The battery in this application is a secondary battery, also known as a rechargeable battery or storage battery, which refers to a battery that can be used again after being discharged by recharging to activate the active materials.

[0030] Typically, a secondary battery includes an electrode assembly, an electrolyte, and an outer casing. The electrode assembly consists of a positive electrode, a negative electrode, and a separator. The electrode assembly and electrolyte are assembled inside the outer casing. During charging and discharging, active ions (such as lithium ions) move back and forth between the positive and negative electrodes, inserting and extracting. The separator, positioned between the positive and negative electrodes, primarily prevents short circuits while allowing active ions to pass through. The electrolyte, located between the positive and negative electrodes, mainly serves to conduct active ions.

[0031] This embodiment provides a method for updating battery cell specifications, applied to a battery cell analysis system that communicates with a battery. Figure 1 This is a flowchart illustrating a method for updating battery cell specifications according to an embodiment of this application. The process includes the following steps:

[0032] Step S102: Obtain the total expansion force data and internal air pressure data of the battery cell during charging, discharging or storage;

[0033] Step S104: Process the internal air pressure data through a preset soft expansion function to obtain the soft expansion force component of the cell at each sampling time, and determine the hard expansion force component of the cell based on the total expansion force data and the soft expansion force component.

[0034] Step S106: Align the soft expansion force component and the hard expansion force component with the synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset.

[0035] Optionally, the charging and discharging equipment automatically captures and collects pressure and air pressure data by acquiring the communication protocol of the air pressure and pressure data acquisition module, and automatically correlates it with the data during charging and discharging, ultimately generating raw charging and discharging test data with air pressure and pressure data. Data linkage can be understood as the air pressure and pressure data acquisition being part of the charging and discharging equipment, synchronously acquiring data such as voltage, current, and temperature that are originally built into the charging and discharging machine.

[0036] Step S108: Determine the target preferred value corresponding to the expansion parameter value based on the multidimensional association dataset and the battery usage environment, and update the specification parameters to which the target specification belongs based on the target preferred value.

[0037] Optionally, firstly, high-precision force sensors and miniature pressure sensors are used to collect in real time the total expansion force reflecting the overall deformation and the internal gas pressure reflecting the gas generation generated by the battery cell during actual charging and discharging or long-term storage. This data is then used to determine the optimal method based on the soft expansion function F obtained in advance through calibration of the empty battery cell. soft =P×A+F, where A is the large surface area of ​​the cell, F0 is the initial pre-tightening force of the battery, and P is the internal pressure. The internal pressure data is converted into a soft expansion force component caused only by gas expansion. By subtracting the soft expansion force from the total expansion force, the hard expansion force component caused by solid mechanisms such as electrode thickening, SEI film growth, and changes in electrode material structure is separated. The decoupled soft and hard expansion force time series are aligned with the synchronously acquired voltage and capacity curves with high precision. For example, based on sampling clock synchronization or interpolation to compensate for sensor delay, a fused multidimensional correlation dataset is constructed so that each expansion fluctuation can correspond to a specific electrochemical reaction stage. Then, using this multidimensional dataset in combination with the environmental conditions of the battery, such as temperature, rate, and cycle number, the optimal expansion control target under the current operating conditions is derived through the algorithm model, i.e., the target optimization value, and the dynamic update of cell design specifications parameters, such as compaction density, venting chamber volume, and safety valve threshold, is automatically triggered.

[0038] Through the above steps, a battery configured such that the expansion parameter values ​​corresponding to the target specification of the battery cell are within a preset safe expansion threshold range is proposed. The battery cell analysis system, connected in communication with the battery, determines the parameter values ​​of the detection parameters. Then, the battery cell analysis system collects total expansion force data and internal pressure data of the battery cell during charging, discharging, or storage. The internal pressure data is processed using a preset soft expansion function to obtain the soft expansion force component of the battery cell at each sampling time. Based on the total expansion force data and the soft expansion force component, the corresponding hard expansion force component of the battery cell is determined. The soft expansion force component and hard expansion force component are aligned with the synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset. Based on the multidimensional correlation dataset and the battery's usage environment, the target optimal value corresponding to the expansion parameter value is determined, and the specification parameters of the target specification are updated based on the target optimal value. Using the above technical solution, through a built-in or external battery cell analysis system, the expansion of the battery cell can be monitored. Precise perception and proactive control of behavior: First, the total expansion force and internal air pressure data of the battery cell during charging, discharging, or storage are collected synchronously. The air pressure signal is converted into a soft expansion force component using a preset soft expansion function. By subtracting the soft expansion force from the total expansion force, the hard expansion force component caused by solid deformation such as electrode thickening is decoupled. Subsequently, these two key mechanical components are precisely aligned with the synchronously collected voltage and capacity curves in the time dimension to construct a multi-dimensional correlation dataset covering mechanical, electrochemical, and environmental factors. Based on this, the dataset is comprehensively analyzed in conjunction with the actual battery usage environment to calculate the most suitable target value under the current operating conditions, i.e., the optimal expansion control target. This automatically triggers dynamic adjustments to the battery cell design specifications, thereby achieving control over battery expansion behavior in the early stages of battery manufacturing. This solves the technical problems of low efficiency in analyzing battery expansion behavior and the inability to dynamically adjust battery cell specifications based on analysis results to adapt to the actual usage environment, thus improving battery safety.

[0039] In an exemplary embodiment, after updating the specification parameters of the target specification based on the target preferred value, the cell specification updating method further includes: comparing the hard expansion preferred value in the target preferred value with the hard expansion limit value in the target specification to obtain a first comparison result; comparing the soft expansion preferred value in the target preferred value with the soft expansion limit value in the target specification to obtain a second comparison result; and generating a cell design adjustment strategy corresponding to the target specification based on the first comparison result and the second comparison result.

[0040] Understandably, after calculating the target optimal value based on the multidimensional behavioral correlation dataset, i.e. the optimal hard expansion and soft expansion control target under the current operating conditions, a risk assessment and design decision-making closed loop is further executed: First, the target optimal value for hard expansion is compared with the preset hard expansion limit value in the cell design specifications, such as the expansion force threshold corresponding to the maximum allowable thickness of the electrode, to determine whether the electrode deformation is close to the safety boundary, thus obtaining the first comparison result; at the same time, the target optimal value for soft expansion is compared with the soft expansion limit value, such as the gas pressure threshold corresponding to the safety valve opening pressure or the expansion force upper limit corresponding to the critical volume of the venting chamber, to assess whether the risk of gas generation exceeds the limit, thus obtaining the second comparison result; subsequently, based on the combined state of these two comparison results, such as: hard expansion exceeds the limit but soft expansion is normal, soft expansion exceeds the limit but hard expansion is controllable, or both are critical, a targeted cell design adjustment strategy is generated, such as suggesting reducing the electrode compaction density or increasing the diaphragm porosity when hard expansion exceeds the limit, and suggesting increasing the venting chamber volume or increasing the safety valve opening pressure when soft expansion exceeds the limit.

[0041] In an exemplary embodiment, generating a cell design adjustment strategy corresponding to the target specification based on a first comparison result and a second comparison result includes: if the first comparison result indicates that the preferred value of hard expansion is greater than or equal to the hard expansion limit value, determining the cell design adjustment strategy as a first strategy, wherein the first strategy includes at least one of the following: reducing the compaction density of the upper electrode sheet of the cell and increasing the porosity of the separator inside the cell; if the second comparison result indicates that the preferred value of soft expansion is greater than or equal to the soft expansion limit value, determining the cell design adjustment strategy as a second strategy, wherein the second strategy includes at least one of the following: increasing the volume of the venting chamber near the cell and increasing the opening pressure of the safety valve connected to the cell.

[0042] Optionally, when the first comparison result shows that the preferred value for hard expansion is greater than or equal to the hard expansion limit, indicating that the electrode thickness or structural expansion has approached the material limit and there is a risk of instability or electrical contact failure, the first strategy is automatically triggered. This involves reducing the compaction density of the positive and negative electrodes to reserve more expansion space, or increasing the porosity of the separator to improve the wettability of the electrolyte and the flexible buffering capacity of the ion transport channels. When the second comparison result shows that the preferred value for soft expansion is greater than or equal to the soft expansion limit, indicating that the gas generation rate is too fast or the gas accumulation exceeds the safe venting capacity and there is a risk of valve opening or thermal runaway, the second strategy is activated. This involves increasing the volume of the venting chamber inside the cell or module to slow down the rate of gas pressure rise, or increasing the opening pressure threshold of the safety valve connected to the cell to allow the gas to be discharged in an orderly manner under higher pressure, thereby improving the safety of battery use.

[0043] In one exemplary embodiment, generating a cell design adjustment strategy corresponding to the target specification based on the first comparison result and the second comparison result further includes: prohibiting the output of the cell design adjustment strategy if the first comparison result indicates that the preferred value of hard expansion is less than the hard expansion limit value or the second comparison result indicates that the preferred value of soft expansion is less than the soft expansion limit value. If the first comparison result indicates that the preferred value of hard expansion is greater than or equal to the hard expansion limit value, and the second comparison result indicates that the preferred value of soft expansion is greater than or equal to the soft expansion limit value, a composite adjustment strategy is triggered, wherein the composite adjustment strategy involves first performing venting chamber adjustment, and then performing electrode structure adjustment.

[0044] Optionally, when the first comparison result shows that the preferred value for hard expansion is lower than the hard expansion limit, or the second comparison result shows that the preferred value for soft expansion is lower than the soft expansion limit, the current expansion behavior of the cell is determined to be within the safe redundancy range. No intervention is required, and any design adjustment strategy is automatically prohibited to avoid over-design or invalid changes, ensuring the simplicity and resource efficiency of the development process. Under extreme conditions, if both exceed the limit, i.e., both hard expansion and soft expansion approach or exceed the safety threshold, a composite adjustment strategy will be triggered. Priority will be given to adjusting the venting chamber, such as increasing the reserved venting chamber volume and optimizing the exhaust channel structure, to quickly alleviate the risk of internal pressure surge caused by gas production and curb the thermal runaway chain reaction. After the gas pressure is initially controlled, the electrode structure adjustment will be initiated, such as reducing the compaction density, increasing the diaphragm thickness, or introducing an elastic buffer layer, to reduce the accumulation of solid deformation and ensure the long-term cycle stability of the cell.

[0045] In an exemplary embodiment, after updating the specification parameters of the target specification based on the target preferred value, the cell specification update method further includes: entering a verification loop mode when the specification parameters have been updated, wherein the verification loop mode is used to determine the deviation rates of different expansion behaviors before and after the specification parameters have been updated; calculating a first deviation rate of soft expansion behavior and a second deviation rate of hard expansion behavior output by the verification loop mode; determining that the update of the specification parameters is a valid parameter update when the first deviation rate is less than a first preset deviation rate and the second deviation rate is less than a second preset deviation rate; and determining that the update of the specification parameters is an invalid parameter update when the first deviation rate is greater than or equal to the first preset deviation rate and / or the second deviation rate is greater than or equal to the second preset deviation rate.

[0046] In other words, after updating the cell specifications based on the target optimal values, the system automatically enters a verification loop mode. Under the same operating conditions, parallel charge-discharge or storage tests are performed on the cells before and after the update, and their soft expansion and hard expansion behavior data are collected simultaneously. The first deviation rate and the second deviation rate of the soft expansion force curve and the hard expansion force curve before and after the update are calculated respectively, such as root mean square error or maximum relative deviation. If both deviation rates are lower than the preset safety threshold, i.e., the first deviation rate < the preset threshold and the second deviation rate < the preset threshold, it indicates that the new specifications have significantly optimized the expansion control performance. The current update is determined to be a valid parameter update and can be included in the formal design library for the production of the cell battery. Conversely, if either deviation rate exceeds the threshold, it indicates that the adjustment has not achieved the expected effect and may even introduce new risks. The current update will be determined to be an invalid parameter update and an alarm will be triggered to re-analyze the multi-dimensional correlation data or adjust the optimization target to optimize the cell parameters.

[0047] In an exemplary embodiment, after determining that the update of the specification parameters is a valid parameter update when the first deviation rate is less than the first preset deviation rate and the second deviation rate is less than the second preset deviation rate, the method further includes: when the update of the specification parameters is a valid parameter update, locking the values ​​of the parameters after the target specification update and generating a target log of successful target specification update; when the update of the specification parameters is an invalid parameter update, determining to revert the parameters in the target specification to the values ​​before the update and triggering an alarm message of target specification update failure.

[0048] In short, once the first deviation rate is less than the first preset deviation rate and the second deviation rate is less than the second preset deviation rate, confirming that the parameter update is valid, the optimized target parameter specifications, such as the venting chamber volume, electrode compaction density, and safety valve opening pressure, are locked to prevent accidental human error or system drift. Simultaneously, a successful target specification update log is generated, containing key information such as update time, parameter comparison before / after optimization, deviation rate analysis results, and verification test number. If the update is deemed invalid, an automatic rollback mechanism is immediately triggered, restoring the cell design parameters to the baseline version before the update. This ensures the consistency of R&D data and that product safety standards remain unaffected. Simultaneously, a target specification update failure alarm message is sent to the R&D platform and project management terminal, including the reason for the failure (e.g., excessive deviation, unresolved trend), suggested troubleshooting directions (e.g., abnormal test conditions, model parameter mismatch), and related data links, assisting R&D personnel in quickly locating the problem.

[0049] In an exemplary embodiment, after updating the specification parameters of the target specification based on the target preferred value, the above-mentioned cell specification update method further includes: determining the real-time expansion data corresponding to the cell when the battery where the cell is located is activated for the first time or fully charged for the first time; performing similarity matching between the real-time expansion data and the expansion behavior database of historical cells of the same model and batch to obtain the target matching degree; and determining whether the cell is an abnormally operating cell based on the size relationship between the target matching degree and the preset standard matching degree.

[0050] In one exemplary embodiment, determining whether a battery cell is an abnormally operating battery cell based on the magnitude relationship between a target matching degree and a preset standard matching degree includes: marking the battery cell as an abnormally operating battery cell when the magnitude relationship indicates that the target matching degree is less than the preset standard matching degree; and marking the battery cell as a non-abnormally operating battery cell when the magnitude relationship indicates that the target matching degree is greater than or equal to the preset standard matching degree.

[0051] In other words, when the battery cell is first activated or fully charged, its dynamic response data of soft and hard expansion is collected in real time as the initial expansion information of the cell. Then, this real-time data is matched with a database of expansion behavior of historical cells of the same model and batch under the same operating conditions to perform multi-dimensional similarity matching and output the target matching degree. If the target matching degree is higher than the preset standard matching degree, such as ≥90%, it indicates that the expansion behavior of the cell is highly consistent with the historical good product group and is in normal operation. Conversely, if the matching degree is lower than the threshold, it is judged as an abnormal cell, and the cell will be marked and an early warning will be triggered. That is, the cell may have potential defects such as uneven internal materials, insufficient liquid injection, diaphragm wrinkles or abnormal trace gas production, and there is a risk of early failure.

[0052] In an exemplary embodiment, after updating the specification parameters of the target specification based on the target preferred value, the method for updating the cell specification further includes: determining the soft and hard expansion curves corresponding to the cell after the cell completes a preset number of charge-discharge cycles; determining the current expansion degradation value of the cell based on the soft and hard expansion curves and the real-time expansion data corresponding to the first activation or first full charge of the battery in which the cell is located; evaluating the health status of the cell based on the expansion degradation value, and adjusting the charging cycle parameters in the target specification according to the health level corresponding to the health status, wherein the charging cycle parameters include at least one of the following: the maximum allowable charging voltage of the cell, the upper limit of the allowable fast charging rate of the cell, and the maximum allowable number of cycles of the cell.

[0053] Optionally, after updating the cell specifications based on the target optimal values, each time the cell completes a preset number of charge-discharge cycles, such as every 50 or 100 cycles, its current soft expansion and hard expansion curves are collected. Combined with the initial expansion baseline data when the cell is first activated or fully charged, an expansion degradation value is calculated, which comprehensively reflects the relative growth rate and deviation trend of the accumulation of gas production during soft expansion and the thickening / structural degradation of the hard expansion electrode. Subsequently, based on the expansion degradation value mapped to a preset health status assessment model, the current health status of the cell is output. Health ratings are categorized as follows: Grade A: Slight degradation; Grade B: Moderate degradation; Grade C: Significant degradation. Based on the health rating, key charging cycle parameters in the target specifications are dynamically adjusted: Grade A allows maintaining the original fast charging rate and cutoff voltage; Grade B automatically reduces the upper limit of the fast charging rate, such as from 2C to 1.5C, or limits the maximum charging voltage, such as from 4.35V to 4.25V, to mitigate side reactions; Grade C triggers a cycle life warning, limits the number of subsequent cycles, and recommends entering a low-power mode or retiring the device.

[0054] In an exemplary embodiment, after updating the specification parameters of the target specification based on the target preferred value, the cell specification updating method further includes: triggering specification freezing if it is detected that the target preferred value has not reduced the total expansion force after at least three consecutive updates or the actual hard expansion force of the cell exceeds the limit of the cell casing, wherein specification freezing is used to prevent arbitrary operations from changing the specification parameters within the target specification; extracting the parameter values ​​of the frozen specification parameters, and generating an expansion event report corresponding to the cell based on the parameter values, the historical expansion curve corresponding to the cell, and the historical risk type of the battery in which the cell is located.

[0055] In the process of continuously optimizing the cell specifications based on the target optimal values, if it is detected that the target optimal values ​​have failed to effectively reduce the total expansion force after at least three consecutive updates, or if the measured hard expansion force continues to exceed the ultimate stress threshold of the cell casing (e.g., exceeding 80% of the casing yield strength), the specifications are immediately frozen. Any manual or automatic operation is prohibited from modifying the parameters in the target specifications, such as electrode thickness, tightness ratio, and reserved air cavity volume, to prevent the risk of structural failure from accumulating due to repeated trial and error. After freezing, all currently frozen parameter values ​​are extracted and linked with the historical soft and hard expansion curves of the corresponding cell and the failure mode database of the same batch of cells, such as valve opening, shell bulging, thermal runaway records, and historical risk types, to generate a structured and traceable expansion event report. The report covers the parameter evolution path, expansion degradation inflection point, over-limit time node, potential failure mechanism inference, and improvement suggestions.

[0056] In an exemplary embodiment, the method for updating the battery cell specifications further includes: when the battery cell shutdown period is longer than a preset period, collecting target internal air pressure data and expansion force change trends of the battery cell under no-load conditions; calculating the soft expansion rate during the shutdown period based on the target internal air pressure data and expansion force change trends; when the soft expansion rate is greater than a preset soft expansion rate, determining that the battery cell has a risk of electrolyte decomposition, increasing the upper limit of the storage temperature in the target specifications, and reducing the pre-charge voltage when the battery cell is restarted.

[0057] Optionally, to address the hidden gas generation risk caused by self-discharge and slow electrolyte decomposition during long-term cell shutdown, a static health inspection mode is activated when the cell shutdown period exceeds a preset threshold, such as 30 or 90 days. This mode collects the target internal gas pressure change trend and small increments of expansion force of the cell under a completely unloaded, constant-temperature environment. By calculating the rate of soft expansion per unit time, the gas generation activity during the static period is quantitatively assessed. When the calculated soft expansion rate exceeds a preset safety threshold, it is determined that the cell has a continuous gas generation risk caused by electrolyte decomposition or membrane growth, even if it performs normally during operation. At this time, adaptive specification adjustment is triggered: on the one hand, the upper limit of storage temperature in the target specification is increased to reduce the ion migration resistance caused by electrolyte viscosity at low temperatures and slow down the side reaction rate; on the other hand, before the cell is used again, the pre-charge voltage is automatically reduced, and an ultra-low current slow charging strategy is adopted to allow abnormal gases to be released gently at low potential, avoiding rapid gas expansion under high voltage that could cause valve opening or diaphragm rupture.

[0058] In an exemplary embodiment, after updating the specification parameters to which the target specification belongs based on the target preferred value, the above-mentioned method for updating the battery cell specification further includes: after updating the specification parameters to which the target specification belongs based on the target preferred value, comparing the parameter differences between the updated specification parameters and the specification parameters before the update; generating a specification change trend of the battery cell based on the parameter differences, and forwarding the specification change trend to the battery cell R&D object for R&D reference.

[0059] After dynamically updating the cell specifications based on the target optimal values, key parameters before and after the update are compared item by item, such as soft and hard expansion thresholds, tightness ratio, reserved air cavity volume, and maximum charging voltage. The magnitude and direction of parameter changes are quantified, such as a 12% reduction in the hard expansion limit, an 8% increase in pre-tightening force, and a 5% expansion of the gas generation space. Based on the parameter evolution path of multiple iterations, a structured cell specification change trend map is generated. This trend map not only presents the dynamic evolution trajectory of the parameters but also associates the expansion force response, cycle life performance, and failure risk changes corresponding to each adjustment. Subsequently, this trend map is automatically pushed to the cell R&D object as a data reference for the next stage of optimization design, helping the R&D object clearly identify which parameter adjustments effectively suppress expansion and which directions have diminishing marginal benefits, thereby avoiding blind trial and error based on experience.

[0060] To better understand the process of updating the battery cell specifications described above, the following description, in conjunction with optional embodiments, further illustrates the implementation flow of the battery cell specification update method, but is not intended to limit the technical solutions of the embodiments of this application.

[0061] This embodiment provides a method for updating battery cell specifications. Figure 2 This is a schematic flowchart of an expansion parsing process according to an embodiment of this application, such as... Figure 2 As shown, cell expansion includes hard expansion and soft expansion. When locating the cause of failure, if hard expansion is dominant, it is mainly reflected in the growth of the cell surface film and the irreversible expansion of the cell material. If soft expansion is dominant, the dominant operating condition caused by soft expansion is located to provide direction for optimizing the operating conditions.

[0062] Optionally, Figure 3 This is a schematic diagram of the architecture of a battery cell analysis system according to an embodiment of this application, including: testing equipment, an integrated platform, and an analysis module. The integrated platform mainly includes: integrated communication, integrated data relay, and integrated data acquisition. In practical applications, the constructed integrated hardware and software expansion testing platform uses a network port as the main communication interface, replacing the traditional RS485, to achieve multi-node parallel communication between the expansion force sensor, the internal pressure detection module, and the charging and discharging equipment. To address the differentiated sampling frequency requirements at different testing stages, such as 0.1s sampling for charging transients and 600s sampling for storage stages, a high-frequency data relay device is deployed to achieve programmable segmented sampling from 0.1s to 600s, with simultaneous high-precision timestamps. This relay device has channel expansion capabilities, capable of receiving multi-channel signals such as voltage, current, and temperature. After long-term stability testing (>500 hours of continuous operation), data integrity reaches 99.98%, with no packet loss and no clock skew. Ultimately, the system outputs a time-aligned multidimensional data stream, enabling the linked analysis of internal pressure, total expansion force, and charge / discharge curves with millisecond-level precision, providing reliable data support for the correlation between soft and hard expansion decomposition and electrochemical reaction mechanisms.

[0063] Optionally, Figure 4 This is a test result of soft expansion decomposition in storage according to an embodiment of this application; wherein the test scheme involves conducting a long-term storage test on the battery cell under conditions of 60°C, 100% SOC, and 2000N preload, and collecting its internal pressure and total expansion force data. Based on a pre-calibrated soft expansion calculation formula F... soft=0.00627×P+2154.35, dynamic analysis of the real-time gas pressure P was performed to separate the soft expansion component and the hard expansion component. The results show that in the early stage of storage, the hard expansion increases with the thickening of the electrode lithiation, but as the storage time increases, the electrode structure gradually loosens, and the hard expansion decreases instead; while the soft expansion continues to increase due to the continuous decomposition of electrolyte and gas production, which dominates the trend of the total expansion force. This phenomenon confirms that in the storage failure mode of high energy density cells, gas production dominates the growth of soft expansion, while hard expansion exhibits nonlinear behavior in structural evolution, providing a quantitative basis for optimizing cell structure, reserving space, adjusting the tightness ratio, and setting the upper limit of storage temperature.

[0064] It should be noted that A in the above formula refers to the area of ​​the large surface of the battery cell. The specific derivation method is to fix an empty battery cell of the same model on an expansion force device, inflate the empty battery cell with air, and derive the formulas for P and F based on the relationship between air pressure and the expansion force. By comparison, it can be seen that A is close to the area of ​​the large surface of the battery cell, and 2154.35 is close to the preload force applied to the battery cell. Therefore, without further verification, F=P can be used. A+F0 represents the approximate size of the soft expansion caused by air pressure, where A is the large surface area of ​​the battery cell and F0 is the initial preload of the battery.

[0065] Optionally, Figure 5 This is a test result of cyclic soft expansion decomposition according to an embodiment of this application; it mainly involves the trend change between capacity retention and soft and hard expansion. Specifically, a 100% SOC cell is subjected to 1 / 2C charging and 1C discharging cycle test under 25°C and 2000N preload conditions. Based on the calibrated soft expansion formula F... soft =0.00627×P+2154.35, where P is the internal pressure and F is the internal pressure. soft For soft expansion force, the soft expansion component in each cycle is calculated in real time, and then expressed through F. hard =F total -F soft Separation of hard expansion. Results show that in the first 100 cycles, when the internal pressure is below 20 kPa, the hard expansion F... hard The total expansion force F total The dominant factors are electrode volume expansion and continuous SEI film growth. After 200 cycles, soft expansion increases significantly, and by 300 cycles, the proportion of soft expansion force exceeds that of hard expansion, which intensifies in tandem with the capacity decay trend. This indicates that gas generation has become the core cause of capacity decay and uncontrolled expansion in the later stages of cycling. This phenomenon reveals the evolutionary path of cell failure from structure-dominated to gas-dominated.

[0066] As an optional implementation, after completing the expansion behavior analysis, relevant components of the battery cell can be adjusted for verification. For example, the differences between Scheme 1 and Scheme 2 can be compared through test results. Specifically, Figure 6 This is a cell expansion trend diagram according to an embodiment of this application, showing the expansion force of the battery cell under different buffer pads. Scheme 1 involves adjusting the size of the buffer pad and introducing waveform gas to monitor the expansion force trend of the battery cell. Scheme 2 involves not adding a buffer pad to the battery cell, adjusting the preload, and introducing waveform gas to monitor the expansion force trend of the battery cell. Without buffer pad: F = 0.0080P + 186; with buffer pad: F = 0.0079P + 138; with U-shaped frame: F = 0.0081P + 175. It can be seen that the expansion force F and pressure P show a linear relationship under different test conditions; the slopes in all fitting formulas are smaller than the actual large surface area of ​​the battery; and the slopes in the fitting formulas measured under different test conditions are close.

[0067] Furthermore, the changes in expansion behavior can be verified by adjusting different preload forces. Figure 7 This is a trend chart of cell preload variation according to an embodiment of this application, including: F=0.0061P+3513 when the preload is 3000N; F=0.0063P+2154 when the preload is 2000N; and F=0.0071P+907 when the preload is 1000N.

[0068] It should be noted that, based on actual results and the formula F=P A. Difference Analysis. 33221 cell large surface area: 220.8 mm. 105.88 10 -6 =0.0234, actual slope: 0.006~0.008. Figure 8 This diagram illustrates the expansion and contraction of a battery cell according to an embodiment of this application. The phenomenon of the cell being thicker in the middle and thinner around the edges is likely due to a reduction in the contact area between the cell and the clamping plate. Specifically, there are several possibilities: during battery expansion, deformation of the large surface area of ​​the cell causes a difference between the actual contact interface area S' and the original cell area S; bulging of the other four sides of the cell further thins the perimeter, further reducing the contact area; slight displacement and deformation of the expansion force fixture during battery expansion may occur, increasing the clamping distance and reducing the contact area between the cell and the clamping plate; or unevenness of the cell casing itself results in a contact area with the clamping plate that is smaller than the actual large surface area.

[0069] Optional, Figure 9This is a soft and hard expansion analysis diagram of a battery cell during charging and discharging according to an embodiment of this application. During a single discharge, the expansion force of the battery cell decreases, increases, and then decreases again, while the internal pressure first increases and then decreases. The changes in expansion force and internal pressure during battery charging are exactly the opposite of those during discharging. Before the cell reaches 70% SOC, both expansion force and internal pressure increase. From 70% to 95% SOC, the internal pressure gradually decreases, while the expansion force first decreases and then increases. After 95% SOC, the expansion force gradually decreases again. After 100 cycles, the voltage curve of the cell shows no significant change from the initial value. The expansion force values ​​near 0% SOC and 100% SOC are also similar, and the curve changes are consistent. However, the expansion force increase of the BOL battery during the low to medium SOC period is significantly smaller than that of the cell after 100 cycles. Combining the internal pressure and voltage comparison chart, it can be seen that the internal pressure of the cell is less than 0 during charge and discharge cycles in the BOL state. Therefore, the cell expansion is all hard expansion. After 100 cycles, the internal pressure of the cell increases to about 10 kPa. Therefore, the faster increase in battery expansion force after 100 cycles is likely mainly due to the increase in internal pressure of the cell.

[0070] Through the above embodiments, by simultaneously collecting the total expansion force and internal pressure data of the battery cell under two typical operating conditions—60℃, 100% SOC, 2000N preload and cyclic charging / discharging at 25℃, 1 / 2C, 2.5–4.25V, and 2000N preload—and using a unified calibration formula F, the data were analyzed. soft =0.00627×P+2154.35 The soft expansion component is dynamically calculated, and the hard expansion component is separated from it, thus decoupling the physical mechanism of cell expansion behavior. The test platform adopts a network communication architecture and high-frequency data relay equipment to achieve high-precision time alignment and synchronous acquisition of multi-source signals such as expansion force, internal pressure, voltage, current, and temperature. During storage, soft expansion continuously increases, while hard expansion first increases and then decreases, and the total expansion force shows a trend of first increasing and then decreasing. During cycling, the initial expansion is dominated by hard expansion, and as the cycle progresses, soft expansion accelerates and becomes dominant. In the 1 / 3C charging range of 70%–95% SOC, a decoupling phenomenon occurs where the internal pressure decreases and the expansion force rebounds. The above tests improve the efficiency of locating expansion failure under static design.

[0071] Through the above description of the embodiments, those skilled in the art can clearly understand that the methods according to the above embodiments can be implemented by means of software plus necessary general-purpose hardware platforms. Of course, they can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a software product. This computer software product is stored in a storage medium (such as ROM / RAM, magnetic disk, optical disk) and includes several instructions to cause a computing device (which may be a mobile phone, computer, server, or network device, etc.) to execute the methods of the various embodiments of this application.

[0072] Figure 10 This is a structural block diagram of a battery according to an embodiment of this application; as shown below. Figure 10 As shown, it includes: a battery 1102 and a cell analysis system 1104 that is communicatively connected to the battery 1102.

[0073] Battery 1102 is configured such that the expansion parameter value corresponding to the target specification of the cell is within a preset safe expansion threshold range, wherein the expansion parameter value is determined by a cell analysis system that is connected to the battery in communication.

[0074] The cell analysis system 1104 is used to: collect total expansion force data and internal air pressure data of the cell during charging, discharging or storage; process the internal air pressure data through a preset soft expansion function to obtain the soft expansion force component of the cell at each sampling time, and determine the corresponding hard expansion force component of the cell based on the total expansion force data and the soft expansion force component; align the soft expansion force component and the hard expansion force component with the synchronously collected voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset; determine the target optimal value corresponding to the expansion parameter value based on the multidimensional correlation dataset and the battery's usage environment, and update the specification parameters to which the target specification belongs based on the target optimal value.

[0075] Based on the above, a battery configuration is proposed where the expansion parameter values ​​corresponding to the target specifications of the battery cells are within a preset safe expansion threshold range. A cell analysis system connected to the battery determines the parameter values ​​for detection. This system then collects total expansion force data and internal pressure data of the battery cells during charging, discharging, or storage. The internal pressure data is processed using a preset soft expansion function to obtain the soft expansion force component of the battery cell at each sampling moment. Based on the total expansion force data and the soft expansion force component, the corresponding hard expansion force component of the battery cell is determined. The soft and hard expansion force components are aligned with the synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset. Based on the multidimensional correlation dataset and the battery's operating environment, a target optimal value corresponding to the expansion parameter values ​​is determined, and the specification parameters of the target specifications are updated based on the target optimal value. Using this technical solution, a battery cell expansion can be monitored through a built-in or external cell analysis system. Precise perception and proactive control of behavior: First, the total expansion force and internal air pressure data of the battery cell during charging, discharging, or storage are collected synchronously. The air pressure signal is converted into a soft expansion force component using a preset soft expansion function. By subtracting the soft expansion force from the total expansion force, the hard expansion force component caused by solid deformation such as electrode thickening is decoupled. Subsequently, these two key mechanical components are precisely aligned with the synchronously collected voltage and capacity curves in the time dimension to construct a multi-dimensional correlation dataset covering mechanical, electrochemical, and environmental factors. Based on this, the dataset is comprehensively analyzed in conjunction with the actual battery usage environment to calculate the most suitable target value under the current operating conditions, i.e., the optimal expansion control target. This automatically triggers dynamic adjustments to the battery cell design specifications, thereby achieving control over battery expansion behavior in the early stages of battery manufacturing. This solves the technical problems of low efficiency in analyzing battery expansion behavior and the inability to dynamically adjust battery cell specifications based on analysis results to adapt to the actual usage environment, thus improving battery safety.

[0076] In an exemplary embodiment, the cell analysis system is further configured to: compare the preferred hard expansion value in the target preferred value with the hard expansion limit value in the target specification to obtain a first comparison result; compare the preferred soft expansion value in the target preferred value with the soft expansion limit value in the target specification to obtain a second comparison result; and generate a cell design adjustment strategy corresponding to the target specification based on the first comparison result and the second comparison result.

[0077] In an exemplary embodiment, the cell analysis system is further configured to: determine a cell design adjustment strategy as a first strategy when the first comparison result indicates that the preferred value of hard expansion is greater than or equal to the hard expansion limit value, wherein the first strategy includes at least one of the following: reducing the compaction density of the upper electrode sheet of the cell and increasing the porosity of the separator inside the cell; and determine a cell design adjustment strategy as a second strategy when the second comparison result indicates that the preferred value of soft expansion is greater than or equal to the soft expansion limit value, wherein the second strategy includes at least one of the following: increasing the volume of the venting chamber near the cell and increasing the opening pressure of the safety valve connected to the cell.

[0078] In an exemplary embodiment, the cell analysis system is further configured to: prohibit the output of cell design adjustment strategies when a first comparison result indicates that the preferred value of hard expansion is less than the hard expansion limit or a second comparison result indicates that the preferred value of soft expansion is less than the soft expansion limit.

[0079] In an exemplary embodiment, the cell analysis system is further configured to: trigger a composite adjustment strategy when the first comparison result indicates that the preferred value of hard expansion is greater than or equal to the hard expansion limit value, and the second comparison result indicates that the preferred value of soft expansion is greater than or equal to the soft expansion limit value, wherein the composite adjustment strategy is to first perform venting chamber adjustment and then perform electrode structure adjustment.

[0080] In an exemplary embodiment, the cell analysis system is further configured to: enter a verification loop mode after the specification parameters have been updated, wherein the verification loop mode is configured to determine the deviation rates of different expansion behaviors before and after the specification parameters have been updated; calculate a first deviation rate of soft expansion behavior and a second deviation rate of hard expansion behavior output by the verification loop mode; determine that the update of the specification parameters is a valid parameter update if the first deviation rate is less than a first preset deviation rate and the second deviation rate is less than a second preset deviation rate; and determine that the update of the specification parameters is an invalid parameter update if the first deviation rate is greater than or equal to the first preset deviation rate and / or the second deviation rate is greater than or equal to the second preset deviation rate.

[0081] In an exemplary embodiment, the cell analysis system is further configured to: lock the values ​​of the updated parameters of the target specification when the update of the specification parameters is a valid parameter update, and generate a target log indicating that the target specification has been successfully updated; and determine to revert the parameters in the target specification to their values ​​before the update when the update of the specification parameters is an invalid parameter update, and trigger an alarm message indicating that the target specification update has failed.

[0082] In an exemplary embodiment, the cell analysis system is further configured to: determine the real-time expansion data corresponding to the cell when the battery containing the cell is first activated or fully charged for the first time; perform similarity matching between the real-time expansion data and a database of expansion behavior of historical cells of the same model and batch to obtain a target matching degree; and determine whether the cell is an abnormally operating cell based on the relationship between the target matching degree and the preset standard matching degree.

[0083] In an exemplary embodiment, the cell analysis system is further configured to: mark a cell as an abnormally operating cell when the target matching degree of the size relationship indicator is less than a preset standard matching degree; and mark a cell as a non-abnormally operating cell when the target matching degree of the size relationship indicator is greater than or equal to the preset standard matching degree.

[0084] In an exemplary embodiment, the cell analysis system is further configured to: determine the soft and hard expansion curves corresponding to the cell after the cell completes a preset number of charge-discharge cycles; determine the current expansion degradation value of the cell based on the soft and hard expansion curves and real-time expansion data corresponding to the first activation or first full charge of the battery in which the cell is located; evaluate the health status of the cell based on the expansion degradation value, and adjust the charging cycle parameters in the target specification according to the health level corresponding to the health status, wherein the charging cycle parameters include at least one of the following: the maximum allowable charging voltage of the cell, the maximum allowable fast charging rate of the cell, and the maximum allowable number of cycles of the cell.

[0085] In an exemplary embodiment, the cell analysis system is further configured to: trigger specification freezing when it is detected that the target preferred value has not been reduced in terms of total expansion force after at least three consecutive updates or that the actual hard expansion force of the cell exceeds the limit of the cell casing, wherein specification freezing is used to prohibit arbitrary operations from changing the specification parameters within the target specification; extract the parameter values ​​of the frozen specification parameters, and generate an expansion event report corresponding to the cell based on the parameter values, the historical expansion curve corresponding to the cell, and the historical risk type of the battery in which the cell is located.

[0086] In an exemplary embodiment, the cell analysis system is further configured to: collect target internal air pressure data and expansion force change trends of the cell under no-load conditions when the cell shutdown period is longer than a preset period; calculate the soft expansion rate during the shutdown period based on the target internal air pressure data and expansion force change trends; determine that the cell has a risk of electrolyte decomposition when the soft expansion rate is greater than the preset soft expansion rate, increase the upper limit of the storage temperature in the target specification, and reduce the pre-charge voltage when the cell is restarted.

[0087] In an exemplary embodiment, the cell analysis system is further configured to: after updating the specification parameters to which the target specification belongs based on the target preferred value, compare the parameter differences between the updated specification parameters and the specification parameters before the update; generate a specification change trend of the cell based on the parameter differences, and forward the specification change trend to the cell's R&D object for R&D reference.

[0088] Embodiments of this application also provide a storage medium including a stored program, wherein the program executes any of the methods described above when it is run.

[0089] Optionally, in this embodiment, the storage medium may be configured to store program code for performing the following steps:

[0090] S1, acquire the total expansion force data and internal air pressure data of the battery cell during charging, discharging or storage;

[0091] S2, the internal air pressure data is processed by a preset soft expansion function to obtain the soft expansion force component of the cell at each sampling time, and the hard expansion force component of the cell is determined based on the total expansion force data and the soft expansion force component.

[0092] S3. Align the soft expansion force component and the hard expansion force component with the synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset.

[0093] S4. Determine the target preferred value corresponding to the expansion parameter value based on the multidimensional association dataset and the battery usage environment, and update the specification parameters to which the target specification belongs based on the target preferred value.

[0094] Embodiments of this application also provide an electronic device including a memory and a processor, wherein the memory stores a computer program and the processor is configured to run the computer program to perform the steps in any of the above method embodiments.

[0095] Optionally, the electronic device may further include a transmission device and an input / output device, wherein the transmission device is connected to the processor and the input / output device is connected to the processor.

[0096] Optionally, in this embodiment, the processor can be configured to perform the following steps via a computer program:

[0097] S1, acquire the total expansion force data and internal air pressure data of the battery cell during charging, discharging or storage;

[0098] S2, the internal air pressure data is processed by a preset soft expansion function to obtain the soft expansion force component of the cell at each sampling time, and the hard expansion force component of the cell is determined based on the total expansion force data and the soft expansion force component.

[0099] S3. Align the soft expansion force component and the hard expansion force component with the synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset.

[0100] S4. Determine the target preferred value corresponding to the expansion parameter value based on the multidimensional association dataset and the battery usage environment, and update the specification parameters to which the target specification belongs based on the target preferred value. Optionally, in this embodiment, the above-mentioned storage medium may include, but is not limited to, various media capable of storing program code such as: USB flash drive, read-only memory (ROM), random access memory (RAM), portable hard drive, magnetic disk, or optical disk.

[0101] Optionally, embodiments of this application also provide a computer program product, which includes a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0102] Optionally, embodiments of this application also provide another computer program product, including a non-volatile computer-readable storage medium storing a computer program that, when executed by a processor, implements the steps in any of the above method embodiments.

[0103] Optionally, embodiments of this application also provide a computer program that includes computer instructions stored in a computer-readable storage medium; a processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the steps in any of the above method embodiments.

[0104] Optionally, embodiments of this application also provide a battery pack including at least two batteries from the above embodiments, each of which is electrically connected to the other.

[0105] It should be noted that the batteries mentioned above are, for example, single-cell batteries.

[0106] Optionally, embodiments of this application also provide a battery pack, including a housing and at least two battery packs as described in the above embodiments, each battery pack being disposed within the housing and electrically connected to each other.

[0107] Optionally, embodiments of this application also provide an electric vehicle including the battery pack described in the above embodiments.

[0108] Optionally, specific examples in this embodiment can refer to the examples described in the above embodiments and optional implementations, and will not be repeated here.

[0109] Obviously, those skilled in the art should understand that the modules or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device. In some cases, the steps shown or described can be performed in a different order than those presented here, or they can be fabricated as separate integrated circuits, or multiple modules or steps can be fabricated as a single integrated circuit. Thus, this application is not limited to any particular hardware and software combination.

[0110] The above description is only a preferred embodiment of this application. It should be noted that for those skilled in the art, several improvements and modifications can be made without departing from the principle of this application, and these improvements and modifications should also be considered within the scope of protection of this application.

Claims

1. A battery, characterized in that, The battery includes at least one cell, and the expansion parameter value corresponding to the target specification adopted by the cell is within a preset safe expansion threshold range. The expansion parameter value is determined by a cell analysis system that is communicatively connected to the battery. The cell analysis system is used for: Collect data on the total expansion force and internal air pressure of the battery cell during charging, discharging, or storage. The internal air pressure data is processed by a preset soft expansion function to obtain the soft expansion force component of the battery cell at each sampling time, and the hard expansion force component of the battery cell is determined based on the total expansion force data and the soft expansion force component. Align the soft expansion force component and the hard expansion force component with the synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset. The target preferred value corresponding to the expansion parameter value is determined based on the multidimensional association dataset and the battery usage environment, and the specification parameters to which the target specification belongs are updated based on the target preferred value.

2. The battery according to claim 1, characterized in that, The cell analysis system is also used for: The preferred value for hard expansion in the target preferred value is compared with the limit value for hard expansion in the target specification to obtain the first comparison result; The preferred soft expansion value in the target preferred value is compared with the soft expansion limit value in the target specification to obtain a second comparison result; Based on the first comparison result and the second comparison result, a cell design adjustment strategy corresponding to the target specification is generated.

3. The battery according to claim 2, characterized in that, The cell analysis system is also used for: If the first comparison result indicates that the preferred value of hard expansion is greater than or equal to the limit value of hard expansion, the cell design adjustment strategy is determined to be the first strategy, wherein the first strategy includes at least one of the following: reducing the compaction density of the upper electrode sheet of the cell and increasing the porosity of the separator inside the cell. If the second comparison result indicates that the preferred value of soft expansion is greater than or equal to the limit value of soft expansion, the cell design adjustment strategy is determined to be the second strategy, wherein the second strategy includes at least one of the following: increasing the volume of the venting chamber near the cell, or increasing the opening pressure of the safety valve connected to the cell.

4. The battery according to claim 2, characterized in that, The cell analysis system is also used for: If the first comparison result indicates that the preferred value of hard expansion is less than the limit value of hard expansion, or if the second comparison result indicates that the preferred value of soft expansion is less than the limit value of soft expansion, the cell design adjustment strategy shall be prohibited from being output.

5. The battery according to claim 2, characterized in that, The cell analysis system is also used for: If the first comparison result indicates that the preferred value of hard expansion is greater than or equal to the limit value of hard expansion, and the second comparison result indicates that the preferred value of soft expansion is greater than or equal to the limit value of soft expansion, a composite adjustment strategy is triggered, wherein the composite adjustment strategy is to first perform venting chamber adjustment and then perform electrode structure adjustment.

6. The battery according to claim 1, characterized in that, The cell analysis system is also used for: Once the specification parameters have been updated, the system enters a verification loop mode, which is used to determine the deviation rate of different expansion behaviors before and after the specification parameters have been updated. Calculate the first deviation rate of the soft expansion behavior and the second deviation rate of the hard expansion behavior output by the verification loop mode; If the first deviation rate is less than the first preset deviation rate and the second deviation rate is less than the second preset deviation rate, the update of the specification parameter is determined to be a valid parameter update. If the first deviation rate is greater than or equal to the first preset deviation rate, and / or the second deviation rate is greater than or equal to the second preset deviation rate, the update of the specification parameter is determined to be an invalid parameter update.

7. The battery according to claim 6, characterized in that, The cell analysis system is also used for: If the update of the specification parameters is a valid parameter update, the updated parameters of the target specification are locked, and a target log of the successful update of the target specification is generated. If the update of the specification parameter is an invalid parameter update, determine to revert the parameter in the target specification to the value before the update, and trigger an alarm message indicating that the target specification update failed.

8. The battery according to claim 1, characterized in that, The cell analysis system is also used for: When the battery containing the cell is activated for the first time or fully charged for the first time, the real-time expansion data corresponding to the cell is determined. The real-time expansion data is matched with the historical expansion behavior database of cells of the same model and batch to obtain the target matching degree. The determination of whether a battery cell is an abnormally operating cell is based on the relationship between the target matching degree and the preset standard matching degree.

9. The battery according to claim 8, characterized in that, The cell analysis system is also used for: If the size relationship indicates that the target matching degree is less than the preset standard matching degree, the cell is marked as an abnormally operating cell; If the size relationship indicates that the target matching degree is greater than or equal to the preset standard matching degree, the cell is marked as a non-abnormal operating cell.

10. The battery according to claim 1, characterized in that, The cell analysis system is also used for: After the battery cell completes a preset number of charge-discharge cycles, the soft and hard expansion curve of the battery cell is determined. Based on the soft and hard expansion curves and the real-time expansion data corresponding to the first activation or first full charge of the battery cell, the current expansion degradation value of the battery cell is determined. The health status of the battery cell is assessed based on the expansion degradation value, and the charging cycle parameters in the target specification are adjusted according to the health level corresponding to the health status. The charging cycle parameters include at least one of the following: the maximum allowable charging voltage of the battery cell, the maximum allowable fast charging rate of the battery cell, and the maximum allowable number of cycles of the battery cell.

11. The battery according to claim 1, characterized in that, The cell analysis system is also used for: If the target preferred value is updated at least three times consecutively without reducing the total expansion force or the actual hard expansion force of the cell exceeds the limit of the cell casing, a specification freeze is triggered. The specification freeze is used to prevent any operation from changing the specification parameters within the target specification. Extract the parameter values ​​of the frozen specifications, and generate an expansion event report for the cell based on the parameter values, the historical expansion curve of the cell, and the historical risk type of the battery in which the cell is located.

12. The battery according to claim 1, characterized in that, The cell analysis system is also used for: When the battery cell shutdown period is longer than a preset period, the target internal air pressure data and expansion force change trend of the battery cell under no-load conditions are collected. The soft expansion rate during the shutdown period is calculated based on the target's internal air pressure data and the expansion force change trend. If the soft expansion rate is greater than the preset soft expansion rate, it is determined that the battery cell has a risk of electrolyte decomposition, and the upper limit of the storage temperature in the target specification is increased, and the pre-charge voltage when the battery cell is reused is reduced.

13. The battery according to claim 1, characterized in that, The cell analysis system is also used for: After updating the specification parameters of the target specification based on the target preferred value, the parameter differences between the updated specification parameters and the specification parameters before the update are compared. Based on the parameter differences, a specification change trend of the battery cell is generated, and the specification change trend is forwarded to the research and development object of the battery cell for research and development reference.

14. A method for updating battery cell specifications, characterized in that, A cell analysis system used in communication with batteries includes: Acquire total expansion force data and internal air pressure data of the battery cell during charging, discharging, or storage; The internal air pressure data is processed by a preset soft expansion function to obtain the soft expansion force component of the battery cell at each sampling time, and the hard expansion force component of the battery cell is determined based on the total expansion force data and the soft expansion force component. Align the soft expansion force component and the hard expansion force component with the synchronously acquired voltage and capacity curves on the time axis to obtain a multidimensional correlation dataset. The target preferred value corresponding to the expansion parameter value is determined based on the multidimensional association dataset and the battery usage environment, and the specification parameters to which the target specification belongs are updated based on the target preferred value.

15. A battery pack, characterized in that, It includes at least two batteries as described in any one of claims 1 to 13, each of which is electrically connected to the other.

16. A battery pack, characterized in that, It includes a housing and at least two battery packs as described in claim 15, each of the battery packs being disposed within the housing and electrically connected to each other.

17. An electric vehicle, characterized in that, Includes the battery pack as described in claim 16.

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