Method for managing a battery in expansion and related devices, systems and apparatuses

Abstract

The application discloses a capacity expansion battery management method and a related device, system and equipment, and relates to the technical field of battery management. The capacity expansion battery management method comprises the following steps: acquiring a voltage differential-capacity curve of a capacity expansion battery in a charging process, and determining a working stage of the capacity expansion battery according to the change trend of the voltage differential-capacity curve at different times; wherein the voltage differential is the differential of the voltage with respect to the capacity; in the case that the current working stage of the capacity expansion battery is in a first preset stage, the capacity expansion battery is managed based on a first voltage management curve; and in the case that the current working stage of the capacity expansion battery is in a second preset stage, the capacity expansion battery is managed based on a second voltage management curve. The capacity expansion battery management method provided by the application can improve the management accuracy when the capacity expansion battery is charged and discharged.

Description

Technical Field

[0001] This application relates to the field of battery management technology, and in particular to a method for managing extended-capacity batteries and related devices, systems and equipment. Background Technology

[0002] Extended-capacity batteries can compensate for the loss of active media during battery formation and long-term cycling, thereby extending cycle life. However, during use, as the internal pre-set capacity is gradually consumed, the internal thermodynamic equilibrium state of extended-capacity batteries will continuously shift, leading to inaccurate estimation of battery status and resulting in low management precision. Summary of the Invention

[0003] The main purpose of this application is to propose a method for managing extended capacity batteries and related devices, systems and equipment, which aims to improve the management accuracy when managing the charge and discharge of extended capacity batteries.

[0004] To achieve the above objectives, in a first aspect, this application provides a method for managing a capacity-enhancing battery. The method includes: acquiring a voltage differential-capacity curve of the capacity-enhancing battery during charging, wherein the voltage differential is the differential of voltage with respect to capacity; determining the operating stage of the capacity-enhancing battery based on the changing trend of the voltage differential-capacity curve at different times; managing the capacity-enhancing battery based on a first voltage management curve when the current operating stage of the capacity-enhancing battery is in a first preset stage, wherein the first voltage management curve characterizes the voltage characteristics of the capacity-enhancing battery in a state where the capacity expansion is not depleted; and managing the capacity-enhancing battery based on a second voltage management curve when the current operating stage of the capacity-enhancing battery is in a second preset stage, wherein the second voltage management curve characterizes the voltage characteristics of the capacity-enhancing battery in a state where the capacity expansion is depleted.

[0005] In this embodiment, the voltage differential-capacity curve offset law of the expanded capacity battery during the charging process is utilized to determine the working stage (i.e., the degradation stage) of the expanded capacity battery. When it is confirmed that the expanded capacity battery is in a first preset stage where the additional capacity has not been exhausted, a first voltage management curve is matched for it; when it is determined that the additional capacity has been exhausted and the battery has crossed the physical aging inflection point and entered a second preset stage, a second voltage management curve is matched for it. In this way, it conforms to the underlying physical evolution law of the expanded capacity battery, matches different management curves for different working stages, eliminates the cumulative error caused by management curve mismatch, and thus improves the management accuracy when charging and discharging the expanded capacity battery. For example, it can improve the estimation accuracy of SOC and SOH of the expanded capacity battery throughout its entire life cycle.

[0006] In some implementations, the first preset stage is a positive electrode capacity limiting stage.

[0007] In this embodiment, by defining the first preset stage as the positive electrode capacity limitation stage, the current lithium-rich health state of the battery can be accurately confirmed. Thus, when the first voltage management curve is invoked, the energy of the expanded battery in the early and middle stages of operation can be fully and safely released, improving the management accuracy of the expanded battery when it is in the positive electrode capacity limitation stage.

[0008] In some implementations, the second preset stage is an active lithium restriction stage.

[0009] In this embodiment, by defining the second preset stage as the active lithium limitation stage, when the battery ages to this stage, it is possible to avoid continuing to use the previous first voltage management curve for estimation strategies, thereby avoiding serious thermal runaway risks such as overcharging, over-discharging, and even lithium plating on the negative electrode. This fundamentally ensures the safety baseline in the later stages of the battery's lifespan and improves the management accuracy of expanded capacity batteries in the active lithium limitation stage.

[0010] In some implementations, both the first voltage management curve and the second voltage management curve are open-circuit voltage-state-of-charge curves.

[0011] In this embodiment, the first open-circuit voltage-state-of-charge curve or the second open-circuit voltage-state-of-charge curve that matches the current actual physical degradation state of the battery is dynamically matched. This overcomes the management curve mismatch problem caused by the traditional battery management system using the same open-circuit voltage-state-of-charge curve throughout the entire life cycle of the expanded battery, and improves the management accuracy when managing the charging and discharging of the expanded battery.

[0012] In some embodiments, obtaining the voltage differential-capacity curve of the expanded capacity battery during the charging process and determining the working stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times includes: obtaining the voltage differential-capacity curve of the expanded capacity battery during the charging process; and determining the working stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times.

[0013] In this embodiment, due to manufacturing tolerances between different individual batteries and the measurement drift of the battery management system's sensors over time, using absolute thresholds often leads to misjudgments. However, this embodiment achieves a self-calibration diagnostic mechanism unaffected by hardware drift by tracking the relative change trend of the voltage derivative-capacity curve over time, thereby accurately tracking the evolution of active medium consumption within the expanded capacity battery.

[0014] In some embodiments, obtaining the voltage differential-capacity curve of the expanded battery during the charging process includes: obtaining the current voltage of the expanded battery while it is being charged, and determining a corresponding target voltage acquisition range based on the obtained current voltage; within the target voltage acquisition range, obtaining the charging voltage and charging current of the expanded battery at a preset frequency; and determining the voltage differential-capacity curve of the expanded battery during the charging process based on the obtained charging voltage and charging current.

[0015] In this embodiment of the application, the above settings can eliminate invalid data interference in the initial transient region and the polarization region of charging, ensuring the signal-to-noise ratio and feature integrity of the voltage differential-capacity curve, and also reduce the system storage burden and computational load caused by full-range data acquisition.

[0016] In some embodiments, before acquiring the current voltage of the expanded battery and determining the corresponding target voltage acquisition interval based on the acquired current voltage when the expanded battery is charging, the expanded battery management method further includes: acquiring the capacity differential-voltage curve of the expanded battery; dividing the capacity differential-voltage curve into multiple voltage intervals along the voltage horizontal axis based on the capacity differential peak of the acquired capacity differential-voltage curve, wherein each voltage interval corresponds to at least one capacity differential peak, and the target voltage acquisition interval is selected from the multiple voltage intervals.

[0017] In this embodiment, by pre-acquiring the capacity differential-voltage curve and dynamically dividing the voltage range based on its characteristic peaks, precise focusing of the target acquisition window is achieved. This solves the problem of feature loss caused by phase transition plateau displacement due to individual battery differences or aging. Simultaneously, it ensures that subsequent data sampling is performed within the most sensitive or representative voltage range. Thus, while reducing redundant system computation, the adaptive capability and accuracy of the working phase judgment logic are improved.

[0018] In some implementations, determining the voltage differential-capacity curve of the expanded battery during the charging process based on the acquired charging voltage and charging current includes: obtaining the cumulative charging capacity within the target voltage acquisition range based on the charging current; determining the differential value of the charging voltage with respect to the cumulative charging capacity; and establishing the correspondence between the differential value and the cumulative charging capacity to generate the voltage differential-capacity curve.

[0019] In this embodiment, the time dimension is first converted into a cumulative capacity axis by current integration. Then, the voltage signal is amplified into a differential characteristic value by voltage-capacity differential calculation. Finally, the mapping relationship between the two is established to generate a voltage differential-capacity curve that reflects the internal phase transition state, providing a data benchmark for subsequent determination of the aging stage by capturing characteristic peak shifts.

[0020] In some embodiments, acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range includes: acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range when the expanded battery is in constant current charging mode.

[0021] In this embodiment of the application, by acquiring data in constant current charging mode, it is possible to ensure that there is better linearity between capacity increment and time increment, and eliminate the nonlinear interference caused by current fluctuations to differential calculation.

[0022] In some embodiments, when the expanded battery is in constant current charging mode, acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range includes: when the expanded battery is in constant current charging mode and the real-time charging rate is less than a preset rate threshold, acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range.

[0023] In this embodiment, under high-current charging conditions, the internal ohmic resistance and electrode polarization of the battery will generate a significant voltage drop, causing the voltage curve to deviate from the thermodynamic equilibrium state, resulting in a false shift of the characteristic peak. By collecting data at a low rate, the battery can be kept in a quasi-static equilibrium process to the maximum extent, thereby capturing the purest characteristic peak position with the smallest shift error, thus improving the accuracy of judging the working stage of the expanded capacity battery.

[0024] In some embodiments, determining the operating stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times includes: determining the offset direction and corresponding offset amount between the voltage differential-capacity curves at at least two different times; and determining the operating stage of the expanded capacity battery based on the determined offset direction and corresponding offset amount.

[0025] In this embodiment, by extracting the offset direction and offset amount of the voltage differential-capacity curve at different times, a two-dimensional vector feature for evaluating the internal state evolution (operating stage) of the expanded capacity battery is constructed. In this way, the macroscopic electrical signal waveform is transformed into microscopic indicators of electrode material slippage and active dielectric loss. The offset amount is used to quantify the degree of loss, and the offset direction is used to confirm the aging mechanism. Thus, the operating stage of the expanded capacity battery can be accurately determined, improving the management accuracy when managing charge and discharge at different operating stages.

[0026] In some embodiments, determining the operating stage of the expanded capacity battery based on the determined offset direction and corresponding offset amount includes: determining that the expanded capacity battery is in a first preset stage when the voltage differential-capacity curve at the current moment shifts towards a higher capacity direction relative to the voltage differential-capacity curve at a historical moment, and the offset amount is greater than a first preset offset amount; determining that the expanded capacity battery is in a second preset stage when the voltage differential-capacity curve at the current moment shifts towards a higher capacity direction relative to the voltage differential-capacity curve at a historical moment, and the offset amount is not greater than the first preset offset amount; and determining that the expanded capacity battery is in a second preset stage when the voltage differential-capacity curve at the current moment shifts towards a lower capacity direction relative to the voltage differential-capacity curve at a historical moment.

[0027] In this embodiment of the application, this delineation logic effectively filters out random noise from a single sampling, locks in the physical inflection point where the battery aging mechanism undergoes a fundamental switch, and thus accurately determines the working stage of the expanded battery.

[0028] In some implementations, determining the offset direction and corresponding offset amount between the voltage differential-capacity curves at at least two different times includes: determining a first peak capacity corresponding to a characteristic peak in the voltage differential-capacity curve at the current time, and a second peak capacity corresponding to a characteristic peak in the voltage differential-capacity curve at a historical time; calculating the difference between the first peak capacity and the second peak capacity; if the difference is positive, determining the offset direction as an offset towards higher capacity; if the difference is negative, determining the offset direction as an offset towards lower capacity; and determining the absolute value of the difference as the corresponding offset amount.

[0029] In this embodiment, the capacity coordinates of characteristic peaks from the same source at different times are extracted. By subtracting historical values ​​from the current value, the physical direction of the displacement is qualitatively determined directly using the sign of the difference. Then, the absolute value of the difference is used to quantitatively extract the absolute span of the displacement. Thus, a method for determining the working stage with high accuracy and low computational complexity is provided.

[0030] In some embodiments, determining the operating stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times includes: determining the offset direction between the voltage differential-capacity curves at at least two different times; and determining the operating stage of the expanded capacity battery based on the determined offset direction.

[0031] In this embodiment, the dominant relationship of active lithium loss and the safety of the aging path within the battery are macroscopically audited by tracking the lateral shift polarity (leftward or rightward) of the characteristic peak on the capacity axis. This determination mechanism, which relies purely on directional changes, can capture atypical physical reversals caused by the depletion of the capacity-enhancing medium while eliminating the need for threshold calibration. This improves the robustness of decision-making in complex operating conditions and reduces computational complexity.

[0032] Secondly, this application provides a battery management system configured to implement the capacity expansion battery management method described above.

[0033] Thirdly, this application provides a battery device that includes the battery management system described above.

[0034] Fourthly, this application provides an electrical device, which includes: an extended capacity battery and a battery management system as described above or a battery device as described above. Attached Figure Description

[0035] 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, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on the structures shown in these drawings without creative effort.

[0036] Figure 1 A flowchart of the first embodiment of the battery capacity management method provided in this application; Figure 2 A flowchart of the second embodiment of the battery capacity management method provided in this application; Figure 3 A flowchart of the third embodiment of the extended battery management method provided in this application; Figure 4 A flowchart of the fourth embodiment of the extended battery management method provided in this application; Figure 5 A flowchart of the fifth embodiment of the battery capacity management method provided in this application; Figure 6 A flowchart of the sixth embodiment of the battery capacity management method provided in this application; Figure 7 A flowchart of the seventh embodiment of the battery capacity management method provided in this application; Figure 8 A flowchart of the eighth embodiment of the extended battery management method provided in this application; Figure 9A flowchart of the ninth embodiment of the extended battery management method provided in this application; Figure 10 A graph of some embodiments of the capacity differential-voltage curve; Figure 11 A graph of some embodiments of the voltage differential-capacity curve; Figure 12 A graph of some embodiments of the voltage differential-capacity curve; Figure 13 Graphs of some embodiments of the first voltage management curve and the second voltage management curve; Figure 14 Schematic block diagrams of some embodiments of the vehicle provided in this application.

[0037] Explanation of icon numbers: 1. Vehicle; 100. Battery device; 300. Controller; 400. Motor.

[0038] The realization of the purpose, functional features and advantages of this application will be further explained in conjunction with the embodiments and with reference to the accompanying drawings. Detailed Implementation

[0039] The embodiments of the technical solution of this application will now be described in detail with reference to the accompanying drawings. These embodiments are only used to more clearly illustrate the technical solution of this application and are therefore merely examples, and should not be used to limit the scope of protection of this application.

[0040] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application pertains; the terminology used herein is for the purpose of describing particular embodiments only and is not intended to limit the application; the terms “comprising” and “having”, and any variations thereof, in the specification, claims, and foregoing description of the drawings are intended to cover non-exclusive inclusion.

[0041] In the description of the embodiments of this application, technical terms such as "first" and "second" are used only to distinguish different objects and should not be construed as indicating or implying relative importance or implicitly specifying the number, specific order, or primary and secondary relationship of the indicated technical features. In the description of the embodiments of this application, "multiple" means two or more, unless otherwise explicitly defined.

[0042] In this document, the term "embodiment" means that a particular feature, structure, or characteristic described in connection with an embodiment may be included in at least one embodiment of this application. The appearance of this phrase in various places throughout the specification does not necessarily refer to the same embodiment, nor is it a mutually exclusive, independent, or alternative embodiment. It will be explicitly and implicitly understood by those skilled in the art that the embodiments described herein can be combined with other embodiments.

[0043] In the description of the embodiments in this application, the term "and / or" is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this document generally indicates that the preceding and following related objects have an "or" relationship.

[0044] It should be noted that step designations such as S100 and S200 are used in this document for the purpose of more clearly and concisely describing the corresponding content, and do not constitute a substantial limitation on the order. In specific implementation, those skilled in the art may execute S200 first and then S100, etc., but these should all be within the protection scope of this application.

[0045] Currently, judging from market trends, battery applications are becoming increasingly widespread. Batteries are not only used in energy storage systems such as hydropower, thermal power, wind power, and solar power plants, but also extensively in electric vehicles such as electric bicycles, electric motorcycles, and electric cars, as well as in military equipment and aerospace. With the continuous expansion of battery applications, market demand is also constantly increasing.

[0046] However, to increase battery life, an extended capacity battery can be constructed by pre-introducing additional active media (such as lithium or sodium) during the manufacturing stage. This pre-compensation mechanism effectively compensates for irreversible losses during the initial and cycling processes. First, during formation, the extended capacity medium preferentially participates in the construction of the solid electrolyte interphase (SEI) film. Compared to traditional batteries that consume a portion of the positive electrode's active lithium for film formation during the first charge and discharge, the extended capacity battery compensates for this loss with the pre-introduced medium, thus protecting the positive electrode's active lithium from being consumed and maintaining full initial capacity. Second, during cycling, the pre-introduced medium forms an active medium reserve. For lithium ions continuously lost due to electrolyte decomposition or material structure collapse, the pre-introduced medium releases replenishing ions and fills lattice vacancies based on potential difference changes. This dynamic replenishment mechanism allows the battery's usable capacity to remain at a high level throughout long-term cycling, thereby delaying capacity decay and indirectly improving the overall battery life.

[0047] However, traditional methods for managing extended-capacity batteries suffer from low precision. Understandably, extended-capacity batteries exhibit unique, phased aging characteristics during use (distinct from non-extended-capacity batteries). As operating time increases, the additional pre-installed capacity of an extended-capacity battery is gradually depleted. This depletion disrupts the original electrochemical matching between the positive and negative electrodes, leading to a continuous and irreversible shift in its internal thermodynamic equilibrium. In contrast, the aging degradation of non-extended-capacity batteries follows a more continuous and monotonous pattern throughout their lifespan, with the capacity decay of the positive and negative electrodes relatively synchronous, without such phased transitions. This makes managing extended-capacity batteries more challenging than managing non-extended-capacity batteries.

[0048] Based on the aforementioned two-stage aging evolution pattern of extended-capacity batteries, it is worth noting that traditional battery management methods rely solely on a single fixed curve model calibrated at the factory for state estimation throughout the entire lifespan of extended-capacity batteries. When the aging of extended-capacity batteries causes their actual thermodynamic characteristics to deviate from the initial settings, continuing to manage them using the fixed curve model may result in the battery management system being completely unable to effectively match the current aging state of the extended-capacity batteries. This leads to severely inaccurate estimations of battery states such as state of charge (SOC) and state of health (SOH), thus exhibiting technical deficiencies in management accuracy.

[0049] Therefore, to improve the management accuracy of extended-capacity batteries, this application provides a method for managing extended-capacity batteries. This method discloses acquiring the voltage differential-capacity curve of the extended-capacity battery during the charging process, identifying the current aging stage of the extended-capacity battery based on the changing trend of the voltage differential-capacity curve at different times, and then adaptively matching the corresponding voltage management curve for dynamic management at different working stages. This solution effectively overcomes the problem of inaccurate management caused by the thermodynamic state deviation of the battery when traditional extended-capacity battery charging and discharging management is based on a single fixed voltage management curve, thereby ultimately improving the management accuracy of extended-capacity battery charging and discharging.

[0050] In one feasible implementation, this application provides a battery management system for performing the battery management methods in some of the following embodiments, that is, the battery management system is directly configured to implement the battery management methods in some of the following embodiments.

[0051] Unless otherwise specified, the battery management methods in some of the following embodiments are all executed by the battery management system (BMS), which can be simply referred to as the system.

[0052] Unless otherwise specified, the batteries appearing in some of the following embodiments can be understood as extended capacity batteries.

[0053] It should be noted that, for the batteries mentioned in this application (i.e., expanded capacity batteries), during the manufacturing process, the cells undergo processes such as liquid injection, impregnation, formation, and screening, and are then packaged into more complete battery cells. Each battery cell is a lithium-sulfur battery, a sodium-ion battery, a lithium-ion battery, or a magnesium-ion battery, but is not limited to these. The battery cell can be cylindrical, flat, cuboid, or other shapes. In a battery, there can be one or more battery cells, which can be connected in series, parallel, or a combination thereof. A combination thereof means that multiple battery cells are connected in both series and parallel connections. Multiple battery cells can be directly connected in series, parallel, or a combination thereof, and then the entire assembly of the multiple battery cells is housed in a casing. Alternatively, the battery can be composed of multiple battery cells first connected in series, parallel, or a combination thereof to form a battery module, and then multiple battery modules are connected in series, parallel, or a combination thereof to form a whole (battery pack), which is then housed in a casing. The battery may also include other structures; for example, the battery may also include a busbar for realizing electrical connections between multiple battery cells.

[0054] The capacity-enhancing battery described in this application is not limited to a specific battery chemistry system. The capacity-enhancing battery can be a lithium-filled battery that introduces additional active lithium through pre-lithiation technology, a sodium-filled battery that introduces additional active sodium through pre-lithiation technology, or any other pre-installed active medium. This application does not specifically limit the type of chemical system or the type of supplementary active medium in the capacity-enhancing battery.

[0055] In one embodiment of this application, as Figure 1 As shown, the battery capacity management method includes steps S100 to S300.

[0056] In this embodiment, step S100 involves obtaining the voltage differential-capacity curve of the expanded capacity battery during the charging process, and determining the working stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times.

[0057] Optionally, the voltage differential is the voltage differential with respect to the capacity, i.e., dV / dQ, where V is the voltage and Q is the capacity. This voltage differential-capacity curve is the dV / dQ-Q curve.

[0058] The voltage differential-capacity curve is used to characterize the thermodynamic or kinetic polarization characteristics of the extended-capacity battery during charging and discharging. For example, during the charging process, especially in the constant-current charging stage, the electrochemical reactions inside the extended-capacity battery are relatively stable. Therefore, the voltage differential-capacity curve obtained during charging can eliminate most of the interference caused by polarization resistance, more accurately reflecting the intrinsic mapping relationship between the battery's internal capacity and voltage. Furthermore, the amount of active media participating in the reaction changes continuously at different aging stages throughout the extended-capacity battery's lifespan, causing shifts or changes in the shape of the characteristic peaks in the voltage differential-capacity curve. Therefore, the battery management system can extract the current voltage differential-capacity curve and compare it with historical voltage differential-capacity curves. Optionally, by calculating the offset direction and amount of the characteristic peaks between these two or more curves, the current aging evolution process of the extended-capacity battery can be dynamically identified, thereby determining its current operating stage.

[0059] The trend of the voltage differential-capacity curve at different times can be the trend of the curve at two different times.

[0060] Optionally, the acquisition of the voltage differential-capacity curve of the expanded battery during the charging process in step S100 can be performed periodically at preset time intervals or cycle numbers, intermittently within a single charging cycle, or continuously within a single charging cycle, thereby monitoring the stage of the expanded battery in real time or near real time. Optionally, the acquisition of the voltage differential-capacity curve of the expanded battery during the charging process in step S100 can also be triggered when specific charging conditions are met. For example, when the battery management system identifies that the expanded battery is in a low-rate constant current charging state (such as AC slow charging), and the voltage or capacity span of this charge is greater than a preset threshold, the acquisition and calculation of the voltage differential-capacity curve is triggered. This ensures that the extracted curve characteristic peaks have a very high signal-to-noise ratio and completeness, and effectively avoids invalid computational load under fragmented fast charging conditions. Of course, the above two acquisition methods can be performed individually or in parallel, and are not limited here.

[0061] Here, the electrochemical principle behind the shift in the voltage differential-capacity curve of an extended-capacity battery with different aging stages is explained as follows: The external voltage of the battery is essentially determined by the difference between the positive and negative electrode potentials. The peaks or inflection points on the voltage differential-capacity curve correspond microscopically to specific crystalline phase transition reactions of the positive and negative electrode active materials during lithium insertion / extraction. In the first stage (e.g., the positive electrode capacity limitation stage), the extended-capacity battery (such as a lithium-filled battery) contains pre-existing extra active lithium, and the system is in a state of lithium surplus. As charge-discharge cycles proceed, this extra active lithium is continuously consumed, causing the potential curves of the positive and negative electrodes to slide relative to each other on the capacity axis (i.e., the electrode slip effect in electrochemistry). Since the boundary of the charge-discharge capacity is limited by the maximum lithium storage capacity of the positive electrode material at this time, and the negative electrode slips relative to the positive electrode, macroscopically, this manifests as the voltage differential-capacity curve and its phase transition characteristic peaks of the full cell continuously shifting towards higher capacity as the aging process progresses. When the battery enters the second stage (e.g., the active lithium limitation stage), the internally reserved expansion capacity has been completely exhausted. At this point, the battery's thermodynamic boundary shifts, and the degradation mechanism ages to the same as that of a normal non-expanded capacity battery. That is, the battery's maximum capacity is now limited by the remaining, decreasing total amount of active lithium in the system. Since there is no longer any additional active medium to support the aforementioned electrode slip effect, the shift of the voltage differential-capacity curve towards higher capacity will stop. Furthermore, with the further irreversible loss of available active lithium, the overall available capacity range continues to shrink, causing the characteristic peak to begin to shrink or deform in the opposite direction towards lower capacity.

[0062] Thus, the voltage differential-capacity curve is extracted, and the current voltage differential-capacity curve is compared with the curves at historical times. Based on the calculated curve's trend in a specific dimension (including but not limited to offset direction, offset amount, or degree of morphological distortion), the current aging stage of the battery can be mapped. It is understandable that due to different types of voltage differential-capacity curves used, the specific geometric evolution characteristics exhibited by the battery at different aging stages will vary. However, regardless of the curve form used, the time-varying evolution law of its geometric shape has a corresponding physical mapping relationship with the consumption process of the additional active medium inside the battery. Therefore, in practical applications, it is only necessary to determine whether the currently calculated trend conforms to the pre-defined characteristic evolution law of the corresponding stage. If the trend conforms to the first evolution law, it can be determined that the expanded battery is in the first preset stage; if the trend conforms to the second evolution law, it can be determined that the expanded battery has entered the second preset stage. Through this trend tracking based on intrinsic aging laws, this application achieves dynamic identification of the aging stage of the expanded battery's life cycle.

[0063] In this embodiment, step S200 involves managing the expanded battery based on a first voltage management curve when the current working stage of the expanded battery is in a first preset stage.

[0064] When the aforementioned steps determine that the expanded battery is in the first preset stage, it means that the pre-set additional expanded capacity inside the battery is still sufficient. At this time, the thermodynamic boundary of the battery is mainly determined by the available amount of positive electrode active medium. In order to match the physical state unique to this stage, a pre-stored first voltage management curve (e.g., the first open-circuit voltage-state-of-charge curve) can be called as a reference model to perform various state estimation and safety management strategies on the expanded battery. In actual battery management applications, the specific process of managing the expanded battery based on the first voltage management curve includes, but is not limited to: when performing state of charge (SOC) estimation, the real-time collected battery open-circuit voltage is substituted into the first voltage management curve for table lookup or function interpolation to obtain the initial SOC value, or the curve is used to perform closed-loop correction of the cumulative error generated by the ampere-hour integration method (e.g., combined with the extended Kalman filter algorithm EKF); optionally, the peak charge and discharge power boundary of the expanded battery at the current moment can also be predicted based on the first voltage management curve, combined with the current internal resistance and polarization state. Since the first voltage management curve perfectly matches the actual electrochemical characteristics of the battery at this aging stage, it can fundamentally eliminate the estimation drift caused by mismatch of management curves and effectively prevent safety risks such as thermal runaway caused by overcharging or over-discharging of the battery.

[0065] Furthermore, in order to obtain the first voltage management curve, this embodiment provides the following two calibration methods: First, a battery in its initial fresh state is obtained as a standard test sample. This initial fresh state means that the battery, after factory formation, has not yet undergone long-term charge-discharge cycle aging, and its internal additional capacity is fully loaded and has not been consumed. Second, under a set constant temperature environment, the battery in its initial fresh state is controlled to undergo complete constant current charging and discharging tests at a preset micro-current rate (usually a very small rate less than or equal to 1 / 20C). The purpose of using a micro-rate for charging and discharging is to minimize the voltage drop interference caused by the battery's internal ohmic resistance and polarization resistance, so that the measured terminal voltage can be approximately equivalent to the battery's true open-circuit voltage. Finally, during the above micro-rate charge-discharge test, the voltage and current data of the battery are simultaneously collected, and the corresponding real-time capacity data is obtained by accurately integrating the charging and discharging current in ampere-hours. By mapping the collected voltage data to the corresponding capacity or SOC data, the first voltage management curve representing the state where the expanded capacity is not exhausted can be plotted and calibrated.

[0066] Secondly, the method for obtaining the first voltage management curve may include: controlling the expanded battery in its initial fresh state to undergo pulse discharge or charging at specific multiple state of charge (SOC) nodes, and controlling the battery to be allowed to rest sufficiently after each pulse. After the internal polarization of the battery is completely eliminated and the terminal voltage reaches a stable state, the stable terminal voltage at this time is collected as the actual open-circuit voltage at the corresponding SOC node. Subsequently, the open-circuit voltages obtained at each SOC node are interpolated or fitted to construct the first voltage management curve.

[0067] In this embodiment, step S300 involves managing the expanded battery based on the second voltage management curve when the current working stage of the expanded battery is in the second preset stage.

[0068] When the system determines that the expanded battery is in the second preset stage through trend comparison in step S100, it means that the additional pre-installed active medium inside the battery (e.g., additionally added active lithium) has been completely depleted. At this time, the maximum capacity decay of the battery shifts, becoming limited by the remaining, continuously decreasing total amount of active lithium, and its thermodynamic characteristics have aged to a state highly similar to that of a normal non-expanded battery. Under this physical context, if the aforementioned first voltage management curve continues to be used, it will cause a deviation in the state of charge estimation, resulting in a decrease in the accuracy of the battery's charge and discharge management. Therefore, in the second preset stage, it is necessary to trigger a curve switching mechanism, that is, to stop calling the first voltage management curve and instead call the second voltage management curve (e.g., the second open-circuit voltage-state of charge curve). In this second preset stage, closed-loop correction, charge and discharge power boundary setting, and health status assessment will be performed based on the second voltage management curve, thereby ensuring that the expanded battery can still be managed with high accuracy after aging.

[0069] Furthermore, in order to obtain the second voltage management curve, this embodiment provides the following two calibration methods: First, the same batch of expanded capacity batteries as those in step S200 is obtained as test samples, and these expanded capacity batteries are subjected to accelerated cycle aging experiments in a laboratory environment. During the aging process, the changing trend of its voltage differential-capacity curve is continuously monitored until it is confirmed that its internal expanded capacity has been completely consumed (i.e., entering the second preset stage). Subsequently, the aged battery is subjected to a preset small rate (e.g., 1 / 20C) constant current charge-discharge test in a constant temperature environment, and voltage and capacity data are collected simultaneously to calibrate and obtain the second voltage management curve.

[0070] Secondly, a reference battery is obtained, which has the exact same positive and negative electrode design parameters as the expanded capacity battery (i.e., using the same electrode plates and electrolyte system). The difference lies in that this reference battery was not configured with additional capacity expansion during the manufacturing stage (e.g., no lithium replenishment process was performed). Since the expanded capacity battery entering the second preset stage has the same thermodynamic nature as the unexpanded reference battery, accelerated cycle aging experiments are conducted in a laboratory environment. After the designed expanded capacity of the expanded capacity battery is exhausted, constant current charge-discharge tests at a preset small rate (e.g., 1 / 20C) are performed in a constant temperature environment to obtain a second voltage management curve. This method saves development time and testing costs.

[0071] It is understood that the first and second voltage management curves were obtained during the experimental phase and are adaptable to the voltage characteristics of the corresponding expanded-capacity battery at different operating stages. They can be pre-stored in non-volatile storage media within the Battery Management System (BMS), Vehicle Control Unit (VCU), or Power Conversion System (PCS). At the data structure level, the first and second voltage management curves can be structured as multidimensional lookup tables, polynomial fitting function parameters, or neural network weight matrices to facilitate rapid addressing and retrieval by the underlying control chip. Furthermore, for electrical devices with Vehicle-to-Everything (V2X) capabilities, the aforementioned first and second voltage management curves can also be pre-stored in a cloud server. Based on the phased diagnostic results from big data analysis, the cloud can dynamically distribute the corresponding voltage management curves to the local device. Alternatively, for electrical devices, the aforementioned first and second voltage management curves can also be stored in the relevant storage media of the electrical device for direct retrieval when needed.

[0072] It should be noted that in this embodiment, only the first and second voltage management curves are disclosed as examples for illustration. Their main purpose is to clearly distinguish between the two most representative operating stages: the undepleted and depleted internally pre-set additional active medium. However, in practical applications, the aging and medium consumption of the extended-capacity battery is essentially a continuous and complex gradual process. Therefore, based on actual control precision requirements, the entire lifecycle of the extended-capacity battery can be more finely divided into three, four, or more consecutive operating stages, and a unique voltage management curve can be matched for each sub-stage. It should be noted that this extension from two-stage to multi-stage voltage curve matching still relies on the core logic of dynamic adaptive management based on the offset law of the extended-capacity battery voltage differential-capacity curve, and does not depart from the core inventive concept of this application, and should be included within the scope of protection of this application.

[0073] Among them, improving the management accuracy during charge and discharge can be reflected in: fully releasing the maximum usable energy of the battery when the expanded capacity is not exhausted, and tightening the charge and discharge cutoff boundary in time after the expanded capacity is exhausted, thereby avoiding serious thermal runaway risks such as overcharging, over-discharging and negative electrode lithium plating caused by estimation errors, and finally achieving a high-precision dynamic balance between the performance and safety baseline of the expanded capacity battery throughout its entire life cycle.

[0074] In summary, by combining steps S100 to S300, the voltage differential-capacity curve offset law of the expanded capacity battery during the charging process is used to determine the working stage (i.e., the degradation stage) of the expanded capacity battery. When it is confirmed that the expanded capacity battery is in the first preset stage where the additional capacity has not been exhausted, a first voltage management curve is matched for it; when it is determined that the additional capacity has been exhausted and the battery has crossed the physical aging inflection point and entered the second preset stage, a second voltage management curve is matched for it. In this way, it conforms to the underlying physical evolution law of the expanded capacity battery, matches different management curves for different working stages, eliminates the cumulative error caused by management curve mismatch, and thus improves the management accuracy when managing the charging and discharging of the expanded capacity battery.

[0075] In one embodiment, the first preset stage is a positive electrode capacity limiting stage.

[0076] During the cathode capacity limitation phase, because additional active lithium is added during battery manufacturing through processes such as pre-lithiation, the expanded capacity battery is in a state of surplus active lithium. In the early and middle stages of charge-discharge cycles, although some active lithium is irreversibly consumed as the solid electrolyte interface film continues to thicken and repair, the available cycle capacity of the entire battery is limited by the physical space capability of the cathode material for lithium insertion and extraction (i.e., the maximum lithium storage capacity of the cathode) because the additional lithium source has not been completely exhausted.

[0077] By defining the first preset stage as the positive electrode capacity limitation stage, the battery management system can accurately sense and confirm the current lithium-rich health state of the battery. Thus, when calling the first voltage management curve, it can fully and safely release the energy of the expanded battery in the early and middle stages of operation, ensuring the accuracy of state estimation within the positive electrode capacity limitation stage. This, in turn, can help improve the management accuracy of charge and discharge management when the expanded battery is in the positive electrode capacity limitation stage.

[0078] In one embodiment, the second preset stage is an active lithium restriction stage.

[0079] As battery operating time continues, various internal side reactions will eventually completely deplete the pre-installed additional active lithium. After crossing this critical depletion point, the thermodynamic equilibrium state inside the battery undergoes a fundamental reversal and boundary shift. At this point, the usable cycle capacity of the extended-capacity battery is no longer limited by the physical lithium storage space of the positive electrode, but rather by the total amount of active lithium. At this stage, the aging mechanism of the extended-capacity battery has essentially become identical to that of a conventional non-extended-capacity battery. This is the active lithium-limiting stage.

[0080] By defining the second preset stage as the active lithium limitation stage, when the battery ages to this stage, the control boundary can be tightened in time to prevent overcharging, over-discharging, and even serious thermal runaway risks such as negative electrode lithium plating caused by continuing to use the relatively optimistic estimation strategy of the previous stage. This fundamentally safeguards the safety bottom line in the middle and late stages of the battery life cycle, ensures the accuracy of state estimation in the positive electrode capacity limitation stage, and thus helps to improve the management accuracy of charge and discharge management when the expanded capacity battery is in the positive electrode capacity limitation stage.

[0081] In one embodiment, the first preset stage is a positive electrode capacity limitation stage, and the second preset stage is an active lithium limitation stage. This breaks through the single management blind spot for expanded capacity batteries, balancing the high-performance output of the expanded capacity battery during the positive electrode capacity limitation stage with the high safety protection during the active lithium limitation stage, thus achieving high-precision management of the expanded capacity battery throughout its entire lifecycle.

[0082] In one embodiment, the first voltage management curve characterizes the voltage characteristics of the expanded battery when the expanded capacity is not depleted, and the second voltage management curve characterizes the voltage characteristics of the expanded battery when the expanded capacity is depleted.

[0083] Because the physical matching relationship between the positive and negative electrodes and the total amount of available active medium in the system change before and after the expanded capacity of the battery is exhausted, this inevitably leads to a drift in the mapping relationship between its macroscopic open-circuit voltage and state of charge. Therefore, two independent voltage management curves are required to accurately characterize these two different internal thermodynamic states.

[0084] Optionally, the first voltage management curve is a first open-circuit voltage-state-of-charge curve (i.e., the first OCV-SOC curve), and the second voltage management curve is a second open-circuit voltage-state-of-charge curve (i.e., the second OCV-SOC curve). Figure 13 As shown, the first open-circuit voltage-state-of-charge curve (solid line) and the second open-circuit voltage-state-of-charge curve (dashed line) exhibit stage-like differences in their overall shape. From Figure 13It can be seen that under low charge conditions, the SOC value corresponding to the same open-circuit voltage deviates between the two curves. If the same open-circuit voltage-state-of-charge curve is used to manage the charging and discharging of the expanded battery before and after the expanded capacity is exhausted, it may lead to an incorrect judgment of the actual remaining capacity of the expanded battery after it has aged to a certain extent, thereby causing corresponding charging and discharging risks.

[0085] Therefore, by introducing and dynamically matching the first open-circuit voltage-state-of-charge (OCC) curve or the second open-circuit voltage-OCC curve that matches the current operating stage of the expanded-capacity battery, the accuracy of state estimation is improved. Before and after the battery crosses the physical inflection point of depletion of its additional capacity, the underlying lookup table data can be adaptively switched, eliminating the cumulative estimation errors of OCV and SOH, and ensuring the absolute accuracy of the remaining driving range prediction for the device. Simultaneously, it effectively prevents deep over-discharge caused by OCV curve drift leading to incorrect SOC estimation, or severe overcharging and lithium plating risks caused by underestimating SOC, thereby enhancing battery reliability and substantially extending the safe operating life of the expanded-capacity battery.

[0086] In one embodiment, such as Figure 2 As shown, step S100, obtaining the voltage differential-capacity curve of the expanded capacity battery during the charging process, and determining the working stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times, includes steps S110 and S120.

[0087] In this embodiment, step S110 involves obtaining the voltage differential-capacity curve of the expanded capacity battery during the charging process.

[0088] Here, the voltage differential is the derivative of the charging voltage with respect to the cumulative charging capacity.

[0089] In terms of implementation, voltage and capacity data during the charging process of the expanded-capacity battery can be collected and differentiated to generate a voltage differential-capacity curve (i.e., dV / dQ-Q curve) reflecting the rate of voltage change with capacity. It is understandable that the microscopic crystal phase transitions during battery charging and discharging may only manifest as extremely weak voltages on conventional charge-discharge curves, making them difficult to accurately capture. The voltage differential-capacity curve, however, can mathematically amplify these minute voltage changes, transforming them into easily identifiable phase transition characteristic peaks. This improves the signal-to-noise ratio of the data and facilitates subsequent judgment of the battery's internal state and operating stage.

[0090] In this embodiment, step S120 involves determining the working stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times.

[0091] By extracting the voltage-capacity curve at the current moment and comparing it with historical voltage-capacity curves, and examining the changes in their geometric characteristics (such as characteristic peaks), the trend over time is obtained and used as the basis for stage division. This avoids dependence on absolute physical thresholds. Due to manufacturing tolerances between different batteries and the measurement drift of the battery management system's sensors over time, using absolute thresholds often leads to misjudgments. By tracking the relative trend of the voltage-capacity curve over time, the battery management system effectively achieves a self-calibration diagnosis unaffected by hardware drift, thereby tracking the changing process of active medium consumption within the expanded battery.

[0092] It is understandable that during the charging and discharging process of a battery, the insertion and extraction of lithium ions into the crystal lattice of the positive and negative electrode active materials inevitably involves phase transitions in the internal crystal structure of the electrode materials. On traditional charge / discharge voltage-capacity (VQ) curves, these phase transitions appear as extremely flat voltage plateaus or barely perceptible tiny inflection points. However, the voltage differential-capacity curve, through the differentiation of voltage relative to capacity, essentially provides a mathematically magnified high-magnification of the "voltage polarization rate" during the battery's charging and discharging process. Specifically, on this voltage differential-capacity curve, each characteristic peak or valley precisely corresponds at the microscopic physical level to the phase transition boundary or single-phase / two-phase transition node of the positive and negative electrode materials at a specific lithium insertion / extraction depth. The positions of these characteristic peaks are entirely determined by the inherent thermodynamic properties of the electrode materials themselves; therefore, they are like digital fingerprints of the electrochemical reactions within the battery. For extended-capacity batteries, the voltage differential-capacity curve is introduced. As the additional active medium (such as active lithium) inside the battery is gradually consumed during charge-discharge cycles, the electrochemical matching capacity range of the positive and negative electrodes will be misaligned, resulting in an electrode slip effect. This microscopic physical slip is intuitively and quantitatively mapped macroscopically as a relative shift of specific characteristic peaks on the horizontal axis (capacity Q axis) of the voltage differential-capacity curve. Therefore, by extracting and tracking the shift trend of characteristic peaks on this curve, this application can accurately demonstrate the actual consumption rate and thermodynamic aging boundary of the active medium inside the battery.

[0093] Optionally, the voltage differential-capacity curve is obtained as follows: within a set charging range, the battery terminal voltage and charging current sequences are collected at a certain frequency. The cumulative charging capacity (Q) is then calculated in real time using the ampere-hour integration method, and the discrete voltage change and capacity change are directly differentiated using a differential algorithm (i.e., dV / dQ is calculated). Optionally, to eliminate the abrupt interference of sensor measurement noise on the differential result, smoothing and denoising algorithms such as Kalman filtering, moving average, or spline interpolation can be introduced before and after the calculation to fit the dV / dQ-Q curve.

[0094] Optionally, the voltage differential-capacity curve is obtained as follows: it is obtained through a preset model. The preset battery model can be a data-driven model (such as a neural network model) trained based on offline big data, or it can be an electrochemical mechanism model or a high-order equivalent circuit model containing internal thermodynamic parameters. The battery management system only needs to input the currently collected macroscopic state parameters (such as terminal voltage, operating current, ambient temperature, and historical cycle count) as input variables into the preset model, and the voltage differential-capacity curve at the current moment can be directly reconstructed or deduced by the state observer inside the model.

[0095] In one embodiment, such as Figure 3 As shown, step S110, obtaining the voltage differential-capacity curve of the expanded capacity battery during the charging process, includes steps S111 to S113.

[0096] In this embodiment, step S111 involves obtaining the current voltage of the expanded battery while it is being charged, and determining the corresponding target voltage acquisition range based on the obtained current voltage.

[0097] The electrochemical phase transition characteristics inside a battery (i.e., the characteristic peaks on the voltage differential-capacity curve) are not uniformly distributed across the entire charging voltage range, but are highly concentrated within certain specific voltage windows. Therefore, the battery management system monitors the battery's terminal voltage during or after charging. When it detects that the current voltage is approaching a preset active phase transition region, it retrieves and defines a target voltage acquisition range (e.g., 3.2V to 3.4V) from a preset calibration table to fully cover the characteristic peaks of that phase transition. Understandably, this targeted window acquisition strategy avoids the large amount of redundant calculations resulting from blindly acquiring and processing full-range charging data, significantly reducing system storage overhead and the computational load on the underlying control chip. On the other hand, some data is unreliable or even interfering. For example, in the voltage transient region during the initial charging phase, or in the region of severe polarization fluctuations when the battery's state of charge (SOC) is close to 0% or 100%, the collected voltage and current data often contain a large amount of dynamic interference noise and cannot stably map the internal phase transition characteristics. Including this data in the calculation can seriously mislead the location of characteristic peaks and the identification of shifts. Therefore, by defining a specific target voltage acquisition interval in step S111, these invalid data intervals without reference value can be actively eliminated, ensuring that the data participating in the subsequent differential calculation are all within the window of stable and distinctive electrochemical reactions, thus improving the anti-interference capability for judging the working stage of the expanded battery.

[0098] In this embodiment, step S112 involves acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range.

[0099] According to the preset frequency, the terminal voltage and charging current values ​​at each time point are recorded synchronously and continuously until the battery voltage is no longer within the target voltage acquisition range. This allows sampling within the critical electrochemical phase transition window, capturing highly representative discrete data points, avoiding aliasing or peak omissions, and ensuring high raw data resolution for subsequent calculus calculations. Of course, the preset frequency is not limited here; it depends on the actual application requirements. The preset frequency must meet the minimum data density required for differential calculations and the resolution requirements for feature recognition.

[0100] In this embodiment, step S113 involves determining the voltage differential-capacity curve of the expanded battery during the charging process based on the obtained charging voltage and charging current.

[0101] Optionally, in step S113, the charging current sequence obtained in step S112 is first integrated in ampere-hours over time to calculate the corresponding cumulative charging capacity (Q). Then, the discrete voltage differential value (dV / dQ) is obtained by dividing the voltage change between adjacent sampling points by the capacity change. Finally, a mapping relationship is established between the dV / dQ value and the cumulative capacity Q to generate a voltage differential-capacity curve.

[0102] Optionally, in order to eliminate high-frequency white noise or operating condition glitches introduced during the sampling of the underlying hardware sensors, digital filtering algorithms (such as moving average filtering, Kalman filtering, or polynomial smoothing fitting) can be called to denoise the differential sequence.

[0103] To establish a mapping relationship between the dV / dQ value and the cumulative capacity Q, generating a high signal-to-noise ratio voltage differential-capacity curve, can be achieved through the following implementation: using the cumulative capacity Q as a unified independent variable benchmark. Since the charging voltage and charging current are acquired synchronously over time in actual sampling, the time axis is first transformed into the capacity axis through ampere-hour integration. Subsequently, for each capacity increment interval, the corresponding voltage increment is extracted, and a functional correspondence is established between their quotient and the central capacity point of that interval.

[0104] In one embodiment, such as Figure 4 As shown, before step S111, when the expanded battery is being charged, obtaining the current voltage of the expanded battery, and determining the corresponding target voltage acquisition range based on the obtained current voltage, the expanded battery management method further includes steps S114 and S115.

[0105] In this embodiment, step S114 involves obtaining the capacity differential-voltage curve of the expanded battery.

[0106] Here, the capacity differential is the derivative of the cumulative charging capacity with respect to the charging voltage.

[0107] The capacity differential-voltage curve dQ / dV-V obtained in step S114 is mainly used to determine the absolute coordinates of electrochemical characteristics on the voltage axis. This capacity differential-voltage curve can be obtained by directly retrieving a preset calibration model from local memory, or generated based on sampling data from the initial charging stage. Since its abscissa is voltage, the system can intuitively determine the voltage range corresponding to the current phase transition reaction of the active medium by identifying the peak point of the capacity differential-voltage curve. Considering that the voltage position of the phase transition platform of the extended-capacity battery will change with the increase of internal resistance and potential shift throughout its entire life cycle, if a fixed voltage range is used for data acquisition, the target characteristics will be out of the sampling window. By identifying the real-time position of the capacity differential-voltage curve, the sampling range can be dynamically adjusted to ensure that the data points required for subsequent voltage differential-capacity curve calculations can completely cover the key phase transition characteristics.

[0108] In the stage identification process, the aging evolution of the expanded capacity battery manifests as the relative slippage of the positive and negative electrode active media. This slippage is much more pronounced on the capacity axis (Q-axis) than on the voltage axis (V-axis). If the capacity differential-voltage curve is used directly for stage determination, the signal-to-noise ratio of its characteristic displacement is extremely low because the voltage axis is highly susceptible to interference from internal resistance polarization, charge / discharge rate, and ambient temperature fluctuations. Therefore, this embodiment first uses the capacity differential-voltage curve to delineate the region in the voltage dimension, and then uses the voltage differential-capacity curve to calculate the shift trend of the characteristic peak in the capacity dimension within the target voltage acquisition range. This eliminates noise interference from voltage fluctuations, obtains higher resolution aging characteristic information, and thus accurately determines the working stage of the expanded capacity battery.

[0109] In this embodiment, step S115 involves dividing the capacity differential-voltage curve into multiple voltage intervals along the horizontal voltage axis based on the capacity differential peak of the acquired capacity differential-voltage curve. Each voltage interval corresponds to at least one capacity differential peak, and the target voltage acquisition interval is selected from the multiple voltage intervals.

[0110] Among them, the capacity differential peak can be the peak value of the capacity differential. Multiple capacity differential peaks on the voltage differential-capacity curve are located using an extreme value retrieval algorithm. These peaks represent the intensity of the electrochemical reaction and also mark the phase transition state of the positive and negative electrode active materials at a specific voltage. Using the voltage points where these peaks are located as a reference, the boundaries of each interval are defined on the horizontal axis according to a preset voltage width, ensuring that each voltage interval contains at least one capacity differential peak that can characterize a specific physical process.

[0111] This step represents a shift from static preset to dynamic focusing at the technical level. Traditional techniques often preset fixed voltage ranges for data capture, but due to individual battery manufacturing tolerances and the evolution of internal resistance during cycling, the position of characteristic peaks may deviate from the preset window. Through the dynamic division and filtering in step S115, the latest voltage coordinates of the characteristic peaks can be locked in real time. Even if the battery experiences a significant voltage shift, the system can still accurately capture the complete phase transition characteristics. This not only prevents feature loss from the source but also improves the robustness and computational efficiency of the stage judgment logic.

[0112] It is understandable that, due to the randomness of the initial voltage at the moment of charging start, the acquired voltage value may already be within a certain target voltage acquisition range (e.g., in the middle of the range). If data is still extracted according to a fixed static range, the acquired voltage differential-capacity curve will be incomplete or key peak information will be lost. Therefore, in this embodiment, steps S114 and S115 are performed in real time, that is, the acquisition and range discrimination of the capacity differential-voltage curve are dynamically performed based on the real-time voltage input. Optionally, the current voltage is acquired, and the target voltage acquisition range is triggered based on the current voltage as a reference or starting point (of course, it must be ensured that the target voltage acquisition range has a capacity differential peak) to ensure that the remaining electrochemical characteristics within the range can be completely captured. In this way, the feature loss problem caused by the random charging start point is solved, ensuring that the effective data window can be locked with the fastest response speed regardless of the battery's state of charge (SOC) at the start of charging, improving the reliability of stage diagnosis and the scenario universality of the solution.

[0113] Based on this, the current operating stage of the expanded battery can be determined by relying only on data from a narrower local voltage range. This technology overcomes the absolute dependence of traditional technologies on full-range data from complete charge-discharge cycles, avoiding redundant calculations.

[0114] In one embodiment, such as Figure 5 As shown, step S113, determining the voltage differential-capacity curve of the expanded capacity battery during the charging process based on the obtained charging voltage and charging current, includes steps S1131 to S1133.

[0115] In this embodiment, step S1131 involves obtaining the cumulative charging capacity within the target voltage acquisition range based on the charging current.

[0116] Optionally, the cumulative charging capacity within the target voltage acquisition range can be calculated using the ampere-hour integration method based on the charging current acquired in real time within that range. To ensure data accuracy, the moment of entering the target voltage range can be used as the zero point for capacity statistics. By integrating the current over time, the dynamic charging process can be transformed into a capacity sequence with energy as the quantifiable indicator.

[0117] In this embodiment, step S1132 involves determining the derivative of the charging voltage with respect to the cumulative charging capacity.

[0118] In this process, based on the accumulated capacity, the rate of change of the charging voltage relative to that accumulated capacity is further calculated, i.e., the differential value is obtained. In the actual algorithm implementation, differential processing can be used, that is, calculating the ratio of the voltage change to the capacity change within adjacent sampling points or a fixed capacity increment. This differential value can capture subtle plateau fluctuations on the voltage curve and transform them into characteristic extrema.

[0119] In this embodiment, step S1133 involves establishing the correspondence between the differential value and the cumulative charging capacity to generate the voltage differential-capacity curve.

[0120] Each calculated differential value is mapped point-to-point to its corresponding cumulative charging capacity, thus generating a complete voltage differential-capacity curve. This voltage differential-capacity curve abstracts the electrical parameters that originally changed over time into an electrochemical spectrum that is only related to the internal physical state of the battery, providing a standard and intuitive data benchmark for subsequent identification of characteristic shifts caused by the consumption of expansion medium.

[0121] Therefore, the time dimension can first be converted into a cumulative capacity axis using current integration; then, the voltage signal is amplified into differential characteristic values ​​through voltage-capacity differential calculation; finally, a mapping relationship between the two is established to generate a voltage differential-capacity curve reflecting the internal phase transition state. This process effectively eliminates external fluctuation interference, extracts the characteristic fingerprints of mapped electrode slip and dielectric consumption, and provides a standardized and high-quality data benchmark for subsequent determination of the aging stage by capturing characteristic peak shifts.

[0122] In one embodiment, step S112, acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range, includes step S1121.

[0123] In this embodiment, step S1121 involves acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range when the expanded battery is in constant current charging mode.

[0124] In this step, the current charging state of the expanded battery is first identified. Sampling logic is triggered only when the battery is in constant current (CC) charging and its real-time voltage falls within the preset target voltage acquisition range. In practical applications, the battery management system determines the charging mode by monitoring the current fluctuations in the charging circuit. If the current remains constant (allowing for small fluctuations), it is confirmed that the current mode is constant current. At this time, voltage and current values ​​are synchronously recorded at a preset frequency (such as 1kHz, 10kHz, or other frequencies) until the current voltage falls outside the target voltage acquisition range.

[0125] Understandably, acquiring data in constant current charging mode ensures a very high linearity between capacity increment and time increment, eliminating nonlinear interference caused by current fluctuations in differential calculations.

[0126] In one embodiment, step S1121, when the expanded battery is in constant current charging mode, acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range includes step S1122.

[0127] In this embodiment, step S1122 involves acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range when the expanded battery is in constant current charging mode and the real-time charging rate is less than a preset rate threshold.

[0128] This step, based on the constant current mode, further adds a real-time charging rate constraint. Specifically, data acquisition will only be performed when the charging current (rate) is lower than a preset rate threshold. Optionally, the preset rate threshold can be set to 0.1C or 0.3C; the specific setting is not limited here. When a high current charging is detected (i.e., the charging current exceeds the preset rate threshold), the current data acquisition will be automatically skipped. Data recording will only be initiated within the target voltage acquisition range under the dual conditions of constant current and low current.

[0129] Understandably, under high-current charging conditions, the internal ohmic resistance and electrode polarization of the battery will cause a significant voltage drop, leading to a deviation of the voltage curve from thermodynamic equilibrium and resulting in a false shift of the characteristic peaks. By collecting data at low rates, the battery can be kept in a quasi-static equilibrium process to the maximum extent, thereby capturing the purest characteristic peak positions with the smallest shift error and improving the accuracy of aging stage assessment.

[0130] In one embodiment, such as Figure 6 As shown, step S120, determining the working stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times, includes steps S121 and S122.

[0131] In this embodiment, step S121 involves determining the offset direction and corresponding offset amount between the voltage differential-capacity curves at at least two different times.

[0132] In this embodiment, step S122 involves determining the working stage of the expanded battery based on the determined offset direction and the corresponding offset amount.

[0133] By comparing the currently acquired voltage-capacity differential curve with the pre-stored historical voltage-capacity differential curves, the spatial evolution characteristics of homogeneous characteristic peaks in the voltage-capacity curves can be identified. Since the aging of extended-capacity batteries manifests as relative slippage between electrode materials, this slippage directly causes a shift in the position of characteristic peaks along the capacity axis. Thus, the lateral direction of peak movement (leftward or rightward shift) can be identified. Subsequently, by extracting the capacity coordinate values ​​of the corresponding peaks in the two curves and calculating the difference, the offset can be calculated. Based on this, the current operating stage of the extended-capacity battery can be analyzed.

[0134] It is worth noting that the offset direction and corresponding offset amount between the voltage differential-capacity curves at two different times constitute a two-dimensional vector feature characterizing the evolution of the internal state of the expanded capacity battery. The offset direction indicates the electrode slip polarity, i.e., the lateral direction of active lithium ion depletion; the offset amount quantifies the degree of loss. In the judgment logic, the offset amount is the direct criterion for defining the lifetime range, dividing it into different ranges (such as the stage of abundant expanded capacity medium or the stage after depletion) through a preset threshold. At the same time, the offset direction reflects the dominant relationship between active lithium loss and active medium loss, and is a key basis for determining whether the aging mechanism has switched. The characteristic peak of the normal consumption period shifts stably along a single direction; if the direction changes abruptly, it indicates the risk of lithium plating caused by the depletion of expanded capacity medium or a sharp increase in polarization.

[0135] Optionally, if the system detects a large offset value, but the offset direction contradicts the expected physical trend, step S122 will identify such data as interference caused by environmental noise or occasional operating condition fluctuations, thereby rejecting erroneous state switching commands. This directional correction mechanism improves the decision-making reliability of the extended battery management system throughout its entire lifecycle.

[0136] Understandably, the voltage differential-capacity curves at at least two different times include the curve acquired at the current time and a reference curve from at least one historical time. This historical time can be a baseline time in the battery's initial state (such as the factory state or the fresh state after the first compensation) to assess the cumulative consumption of the expansion medium relative to the initial state; or it can be the previous charging cycle or multiple preset specific life cycle nodes (such as the 100th or 500th cycle). By comparing the displacement of adjacent or cross-nodes, it is possible to monitor in real time whether the dynamic rate of change of battery aging and its evolution rate have abruptly changed.

[0137] Furthermore, step S121 can also employ statistical fitting of curves at multiple time points to determine the offset pattern. This can be achieved by extracting the characteristic peak coordinates from the most recent consecutive charging cycles and constructing a time-series model of the characteristic displacement using algorithms such as least squares or linear regression. Compared to comparing two curves at a single time point, this method can effectively smooth out random fluctuations or polarization deviations in a single sampling. By determining the average offset intensity and direction of the curve on the capacity axis, it can more robustly identify the true physical slippage trend inside the battery.

[0138] In one embodiment, such as Figure 7 As shown, step S122, determining the working stage of the expanded battery according to the determined offset direction and the corresponding offset amount, includes steps S1221 to S1223.

[0139] In this embodiment, step S1221, if the voltage differential-capacity curve at the current moment shifts towards a higher capacity direction relative to the voltage differential-capacity curve at a historical moment, and the shift amount is greater than a first preset shift amount, it is determined that the capacity-expanding battery is in a first preset stage.

[0140] When the system detects that the voltage differential-capacity curve at the current moment has shifted to the right (in the direction of higher capacity) relative to the voltage differential-capacity curve at a historical moment, and the shift exceeds a first preset shift threshold, the system determines that the battery is in a first preset stage. This phenomenon corresponds to the drastic electrochemical evolution of the capacity-enhanced battery within a specific cycle range, for example, the capacity-enhancing medium (such as the active lithium source) is being rapidly consumed to compensate for the loss of the basic active medium.

[0141] From a physical mechanism perspective, during the cycling process of a capacity-enhancing battery, the capacity-enhancing medium on the negative electrode side continuously releases lithium ions to compensate for the active lithium lost due to side reactions. This is macroscopically manifested as a significant shift in the negative electrode potential curve relative to the positive electrode potential curve on the capacity axis. When the characteristic peak of the voltage differential-capacity curve shows a rightward shift exceeding a first preset threshold, it indicates that the battery is in a period of efficient release of the capacity-enhancing medium or at a turning point of a sudden increase in the basic aging rate. This judgment logic captures the critical point of battery evolution. Traditional management logic often struggles to perceive the severity of internal medium consumption in real time, while step S1221, through a combination of offset direction and offset amount criteria, can eliminate the slight fluctuations caused by normal aging and pinpoint the life cycle segment with the most drastic battery performance evolution. After determining it to be in the first preset stage, the system can immediately identify that the battery is in the active period with the strongest lithium replenishment effect, thus providing a high-confidence physical basis for subsequent targeted adjustments to the charging cutoff voltage or rate strategy.

[0142] In this embodiment, step S1222, if the voltage differential-capacity curve at the current moment shifts towards a higher capacity direction relative to the voltage differential-capacity curve at a historical moment, and the shift amount is not greater than a first preset shift amount, it is determined that the capacity-expanding battery is in the second preset stage.

[0143] In step S1222, if the curve also shifts towards higher capacity, but the shift is at a low level (i.e., not greater than the first preset shift), the battery is determined to be in the second preset stage. This indicates that the electrode slippage inside the battery is relatively slow, and the compensation effect of the capacity-expanding medium and the consumption caused by basic aging are in a relatively balanced state. This condition is classified as the second preset stage. From a physical mechanism perspective, in this stage, the rate at which the capacity-expanding medium releases lithium ions and the rate at which active lithium is lost due to basic aging are in a dynamic equilibrium. At this time, the relative slippage between the positive and negative electrode materials is not drastic, and the mapping relationship between the battery's state of charge and voltage remains stable.

[0144] In this embodiment, step S1223, when the voltage differential-capacity curve at the current moment shifts towards a lower capacity direction relative to the voltage differential-capacity curve at a historical moment, determines that the expanded capacity battery is in the second preset stage.

[0145] From a physical mechanism perspective, the reverse offset towards lower capacity may be a false displacement caused by fluctuations in operating conditions. This phenomenon may be caused by the self-recovery of potential after the battery has been idle for a long time, random polarization differences between charge and discharge cycles, or fluctuations in the sampling environment temperature. Therefore, step S1223 treats this reverse offset as an allowable fluctuation deviation or diagnostic dead zone. Through this logical processing, noise interference caused by the randomness of operating conditions can be effectively filtered out.

[0146] The historical moment can be the reference moment in the initial state of the battery, or it can be the node of the previous charging cycle.

[0147] In summary, combining steps S1221 to S1223, the battery is determined to enter the first preset stage of drastic evolution only when the offset direction is towards the high capacity direction and the offset amount exceeds the first preset threshold; other minor positive offset, reverse offset or no offset conditions are all determined to be the second preset stage.

[0148] Optionally, the specific value of the first preset threshold is not limited here, but depends on the actual battery characteristics.

[0149] In one embodiment, such as Figure 8 As shown, step S121, determining the offset direction and corresponding offset amount between the voltage differential-capacity curves at at least two different times, includes steps S1211 to S1215.

[0150] In this embodiment, step S1211 involves determining the first peak capacity corresponding to the characteristic peak in the voltage differential-capacity curve at the current moment, and the second peak capacity corresponding to the characteristic peak in the voltage differential-capacity curve at a historical moment.

[0151] It is understandable that in step S1211, in order to determine the offset direction and corresponding offset between the voltage differential-capacity curves at at least two different times, two methods are used: within the selected target voltage acquisition interval, the local maximum point of the voltage differential-capacity curve is retrieved using a peak-finding algorithm, and the specific value of the characteristic peak on the capacity axis is recorded.

[0152] It is important to note that the two characteristic peaks specifically correspond to characteristic sites with the same electrochemical significance in the voltage differential-capacity curve. Although the characteristic peaks numerically represent local maxima on the voltage differential axis (Y-axis), during the matching process, it is crucial to ensure that the selected characteristic peak at the current moment and the characteristic peak at a historical moment are of the same origin. That is, these two peaks must correspond to the same phase transition reaction plateau within the battery and be located at the same relative position in the evolution trajectory. Only in this way can we ensure that the calculated offset is an effective displacement based on the same physical reference.

[0153] The first peak capacity is the projected coordinate of the characteristic peak at the current moment onto the capacity axis (X-axis) of the voltage-capacity curve at the current moment; the second peak capacity is the projected coordinate of the characteristic peak at a historical moment onto the capacity axis (X-axis) of the voltage-capacity curve at a historical moment. At a physical level, these two capacity values ​​respectively lock in the cumulative charge required for the battery to complete a specific electrochemical phase transition at different points in its life cycle. Because battery aging causes relative slippage of the electrode materials, resulting in an overall displacement of the voltage plateau, the absolute values ​​of these two characteristic peaks on the capacity axis will deviate, i.e., there will be a slight difference between the first and second peak capacities. Therefore, by calculating the coordinate difference between these two homologous characteristic peaks on the capacity axis, the physical scale of material slippage within the battery can be quantified.

[0154] In this embodiment, step S1212 involves calculating the difference between the first peak capacity and the second peak capacity.

[0155] In this method, the first peak capacity extracted at the current moment is used as the minuend, and the second peak capacity extracted at a historical moment is used as the subtrahend. The algebraic difference between the two is calculated as: Difference = First Peak Capacity - Second Peak Capacity. The calculated difference not only quantifies the displacement span of the characteristic peak in absolute value, but its inherent positive or negative sign directly maps the vector direction of the displacement.

[0156] In this embodiment, step S1213, if the difference is positive, determines that the offset direction is offset towards the high capacity direction.

[0157] Specifically, when the difference between the first peak capacity and the second peak capacity is positive, it means that the cumulative capacity corresponding to the current electrochemical phase transition point is greater than the historical baseline value, i.e., the characteristic peak has shifted to the right on the spectrum. From a physical mechanism perspective, this shift towards higher capacity is a standard characteristic of the cycle degradation of extended-capacity batteries. It characterizes the relative slippage of the charge-discharge curves of the positive and negative electrode materials as the internal capacity-enhancing medium (such as the active lithium source) is continuously released and consumed, along with the accompanying irreversible loss of active lithium. In terms of macroscopic electrical performance, this means that the battery must be charged with more electricity than before to drive the internal materials to reach the same phase transition reaction plateau as at historical moments. Therefore, clarifying this shift direction provides a deterministic logical premise for confirming that the battery is undergoing substantial consumption of the capacity-enhancing medium.

[0158] In this embodiment, step S1214, when the difference is negative, determines that the offset direction is offset towards the low capacity direction.

[0159] When the difference between the first peak capacity and the second peak capacity is negative, it means that the cumulative capacity required to reach the phase transition point at the current moment has actually decreased, and the characteristic peak has shifted to the left on the spectrum. From a physical mechanism perspective, this reverse shift towards lower capacity may not originate from irreversible structural aging of the battery. Instead, it may be a pseudo-displacement caused by fluctuations in operating conditions, such as a sudden increase in ambient temperature leading to a decrease in internal resistance and polarization, or the self-recovery of potential after the battery has been idle for a long time. Introducing step S1214 into the battery management system, by separately isolating and accurately identifying this negative shift, can prevent short-term environmental noise from being misjudged as real aging degradation, thereby ensuring the anti-interference capability and robustness of the diagnostic algorithm throughout the entire lifespan.

[0160] In this embodiment, step S1215 involves determining the absolute value of the difference as the corresponding offset.

[0161] In this step, the system performs an absolute value operation on the algebraic difference calculated in the previous step S1212, thereby converting the algebraic difference, which has positive and negative attributes, into a purely non-negative scalar value. The absolute value of the difference removes the influence of the direction of shift. This absolute value quantifies the absolute physical span of the characteristic peak shift on the capacity axis (X-axis) and reflects the degree of deviation of the battery's current electrochemical state from the historical benchmark.

[0162] At the system algorithm implementation level, extracting the absolute value as a unified metric greatly optimizes the subsequent logical decision-making process. Through this transformation, when executing the subsequent step S122 (stage determination), the system no longer needs to design two sets of complex numerical comparison logics for positive and negative offsets. Instead, it directly compares the absolute offset with the first preset offset. This reduces the computational complexity of the control program and improves execution efficiency.

[0163] Of course, in other embodiments, the specific calculation logic of step S1212 can also be adaptively adjusted to: calculate the difference between the second peak capacity (historical baseline) and the first peak capacity (current moment), i.e., difference = second peak capacity - first peak capacity. Under this calculation rule, the system's determination logic for the offset direction (i.e., steps S1213 and S1214) will undergo a corresponding polarity reversal. It should be noted that, regardless of whether the current minus the historical or the historical minus the current difference calculation method is used, the core purpose is to obtain the vector characteristics of the characteristic peak displacement.

[0164] In conjunction with the above embodiments and referring to Figures 10 to 12 , Figures 10 to 12 Medium aging state 1 can be the initial state of the corresponding battery or the freshest state with the most abundant expansion medium, while aging state 4 is the extreme state with the deepest aging (or the most complete consumption of expansion medium). That is, aging state 1, aging state 2, aging state 3, and aging state 4 are ordered in ascending order of aging severity. Figure 10 The capacity differential-voltage curves of the expanded battery under four different aging conditions are shown. Figure 10 It includes peaks A, B, and C, which characterize different stages of the electrochemical reaction. Among them, Figure 11 It is taken from Figure 10 The voltage differential-capacitance curve is obtained by converting voltage data in the 3.2V-3.3V range. From... Figure 11 As can be seen from this, the characteristic peaks (corresponding to) within this voltage range Figure 10 The region near peaks A and B exhibits a relatively complex evolution along the capacity axis as aging progresses, with a smaller overall shift and a tendency for overlapping morphologies. In contrast, Figure 12 To be taken from Figure 10 The voltage differential-capacitance curve is obtained by converting data in the 3.32V-3.35V voltage range. For example... Figure 12 As shown, the characteristic peaks (corresponding to) within this interval Figure 10 The C peak (in the image) shows a trend of shifting towards higher capacity (i.e., to the right) as the aging process progresses (from aging state 1 to aging state 4). Therefore, by comparison... Figure 11 and Figure 12It can be seen that when the system performs the aforementioned steps, it will prioritize obtaining information such as... Figure 12 Feature extraction is performed on a specific voltage range that exhibits significant unidirectional displacement characteristics.

[0165] Reference Figure 12 It is important to note that in the early to mid-stages of battery aging (e.g., aging state 2 to aging state 3), the battery has a relatively sufficient reserve of additional active media. To compensate for the irreversible loss of active lithium during cycling, this additional media is released in large quantities, leading to significant relative slippage, which is manifested as a large shift of the characteristic peak on the voltage differential-capacity curve towards higher capacity. However, as the aging process progresses to state 3 and evolves towards state 4, the pre-installed additional capacity-enhancing media inside the battery has been largely consumed and is nearing depletion. At this point, it is gradually approaching the physical critical point of transition from the first preset stage (positive electrode capacity-limiting stage) to the second preset stage (active lithium-limiting stage). Due to the lack of sufficient additional active media to continue supporting this consumption, the relative slippage effect between electrode materials is significantly weakened or even stagnates. The thermodynamic boundary of the battery then undergoes a fundamental shift, and the overall capacity decay begins to be limited by the total amount of active lithium remaining in the system. This is manifested as a relatively small shift of the characteristic peak on the voltage differential-capacity curve, exhibiting a stable state.

[0166] In one embodiment, such as Figure 9 As shown, step S120, determining the working stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times, includes steps S123 and S124. It can be understood that steps S123 and S124, compared to steps S121 and S122, are two independent implementation methods; that is, one of them can be chosen to specifically implement step S120.

[0167] In this embodiment, step S123 involves determining the offset direction between the voltage differential-capacity curves at at least two different times.

[0168] By comparing the currently acquired voltage-capacity differential curve with the pre-stored historical voltage-capacity differential curves, the spatial evolution characteristics of homogeneous characteristic peaks in the voltage-capacity curves are identified. Since the aging of expanded-capacity batteries manifests as relative slippage between electrode materials, this slippage directly causes a shift in the position of characteristic peaks along the capacity axis. By extracting the capacity coordinate values ​​of the corresponding peak apexes from the two curves, the lateral direction of peak movement (e.g., a rightward shift towards higher capacity or a leftward shift towards lower capacity) is identified without the need for additional calculation of the specific absolute shift magnitude.

[0169] In this embodiment, step S124 involves determining the working stage of the expanded capacity battery based on the determined offset direction.

[0170] It is worth noting that the offset direction between the voltage differential-capacity curves at two different times constitutes the core directional feature characterizing the internal state evolution of the extended-capacity battery. The offset direction directly indicates the polarity of electrode slip, i.e., the lateral direction of active lithium-ion depletion. It reflects the dominant relationship between active lithium loss (LLI) and active medium loss (LAM), and is a key basis for determining whether the aging mechanism has undergone a fundamental switch. During the normal consumption period of the extended medium, the characteristic peak shifts stably along a single direction (e.g., continuously towards the high-capacity direction). Once it is determined that this offset direction changes abruptly or exhibits an unexpected reversal, it indicates that the extended medium may have been depleted, triggering the risk of lithium plating or a sharp increase in polarization inside the battery. Based on this, it can be diagnosed that the battery has entered a new basic aging stage.

[0171] Optionally, if the detected offset direction is contrary to the long-term physical aging trend of the expanded battery (e.g., a sudden leftward shift after a long-term rightward shift), step S124 can identify such atypical directions as false interference caused by environmental noise (such as drastic changes in ambient temperature) or occasional fluctuations in operating conditions, thereby rejecting the execution of the erroneous state switching command.

[0172] Understandably, the voltage differential-capacity curves at at least two different times include the curve acquired at the current time and a reference curve from at least one historical time. This historical time can be a baseline time in the initial state of the battery (such as the factory state or the fresh state after the first compensation) to assess the overall evolution polarity of the capacity expansion medium; or it can be the previous charging cycle or multiple preset specific life cycle nodes (such as the 100th or 500th cycle). By comparing the directional consistency of adjacent or cross-nodes, it is possible to monitor in real time whether the battery aging path has deviated.

[0173] Secondly, this application provides a battery management system configured to implement the capacity expansion battery management method described above.

[0174] In this embodiment, the battery management system includes a control device for storing and executing the battery capacity expansion management method described above. The control device can be implemented using a main controller, such as an MCU, DSP (Digital Signal Processor), PLC, SOC (System-on-Chip), or FPGA (Field-Programmable Gate Array). Optionally, the main controller can integrate both a processor and a memory. Optionally, the control device can also include a memory additionally electrically connected to the main controller. Optionally, in addition to the main controller, the control device can also have peripheral circuitry that cooperates with the main controller, including at least one of the following functional circuits: current detection circuit, voltage detection circuit, main controller port matching circuit, sensor detection circuit, and communication matching circuit.

[0175] In this embodiment, optionally, the battery management system can be integrated with the extended-capacity battery in the same battery pack, so that the control device in the battery management system can execute the extended-capacity battery management method process for the battery according to the processes in some embodiments of this application described above. Alternatively, the battery management system can also be set up separately to execute the extended-capacity battery management method in some embodiments of this application for the connected battery. Thus, through the above settings, the battery management system of this application can improve the management accuracy of charging and discharging the extended-capacity battery when it is connected.

[0176] Optionally, the first and second voltage management curves can be preset data tables, multidimensional mapping matrices, or parameterized function models stored in the local memory of the control device (such as non-volatile storage media like EEPROM or Flash). Before the battery leaves the factory, these curve data can be directly burned and solidified into the storage unit as underlying calibration parameters, so that the main controller can perform fast addressing, calling, and interpolation calculations in real time according to the determined current working stage during actual operation, thereby outputting the corresponding voltage control commands without delay. In addition, in embodiments with vehicle-to-cloud or Internet of Things (IoT) interaction capabilities, the first and second voltage management curves can also be dynamic configuration files stored on a remote cloud server. During operation, the battery management system can establish a data connection with the cloud server through its communication matching circuit (such as an onboard T-BOX or wireless communication module) and periodically acquire, verify, or update these curve data using over-the-air (OTA) download technology.

[0177] It should be noted that this battery management system includes the aforementioned expanded battery management method. Therefore, this battery management system adopts all the technical solutions of all the above embodiments and has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be elaborated here.

[0178] Thirdly, this application provides a battery device, which includes the battery management system described above.

[0179] It should be noted that the battery device adopts all the technical solutions of all the above embodiments, and therefore has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be repeated here.

[0180] In some embodiments of this application, the battery device has a power battery and a controller. The controller is used to determine the operating mode of the battery device and, based on the operating mode, control the power battery to output electrical energy to the load device connected to the battery device.

[0181] The controller in the battery device can be a battery management system or a microcontroller, etc., which can be used to manage and control the power battery (for expanded capacity batteries) of the battery device.

[0182] Fourthly, this application provides an electrical device, which includes: an extended capacity battery and a battery device or a battery management system as described above.

[0183] It should be noted that the electrical equipment adopts all the technical solutions of all the above embodiments, and therefore has at least all the beneficial effects brought about by the technical solutions of the above embodiments, which will not be repeated here.

[0184] For ease of explanation, the following embodiments use a vehicle as an example of electrical equipment.

[0185] For example, such as Figure 14 As shown, vehicle 1 can be a gasoline-powered vehicle, a natural gas-powered vehicle, or a new energy vehicle. New energy vehicles can be pure electric vehicles, hybrid electric vehicles, or range-extended electric vehicles, etc. The interior of vehicle 1 can house a motor 400, a controller 300, and a battery device 100. The controller 300 controls the battery device 100 to supply power to the motor 400. For example, the battery device 100 can be located at the bottom, front, or rear of vehicle 1. The battery device 100 can be used to power vehicle 1; for example, it can serve as the operating power source for the vehicle 1's electrical system, such as meeting the power requirements for starting, navigation, and operation. In another embodiment of this application, the battery device 100 can not only serve as the operating power source for vehicle 1 but also as the driving power source, replacing or partially replacing gasoline or natural gas to provide driving power to vehicle 1.

[0186] Of course, electrical equipment includes, but is not limited to, electric vehicles, energy storage systems, electric ships, drones, and consumer electronics.

[0187] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this application, and not 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 or all of the technical features therein. These modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of this application, and they should all be covered within the scope of the claims and specification of this application. In particular, as long as there is no technical conflict, the various technical features mentioned in the various embodiments can be combined in any way. This application is not limited to the specific embodiments disclosed herein, but includes all technical solutions falling within the scope of the claims.

Claims

1. A method for managing extended-capacity batteries, characterized in that, The expanded battery management method includes: Obtain the voltage differential-capacity curve of the expanded capacity battery during the charging process, and determine the working stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times, wherein the voltage differential is the differential of voltage with respect to capacity; When the expanded capacity battery is in a first preset stage of operation, the expanded capacity battery is managed based on a first voltage management curve, which characterizes the voltage characteristics of the expanded capacity battery when its expanded capacity is not depleted; and / or, When the expanded capacity battery is in the second preset stage of operation, the expanded capacity battery is managed based on the second voltage management curve, which characterizes the voltage characteristics of the expanded capacity battery in the state of depleted expanded capacity. The first preset stage is the positive electrode capacity limitation stage, and the second preset stage is the active lithium limitation stage; The process of determining the operating stage of the expanded capacity battery based on the changing trend of the voltage differential-capacity curve at different times includes: Determine the offset direction and corresponding offset amount between the voltage differential-capacitance curves at at least two different times; The operating stage of the expanded battery is determined based on the determined offset direction and the corresponding offset amount.

2. The battery capacity management method as described in claim 1, characterized in that, Both the first voltage management curve and the second voltage management curve are open-circuit voltage-state-of-charge curves.

3. The battery capacity management method as described in claim 1, characterized in that, The process of obtaining the voltage differential-capacity curve of the expanded capacity battery during charging includes: While the expanded battery is charging, the current voltage of the expanded battery is acquired, and the corresponding target voltage acquisition range is determined based on the acquired current voltage. Within the target voltage acquisition range, the charging voltage and charging current of the expanded battery are acquired at a preset frequency. Based on the obtained charging voltage and charging current, the voltage differential-capacity curve of the expanded battery during the charging process is determined.

4. The battery management method for expanding capacity as described in claim 3, characterized in that, Before acquiring the current voltage of the expanded battery and determining the corresponding target voltage acquisition range based on the acquired current voltage while the expanded battery is charging, the expanded battery management method further includes: Obtain the capacity differential-voltage curve of the expanded battery; Based on the capacity differential peak of the acquired capacity differential-voltage curve, the capacity differential-voltage curve is divided into multiple voltage intervals along the voltage horizontal axis, wherein each voltage interval corresponds to at least one capacity differential peak, and the target voltage acquisition interval is selected from multiple voltage intervals.

5. The battery management method for increased capacity as described in claim 3, characterized in that, The step of determining the voltage differential-capacity curve of the expanded battery during the charging process based on the acquired charging voltage and charging current includes: Based on the charging current, the cumulative charging capacity within the target voltage acquisition range is obtained; Determine the derivative of the charging voltage with respect to the cumulative charging capacity; Establish the correspondence between the differential value and the cumulative charging capacity to generate the voltage differential-capacity curve.

6. The battery management method for expanding capacity as described in claim 3, characterized in that, The step of acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range includes: When the expanded battery is in constant current charging mode, the charging voltage and charging current of the expanded battery are acquired at a preset frequency within the target voltage acquisition range.

7. The battery capacity management method as described in claim 6, characterized in that, When the expanded battery is in constant current charging mode, acquiring the charging voltage and charging current of the expanded battery at a preset frequency within the target voltage acquisition range includes: When the expanded battery is in constant current charging mode and the real-time charging rate is less than a preset rate threshold, the charging voltage and charging current of the expanded battery are acquired at a preset frequency within the target voltage acquisition range.

8. The battery management method for expanding capacity as described in claim 1, characterized in that, The step of determining the working stage of the expanded battery based on the determined offset direction and corresponding offset amount includes: If the voltage differential-capacity curve at the current moment shifts towards a higher capacity direction relative to the voltage differential-capacity curve at a historical moment, and the shift amount is greater than a first preset shift amount, then the expanded capacity battery is determined to be in a first preset stage. If the voltage differential-capacity curve at the current moment shifts towards a higher capacity direction relative to the voltage differential-capacity curve at a historical moment, and the shift amount is not greater than a first preset shift amount, then the expanded capacity battery is determined to be in a second preset stage. If the voltage differential-capacity curve at the current moment shifts towards a lower capacity direction relative to the voltage differential-capacity curve at a historical moment, it is determined that the expanded capacity battery is in the second preset stage.

9. The battery management method for expanding capacity as described in claim 1, characterized in that, Determining the offset direction and corresponding offset amount between the voltage differential-capacity curves at at least two different times includes: Determine the first peak capacity corresponding to the characteristic peak in the voltage differential-capacity curve at the current moment, and the second peak capacity corresponding to the characteristic peak in the voltage differential-capacity curve at historical moments; Calculate the difference between the first peak capacity and the second peak capacity; If the difference is positive, the offset direction is determined to be an offset towards the high-capacity direction; If the difference is negative, the offset direction is determined to be an offset towards the lower capacity direction; The absolute value of the difference is determined as the corresponding offset.

10. A battery management system, characterized in that, The battery management system is configured to implement the capacity expansion battery management method as described in any one of claims 1 to 9.

11. A battery device, characterized in that, The battery device includes the battery management system as described in claim 10.

12. An electrical appliance, characterized in that, The electrical equipment includes: Expanded battery capacity; The battery management system as described in claim 10 or the battery device as described in claim 11.

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