Battery capacity estimation method, electronic equipment and storage medium

Abstract

The embodiment of the invention discloses a battery capacity estimation method, electronic equipment and a storage medium. A first differential voltage association relationship corresponding to a to-be-evaluated target battery is obtained, and the first differential voltage association relationship indicates the relationship between the voltage of the target battery and the battery capacity; determining a first feature interval corresponding to the target battery based on the first differential voltage association relationship, wherein the first feature interval is determined based on the loss condition of the active substance in the target battery; and determining a first target battery capacity corresponding to the target battery based on the first feature interval and a battery capacity estimation model corresponding to the target battery. Therefore, accurate capacity estimation can be carried out on the battery without higher data acquisition precision requirement and time cost, so that the battery capacity estimation efficiency is effectively improved.

Description

Technical Field

[0001] The present application relates to the field of battery technology, and in particular to a battery capacity estimation method, electronic device, and storage medium. Background Art

[0002] To ensure proper battery operation in communications energy storage systems, it's often necessary to estimate battery capacity to determine the battery's degradation stage. Existing battery capacity estimation methods typically use ampere-hour integration, accumulating the integral of the battery's charge and discharge current to estimate the remaining charge.

[0003] During the research and practice of existing technologies, it was found that the existing battery capacity estimation method using ampere-hour integration has relatively high requirements for data acquisition accuracy, and the battery needs to be fully charged and discharged during the estimation process, which results in high time costs and thus low efficiency in battery capacity estimation. Summary of the Invention

[0004] The embodiments of the present application provide a battery capacity estimation method, electronic device, and storage medium, which can accurately estimate the battery capacity of a battery without requiring high data acquisition accuracy and time costs, thereby effectively improving the efficiency of battery capacity estimation.

[0005] The present invention provides a method for estimating battery capacity, including:

[0006] Obtaining a first differential voltage association relationship corresponding to a target battery to be evaluated, where the first differential voltage association relationship indicates a relationship between a voltage and a battery capacity of the target battery;

[0007] determining a first characteristic interval corresponding to the target battery based on the first differential voltage association relationship, where the first characteristic interval is determined based on a loss of active material in the target battery;

[0008] A first target battery capacity corresponding to the target battery is determined based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery.

[0009] Accordingly, an embodiment of the present application further provides a battery capacity estimation device, comprising:

[0010] an acquiring unit, configured to acquire a first differential voltage association relationship corresponding to a target battery to be evaluated, where the first differential voltage association relationship indicates a relationship between a voltage and a battery capacity of the target battery;

[0011] a first determining unit, configured to determine a first characteristic interval corresponding to the target battery based on the first differential voltage association relationship, wherein the first characteristic interval is determined based on a loss of active material in the target battery;

[0012] The second determining unit is configured to determine a first target battery capacity corresponding to the target battery based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery.

[0013] In one embodiment, the acquiring unit is configured to:

[0014] Acquire first voltage data of a target battery to be evaluated and first battery capacity data corresponding to the first voltage data;

[0015] A first differential voltage association relationship of the target battery is established based on the first voltage data and the first battery capacity data.

[0016] In one embodiment, the first differential voltage association relationship of the target battery is constructed based on the first voltage data and the first battery capacity data, specifically for:

[0017] constructing a voltage curve based on the first voltage data and the first battery capacity data, wherein the ordinate of the voltage curve is voltage and the abscissa of the voltage curve is battery capacity;

[0018] Performing differential processing on the voltage curve to obtain a first differential voltage correlation relationship of the target battery.

[0019] In one embodiment, the first determining unit is configured to:

[0020] determining a characteristic peak in the first differential voltage correlation relationship;

[0021] Determining a first characteristic peak and a second characteristic peak among the characteristic peaks;

[0022] A first characteristic interval corresponding to the target battery is determined based on the first characteristic peak and the second characteristic peak.

[0023] In one embodiment, the determining of the first characteristic peak and the second characteristic peak from the characteristic peaks is specifically used for:

[0024] Obtaining a battery capacity value corresponding to the characteristic peak in the first differential voltage association relationship;

[0025] Calculating the distance between the characteristic peaks based on the battery capacity value;

[0026] A first characteristic peak and a second characteristic peak are determined among the characteristic peaks based on the distance.

[0027] In one embodiment, the battery capacity estimation model includes a mapping relationship between the battery capacity difference and the target battery capacity, and the second determining unit is configured to:

[0028] Obtaining a first target battery capacity difference corresponding to the first characteristic interval in the first differential voltage association relationship;

[0029] A first target battery capacity corresponding to the target battery is determined based on the first target battery capacity difference and a mapping relationship between the battery capacity difference and the target battery capacity indicated by a battery capacity estimation model.

[0030] In one embodiment, the battery capacity estimation device further includes a model building unit configured to:

[0031] Acquire second voltage data of a plurality of batteries at different degradation stages and second battery capacity data corresponding to the second voltage data, where the type of the batteries is the same as that of the target battery;

[0032] constructing a second differential voltage association relationship corresponding to the battery based on the second voltage data and the second battery capacity data;

[0033] determining a second characteristic interval corresponding to the battery based on the second differential voltage association relationship;

[0034] A battery capacity estimation model is constructed based on the second target battery capacities of the plurality of batteries in the fully charged state and the second characteristic intervals.

[0035] In one embodiment, the battery capacity estimation model is constructed based on the second target battery capacities of the plurality of batteries in a fully charged state and the second characteristic intervals, and is specifically used for:

[0036] Acquire a plurality of second target battery capacities of the batteries in a fully charged state, and second target battery capacity differences of the second characteristic intervals in the second differential voltage association relationship;

[0037] Curve fitting is performed based on the second target battery capacity differences corresponding to the plurality of batteries and the second target battery capacity to obtain a battery capacity estimation model.

[0038] In addition, an embodiment of the present application also provides an electronic device, including a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor performs the steps of any one of the battery capacity estimation methods provided in the embodiments of the present application.

[0039] In addition, an embodiment of the present application also provides a computer-readable storage medium, including a computer program. When the computer program is run on an electronic device, the computer program is used to enable the electronic device to perform any step of the battery capacity estimation method provided in the embodiment of the present application.

[0040] In addition, an embodiment of the present application also provides a computer program product, including a computer program, which is stored in a computer-readable storage medium; when a processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, so that the electronic device performs any step of the battery capacity estimation method provided in the embodiment of the present application.

[0041] The embodiment of the present application obtains a first differential voltage correlation relationship corresponding to a target battery to be evaluated, wherein the first differential voltage correlation relationship indicates the relationship between the voltage and battery capacity of the target battery; determines a first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship, wherein the first characteristic interval is determined based on the loss of active materials in the target battery; and determines a first target battery capacity corresponding to the target battery based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery. Thus, by constructing a differential voltage correlation relationship for the target battery to be evaluated, a first characteristic interval corresponding to the target battery, which characterizes the battery degradation based on the loss of active materials in the battery, is determined based on the differential voltage correlation relationship. Furthermore, based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery, the first target battery capacity corresponding to the target battery is determined. This allows for battery capacity estimation without requiring high data acquisition accuracy and without requiring the battery to be fully charged or discharged. This further allows for accurate battery capacity estimation without requiring high data acquisition accuracy and time costs, thereby effectively improving the efficiency of battery capacity estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0042] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0043] Figure 1 Schematic diagram of an implementation scenario of a battery capacity estimation method provided in an embodiment of the present application;

[0044] Figure 2 1 is a flow chart of a battery capacity estimation method provided in an embodiment of the present application;

[0045] Figure 3a 1 is a schematic diagram of a voltage curve of a battery capacity estimation method provided in an embodiment of the present application;

[0046] Figure 3b Schematic diagram of a model construction of a battery capacity estimation method provided in an embodiment of the present application;

[0047] Figure 3c This is a schematic diagram of a specific flow chart of a battery capacity estimation method provided in an embodiment of the present application;

[0048] Figure 4 is a structural diagram of a battery capacity estimation device provided in an embodiment of the present application;

[0049] Figure 5 It is a structural diagram of the electronic device provided in the embodiment of the present application. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of this application to clearly and completely describe the technical solutions in the embodiments of this application. Obviously, the embodiments described are only part of the embodiments of this application, not all of the embodiments. Based on the embodiments in this application, all other embodiments obtained by those skilled in the art without making creative efforts are within the scope of protection of this application.

[0051] At the same time, in the description of the embodiments of this application, the terms "first", "second", etc. are used only to distinguish the description and should not be understood as indicating or implying relative importance. Therefore, the features defined as "first" or "second" may explicitly or implicitly include one or more features. In the description of the embodiments of this application, the meaning of "plurality" is two or more, unless otherwise clearly and specifically defined.

[0052] To ensure proper battery operation in communication energy storage systems, it's often necessary to estimate battery capacity to determine the battery's degradation stage. Existing battery capacity estimation methods typically use ampere-hour integration, accumulating the integral of the battery's charge and discharge current to estimate the remaining battery charge. However, this ampere-hour integration method places high demands on data acquisition accuracy, and the battery needs to be fully charged and discharged during the estimation process, which increases the time cost and leads to low efficiency.

[0053] In order to solve the above technical problems existing in the prior art, an embodiment of the present application provides a battery capacity estimation method, which constructs a differential voltage curve of a target battery to be evaluated, and thereby determines a first characteristic interval corresponding to the target battery, which characterizes the battery degradation based on the loss of active substances in the battery, according to the differential voltage curve. Then, based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery, the first target battery capacity corresponding to the target battery is determined. This can achieve capacity estimation of the battery without the need for high data acquisition accuracy requirements and the need to fully charge and discharge the battery, and further achieves accurate battery capacity estimation of the battery without the need for high data acquisition accuracy requirements and time costs, thereby effectively improving the efficiency of battery capacity estimation.

[0054] The present invention provides a battery capacity estimation method, an electronic device, and a storage medium. The battery capacity estimation device can be integrated into an electronic device, which can be a server, a terminal, or other device.

[0055] Among them, the server can be an independent physical server, or a server cluster or distributed system composed of multiple physical servers, or a cloud server that provides cloud services, cloud databases, cloud computing, cloud functions, cloud storage, network services, cloud communications, middleware services, domain name services, security services, network acceleration services (Content Delivery Network, CDN), as well as basic cloud computing services such as big data and artificial intelligence platforms. Terminals may include but are not limited to mobile phones, computers, intelligent voice interaction devices, smart home appliances, vehicle-mounted terminals, aircraft, etc. Terminals and servers can be directly or indirectly connected through wired or wireless communication, and this application does not impose any restrictions on this.

[0056] See also Figure 1 , taking the battery capacity estimation device integrated into electronic equipment as an example, Figure 1 A schematic diagram of an implementation scenario of the battery capacity estimation method provided in an embodiment of the present application, wherein the electronic device can be a server or a terminal, and the electronic device can obtain a first differential voltage correlation relationship corresponding to a target battery to be evaluated, where the first differential voltage correlation relationship indicates a relationship between the voltage and battery capacity of the target battery; determine a first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship, where the first characteristic interval is determined based on the loss of active materials in the target battery; and determine a first target battery capacity corresponding to the target battery based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery.

[0057] It should be noted that Figure 1The schematic diagram of the implementation environment scenario of the battery capacity estimation method shown is only an example. The implementation environment scenario of the battery capacity estimation method described in the embodiment of the present application is to more clearly illustrate the technical solution of the embodiment of the present application and does not constitute a limitation on the technical solution provided by the embodiment of the present application. It is known to those skilled in the art that with the evolution of data processing and the emergence of new business scenarios, the technical solution provided in this application is also applicable to similar technical problems.

[0058] The solutions provided in the embodiments of the present application are specifically described by the following embodiments. It should be noted that the description order of the following embodiments does not limit the preferred order of the embodiments.

[0059] This embodiment will be described from the perspective of a battery capacity estimation device. The battery capacity estimation device may be integrated into an electronic device, which may be a server or a terminal. This application does not limit this.

[0060] See also Figure 2 , Figure 2 : is a flow chart of a battery capacity estimation method provided in an embodiment of the present application. The battery capacity estimation method includes:

[0061] In step 101, a first differential voltage association relationship corresponding to a target battery to be evaluated is obtained.

[0062] The first differential voltage correlation relationship indicates a relationship between the voltage of the target battery and the battery capacity.

[0063] The target battery may be a battery for which battery capacity evaluation is to be performed, for example, the target battery may be a lithium iron phosphate battery. Battery capacity may be a performance indicator for measuring a battery's ability to store electricity, typically expressed in milliampere-hours (mAh) or ampere-hours (Ah), reflecting the amount of electricity that can be released by the battery under specific conditions. The first differential voltage correlation may be a differential voltage correlation corresponding to the target battery, and the differential voltage correlation may characterize the correlation between the battery's differential voltage and battery capacity. For example, the first differential voltage correlation may be a differential voltage curve corresponding to the target battery, and may be a differential voltage curve constructed based on the first voltage data and the first battery capacity data.

[0064] Among them, there can be multiple ways to obtain the first differential voltage association relationship corresponding to the target battery to be evaluated. For example, the first voltage data of the target battery to be evaluated and the first battery capacity data corresponding to the first voltage data can be obtained, and the first differential voltage association relationship of the target battery can be constructed based on the first voltage data and the first battery capacity data.

[0065] Among them, the first voltage data can be voltage data collected during the charging or discharging process of the target battery, and the first battery capacity data can be the amount of electricity charged into the target battery during the charging process or the amount of electricity discharged by the target battery during the discharging process. The first battery capacity data and the corresponding first voltage data are data collected at the same time.

[0066] For example, the target battery can be cyclically charged, and multiple first voltage data can be collected during the cyclic charging process of the target battery. At the same time, when collecting each voltage data, the current amount of electricity charged in the target battery can be synchronously collected to obtain the first battery capacity data corresponding to the first voltage data.

[0067] Optionally, the first battery capacity data may be measured in an ampere-hour integration manner.

[0068] Among them, there are many ways to construct the first differential voltage correlation relationship of the target battery based on the first voltage data and the first battery capacity data. For example, a voltage curve can be constructed based on the first voltage data and the first battery capacity data, wherein the vertical coordinate of the voltage curve is the voltage and the horizontal coordinate of the voltage curve is the battery capacity; the voltage curve is differentially processed to obtain the first differential voltage correlation relationship of the target battery.

[0069] The voltage curve may be a voltage change curve of the target battery during charging or discharging. The ordinate of the voltage curve may be voltage, and the abscissa may be battery capacity, i.e., the amount of electricity stored or released by the target battery during charging or discharging. The first differential voltage association may be a differential voltage curve corresponding to the target battery, i.e., a first differential voltage curve.

[0070] Among them, there are many ways to construct a voltage curve based on the first voltage data and the first battery capacity data. For example, a curve can be constructed based on each first voltage data Un and the corresponding first battery capacity data Qn as data points (Qn, Un) to obtain a voltage curve, that is, the vertical coordinate of the voltage curve is the voltage V, and the horizontal coordinate is the battery capacity Q.

[0071] Furthermore, after constructing a voltage curve based on the first voltage data and the first battery capacity data, the voltage curve can be differentially processed to obtain a first differential voltage correlation relationship of the target battery. There are various ways to perform differential processing on the voltage curve to obtain the first differential voltage correlation relationship of the target battery. For example, for the voltage curve, the voltage V can be differentiated with respect to the battery capacity Q to obtain a first differential voltage curve as the first differential voltage correlation relationship. Specifically, the ordinate of the first differential voltage correlation relationship is dV / dQ, representing the derivative of the voltage V with respect to the battery capacity Q, i.e., the rate at which the voltage changes with charge, and the abscissa can be the battery capacity Q.

[0072] For example, see Figure 3a , Figure 3a is a voltage curve diagram of a battery capacity estimation method provided in an embodiment of the present application. Figure 3a In the figure above, the voltage curve of the battery can be shown, where the horizontal axis of the voltage curve is the battery capacity Q, in Ah, and the vertical axis is the voltage, in V. By performing differential processing on the voltage curve, we can get the following: Figure 3a The lower middle figure shows the first differential voltage curve, where the abscissa of the first differential voltage curve is the battery capacity Q, in Ah, and the ordinate is dV / dQ, in V / Ah.

[0073] Optionally, the differential voltage curve can distinguish between the loss of active materials and the loss of active lithium in the positive and negative electrodes of the target battery. The battery can be charged and discharged with a small current to analyze the phase change of the positive and negative active materials, thereby determining the loss of positive and negative active materials and active lithium (Li). The chemical change process inside the battery can be known by performing differential voltage analysis on the voltage curve, and information characterizing the battery degradation can be obtained based on the differential voltage curve.

[0074] In one embodiment, the first differential voltage correlation relationship may also be characterized based on a functional relationship or a neural network model.

[0075] In step 102 , a first characteristic interval corresponding to a target battery is determined based on the first differential voltage association relationship.

[0076] The first characteristic interval may be determined based on the loss of active material in the target battery.

[0077] The first characteristic interval may be a characteristic interval corresponding to the target battery, and the characteristic interval may be information characterizing the battery degradation condition of the target battery.

[0078] Since the differential voltage analysis of the battery's voltage curve is mainly based on the fact that during the insertion and extraction of lithium ions from the positive and negative electrode active materials of the lithium iron phosphate battery, the battery's negative electrode graphite will undergo a variety of different phase change stages, from the first graphite intercalation lithium compound (LiC24), the second graphite intercalation lithium compound (LiC12) to the third graphite intercalation lithium compound (LiC6). Each phase change stage corresponds to a voltage platform on the voltage curve of the positive and negative electrodes of the battery. The voltage curve of the entire battery is equal to the difference between the voltage curves of the positive and negative electrodes. Therefore, the voltage platform on the voltage curve of the entire battery can be the result of the combined action of multiple phase change stages of the positive and negative electrodes of the battery. Each voltage platform on the voltage curve of the entire battery corresponds to a specific combination of positive and negative electrode phase change stages. As the battery ages, the electrochemical state of the battery will change accordingly. As the battery ages, the active lithium inside the battery will decrease, and the lithium content per unit of negative electrode graphite will decrease, causing the voltage platform on its voltage curve to drop. This change is closely related to the battery capacity attenuation. Therefore, the battery capacity can be estimated based on the differential voltage analysis of the voltage curve, thereby comparing the current actual capacity of the battery with the rated capacity or initial capacity of the battery to obtain the battery degradation.

[0079] Among them, there can be multiple ways to determine the first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship. For example, the characteristic peak in the first differential voltage correlation relationship can be determined; the first characteristic peak and the second characteristic peak can be determined in the characteristic peak; based on the first characteristic peak and the second characteristic peak, the first characteristic interval corresponding to the target battery can be determined.

[0080] The characteristic peak may be a peak in the first differential voltage correlation relationship, the first characteristic peak and the second characteristic peak may be peaks selected from the characteristic peaks to characterize the degradation of the target battery, and the first characteristic interval may be an interval formed by the first characteristic peak and the second characteristic peak.

[0081] Among them, there are many ways to determine the first characteristic peak and the second characteristic peak in the characteristic peak. For example, the battery capacity value corresponding to the characteristic peak in the first differential voltage correlation relationship can be obtained; based on the battery capacity value, the distance between the characteristic peaks is calculated; and based on the distance, the first characteristic peak and the second characteristic peak are determined in the characteristic peak.

[0082] The battery capacity value may be the battery capacity corresponding to the characteristic peak, that is, the value of the abscissa of the characteristic peak.

[0083] There are many ways to calculate the distance between characteristic peaks based on the battery capacity value. For example, the difference between the battery capacity values ​​of any two characteristic peaks can be calculated to obtain the distance between the characteristic peaks.

[0084] After calculating the distance between the characteristic peaks based on the battery capacity value, the first characteristic peak and the second characteristic peak can be determined from the characteristic peaks based on the distance. There are various ways to determine the first characteristic peak and the second characteristic peak from the characteristic peaks based on the distance. For example, the two characteristic peaks with the largest distance, i.e., the two peaks with the largest difference in battery capacity value, can be determined as the first characteristic peak and the second characteristic peak.

[0085] Optionally, the first peak and the last peak in the first differential voltage curve may also be directly determined as the first characteristic peak and the second characteristic peak.

[0086] Among them, the first peak in the first differential voltage curve can correspond to the first phase change inside the target battery during the charging and discharging process, and the last peak in the first differential voltage curve can correspond to the last phase change inside the target battery during the charging and discharging process. In this way, the first characteristic interval composed of the first characteristic peak and the second characteristic peak can indicate the first phase change and the last phase change of the target battery, thereby characterizing the changes in the electrochemical properties inside the target battery. Since for batteries of the same type, the changes in electrochemical properties occurring in batteries at the same degradation stage are often the same, while the changes in electrochemical properties occurring in batteries at different degradation stages are often different, the different stages of battery degradation can be characterized based on the first characteristic interval composed of the first characteristic peak and the second characteristic peak, thereby realizing battery capacity estimation.

[0087] Optionally, since the degradation of battery capacity is mainly due to the loss of active lithium inside the battery, and the active lithium mainly exists in the form of graphite intercalated lithium compounds (LixC6) in the negative electrode of the battery, the positive electrode of the lithium iron phosphate battery does not have an obvious phase change process during the charge and discharge process. Therefore, the position and intensity of the peak in the differential voltage curve are mainly related to the phase change of the negative electrode graphite. Therefore, with the loss of active lithium, the peak in the differential voltage curve will also change accordingly, thereby changing the first characteristic interval corresponding to the battery. The aging of the battery is mainly characterized by the degradation of the battery capacity. The battery capacity is controlled by the growth of the solid electrolyte membrane and the consumption of active lithium by lithium dendrites. Therefore, the interval size of the first characteristic interval determined based on the first differential voltage curve is closely related to the degradation of the battery capacity. Therefore, further, the characteristic interval for effectively characterizing the changes in the electrochemical properties inside the battery can be determined by analyzing the differential voltage curve, thereby characterizing the degradation of the battery based on the characteristic interval.

[0088] For example, please refer to Figure 3a, the first differential voltage curve corresponding to the target battery can be analyzed, and the first characteristic interval (L1) can be determined in the first differential voltage curve. For example, the two characteristic peaks with the farthest distance in the first differential voltage curve can be determined as the first characteristic peak and the second characteristic peak, for example, the characteristic peak at the battery capacity of 15Ah and the characteristic peak at the battery capacity of 105Ah, so that the first characteristic interval L1 can be determined in the first differential voltage curve based on the first characteristic peak and the second characteristic peak.

[0089] In step 103 , a first target battery capacity corresponding to the target battery is determined based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery.

[0090] The battery capacity estimation model may be a model for estimating a target battery capacity of a battery based on a characteristic interval. The target battery capacity may be the battery capacity of the battery in a fully charged state, that is, the actual capacity of the battery. The first target battery capacity may be the target battery capacity of the target battery.

[0091] Optionally, the battery capacity estimation model may be a fitting curve, which may be used to fit a mapping relationship between the battery capacity difference and the target battery capacity.

[0092] Among them, there can be multiple ways to determine the first target battery capacity corresponding to the target battery based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. For example, the battery capacity estimation model may include a mapping relationship between the battery capacity difference and the target battery capacity, and the first target battery capacity difference corresponding to the first characteristic interval in the first differential voltage association relationship can be obtained; based on the first target battery capacity difference and the mapping relationship between the battery capacity difference indicated by the battery capacity estimation model and the target battery capacity, the first target battery capacity corresponding to the target battery is determined.

[0093] The first target battery capacity difference may be the difference between the battery capacity value corresponding to the first characteristic peak and the battery capacity value corresponding to the second characteristic peak in the first characteristic interval. For example, please continue to refer to Figure 3a , the first target battery capacity difference may be the difference between the battery capacity value corresponding to the first characteristic peak (15 Ah) and the battery capacity value corresponding to the second characteristic peak (105 Ah), that is, 90 Ah.

[0094] Among them, there are multiple ways to determine the first target battery capacity corresponding to the target battery based on the first target battery capacity difference and the mapping relationship between the battery capacity difference indicated by the battery capacity estimation model and the target battery capacity. For example, the target battery capacity corresponding to the first target battery capacity difference can be determined based on the mapping relationship between the battery capacity difference indicated by the battery capacity estimation model and the target battery capacity, that is, the first target battery capacity can be obtained.

[0095] In this way, based on the mapping relationship between the battery capacity difference indicated by the battery capacity estimation model and the target battery capacity, the first target battery capacity corresponding to the first target battery capacity difference is determined, which can realize a convenient and efficient evaluation of the battery aging status, avoiding the problem of over-reliance on sensor accuracy and the need to fully charge and discharge the battery through the estimation method of ampere-hour integration.

[0096] In one embodiment, a battery capacity estimation model can be constructed in a variety of ways. For example, second voltage data of multiple batteries in different degradation stages and second battery capacity data corresponding to the second voltage data can be obtained; based on the second voltage data and the second battery capacity data, a second differential voltage association relationship corresponding to the battery is constructed; based on the second differential voltage association relationship, a second characteristic interval corresponding to the battery is determined; and based on the second target battery capacity and the second characteristic interval of multiple batteries in a fully charged state, a battery capacity estimation model is constructed.

[0097] The second voltage data may be voltage data collected during the battery's charging or discharging process, the second battery capacity data may be the amount of electricity charged into the battery during charging or the amount of electricity discharged from the target battery during discharging, and the second battery capacity data and the corresponding second voltage data may be data collected at the same time. The second characteristic interval may be characteristic intervals corresponding to multiple batteries. The second differential voltage association relationship may be a differential voltage curve corresponding to the battery, i.e., a second differential voltage curve.

[0098] Optionally, in order to improve the accuracy of the battery capacity estimation model in estimating the battery capacity of the target battery, the types of the multiple batteries in different degradation stages can be the same as the target battery, so that a battery capacity estimation model that is more matched with and more similar to the electrochemical characteristics of the target battery can be fitted, thereby achieving a more accurate battery capacity estimation of the target battery based on the battery capacity estimation model.

[0099] Among them, there can be multiple ways to construct the second differential voltage association relationship corresponding to the battery based on the second voltage data and the second battery capacity data. For example, a voltage curve can be constructed based on the second voltage data and the second battery capacity data, wherein the vertical coordinate of the voltage curve is the voltage and the horizontal coordinate of the voltage curve is the battery capacity. The voltage curve is differentially processed to obtain the second differential voltage association relationship of multiple batteries.

[0100] Optionally, the method for determining the second characteristic interval corresponding to the battery based on the second differential voltage association relationship may be the same as the method for determining the first characteristic interval.

[0101] Among them, there are many ways to construct a battery capacity estimation model based on the second target battery capacity and the second characteristic interval of multiple batteries in a fully charged state. For example, the second target battery capacity of multiple batteries in a fully charged state and the second target battery capacity difference in the second characteristic interval in the second differential voltage correlation relationship can be obtained; curve fitting is performed based on the second target battery capacity difference and the second target battery capacity corresponding to multiple batteries to obtain a battery capacity estimation model.

[0102] The second target battery capacity may be a target battery capacity of the battery in a fully charged state, and the second target battery capacity difference may be a difference between battery capacity values ​​corresponding to two characteristic peaks constituting the second characteristic interval.

[0103] Among them, there are many ways to obtain a battery capacity estimation model by performing curve fitting based on the second target battery capacity difference and the second target battery capacity corresponding to multiple batteries. For example, the second target battery capacity difference and the second target battery capacity corresponding to each battery can be taken as a data point to obtain multiple data points corresponding to multiple batteries, so that curve fitting can be performed based on the multiple data points. The obtained curve expression is the battery capacity estimation model.

[0104] For example, see Figure 3b This is a schematic diagram of a model construction of a battery capacity estimation method provided in an embodiment of the present application, wherein the horizontal axis is the target battery capacity, in Ah, and the vertical axis is the battery capacity difference, in Ah. In this way, correlation analysis and curve fitting can be performed based on multiple data points corresponding to batteries in multiple different degradation stages to obtain a battery capacity estimation model. For example, it can be expressed as y=14.1238+0.70816x, wherein x can be expressed as a variable corresponding to the target battery capacity, and y can be expressed as a variable corresponding to the battery capacity difference.

[0105] In one embodiment, please refer to Figure 3c , Figure 3cIt is a specific flow chart of a battery capacity estimation method provided in an embodiment of the present application. Data collection can be performed through a battery management system (BMS) to obtain second voltage data of multiple batteries in different degradation stages during the charging process and second battery capacity data corresponding to the second voltage data. Then, a charging voltage curve corresponding to the battery can be constructed based on the second voltage data and the second battery capacity data. Therefore, differential voltage analysis can be performed on the charging voltage curve through data analysis to obtain a second differential voltage curve corresponding to the battery. Then, the degradation characterization quantity L1 can be extracted to determine the second characteristic interval corresponding to the battery based on the second differential voltage curve, so that a battery capacity estimation model can be constructed. Curve fitting is performed based on the second target battery capacity and the second characteristic interval of multiple batteries in a fully charged state to obtain a battery capacity estimation model.

[0106] Existing battery capacity estimation methods usually use the ampere-hour integration method, which has high requirements for data acquisition accuracy and high time cost. It also does not combine the internal electrochemical process of the battery for estimation, and cannot accurately and efficiently estimate the capacity of the battery. In addition, considering that the voltage platform of the charge and discharge curve of the lithium iron phosphate battery is large, it is difficult to identify the parameters that characterize the battery capacity degradation. The ampere-hour integration method cannot accurately estimate the battery capacity of the lithium iron phosphate battery. Therefore, it is very important to develop a suitable method for estimating the capacity of the lithium iron phosphate battery. To this end, the embodiment of the present application provides a battery capacity estimation method that combines the battery aging mechanism to realize battery capacity estimation. By using the change in the phase change of the negative electrode material caused by the change in the active lithium content of the lithium iron phosphate battery as the evaluation index of the battery capacity estimation, it is possible to accurately characterize the battery degradation of the lithium iron phosphate battery. Further, L1 is correlated with the battery capacity degradation to construct a battery capacity degradation model, which can achieve efficient and accurate battery capacity estimation of the battery, and solves the problem of high time cost and cumulative error of the existing estimation method using ampere-hour integration, thereby greatly improving the efficiency of battery capacity estimation.

[0107] As can be seen from the above, the embodiment of the present application obtains a first differential voltage correlation relationship corresponding to the target battery to be evaluated, the first differential voltage correlation relationship indicating the relationship between the voltage and battery capacity of the target battery; determines a first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship, the first characteristic interval being determined based on the loss of active materials in the target battery; and determines a first target battery capacity corresponding to the target battery based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. In this way, by constructing a differential voltage correlation relationship for the target battery to be evaluated, the first characteristic interval corresponding to the target battery, which characterizes the battery degradation based on the loss of active materials in the battery, is determined based on the differential voltage correlation relationship, and the first target battery capacity corresponding to the target battery is determined based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. This can achieve the goal of achieving battery capacity estimation without requiring high data acquisition accuracy and without requiring the battery to be fully charged and discharged. This further achieves accurate battery capacity estimation without requiring high data acquisition accuracy and time costs, thereby effectively improving the efficiency of battery capacity estimation.

[0108] In order to better implement the above method, an embodiment of the present invention further provides a battery capacity estimation device, which can be integrated into an electronic device, and the electronic device can be a terminal or a server.

[0109] For example, Figure 4 FIG. 2 is a schematic diagram of the structure of a battery capacity estimation device provided in an embodiment of the present application. The battery capacity estimation device may include an acquisition unit 201, a first determination unit 202, and a second determination unit 203, as follows:

[0110] An acquiring unit 201 is configured to acquire a first differential voltage correlation relationship corresponding to a target battery to be evaluated, where the first differential voltage correlation relationship indicates a relationship between a voltage and a battery capacity of the target battery;

[0111] A first determining unit 202 is configured to determine a first characteristic interval corresponding to a target battery based on the first differential voltage correlation relationship, where the first characteristic interval is determined based on a loss of active material in the target battery;

[0112] The second determining unit 203 is configured to determine a first target battery capacity corresponding to the target battery based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery.

[0113] In one embodiment, the acquiring unit 201 is configured to:

[0114] Acquire first voltage data of a target battery to be evaluated and first battery capacity data corresponding to the first voltage data;

[0115] A first differential voltage association relationship of the target battery is established based on the first voltage data and the first battery capacity data.

[0116] In one embodiment, the first differential voltage association relationship of the target battery is constructed based on the first voltage data and the first battery capacity data, specifically for:

[0117] constructing a voltage curve based on the first voltage data and the first battery capacity data, wherein the ordinate of the voltage curve is voltage and the abscissa of the voltage curve is battery capacity;

[0118] The voltage curve is differentially processed to obtain a first differential voltage correlation relationship of the target battery.

[0119] In one embodiment, the first determining unit 202 is configured to:

[0120] determining a characteristic peak in the first differential voltage correlation relationship;

[0121] Determining a first characteristic peak and a second characteristic peak among the characteristic peaks;

[0122] Based on the first characteristic peak and the second characteristic peak, a first characteristic interval corresponding to the target battery is determined.

[0123] In one embodiment, the above-mentioned determination of the first characteristic peak and the second characteristic peak in the characteristic peak is specifically used for:

[0124] Obtaining a battery capacity value corresponding to the characteristic peak in the first differential voltage correlation relationship;

[0125] Based on the battery capacity value, the distance between the characteristic peaks is calculated;

[0126] A first characteristic peak and a second characteristic peak are determined among the characteristic peaks based on the distance.

[0127] In one embodiment, the battery capacity estimation model includes a mapping relationship between the battery capacity difference and the target battery capacity. The second determining unit 203 is configured to:

[0128] Obtaining a first target battery capacity difference corresponding to the first characteristic interval in the first differential voltage association relationship;

[0129] A first target battery capacity corresponding to the target battery is determined based on the first target battery capacity difference and a mapping relationship between the battery capacity difference and the target battery capacity indicated by the battery capacity estimation model.

[0130] In one embodiment, the battery capacity estimation device further includes a model building unit configured to:

[0131] Acquire second voltage data of a plurality of batteries at different degradation stages and second battery capacity data corresponding to the second voltage data, where the type of the batteries is the same as that of the target battery;

[0132] Constructing a second differential voltage association relationship corresponding to the battery based on the second voltage data and the second battery capacity data;

[0133] determining a second characteristic interval corresponding to the battery based on the second differential voltage association relationship;

[0134] A battery capacity estimation model is constructed based on the second target battery capacities of the multiple batteries in the fully charged state and the second characteristic interval.

[0135] In one embodiment, the battery capacity estimation model is constructed based on the second target battery capacity and the second characteristic interval of the plurality of batteries in the fully charged state, and is specifically used for:

[0136] Obtaining second target battery capacities of the multiple batteries in a fully charged state and second target battery capacity differences in the second characteristic interval in the second differential voltage correlation relationship;

[0137] Curve fitting is performed based on the second target battery capacity differences corresponding to the multiple batteries and the second target battery capacities to obtain a battery capacity estimation model.

[0138] As can be seen from the above, in the embodiment of the present application, the acquisition unit 201 acquires a first differential voltage correlation corresponding to the target battery to be evaluated, the first differential voltage correlation indicating the relationship between the voltage and battery capacity of the target battery; the first determination unit 202 determines a first characteristic interval corresponding to the target battery based on the first differential voltage correlation, the first characteristic interval being determined based on the loss of active materials in the target battery; and the second determination unit 203 determines a first target battery capacity corresponding to the target battery based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. In this way, by constructing the differential voltage correlation of the target battery to be evaluated, the first characteristic interval corresponding to the target battery, which characterizes the battery degradation based on the loss of active materials in the battery, is determined based on the differential voltage correlation. Based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery, the first target battery capacity corresponding to the target battery is determined. This allows for battery capacity estimation without requiring high data acquisition accuracy and without requiring the battery to be fully charged and discharged. This further allows for accurate battery capacity estimation without requiring high data acquisition accuracy and time costs, thereby effectively improving the efficiency of battery capacity estimation.

[0139] Accordingly, an embodiment of the present application further provides an electronic device, which may be a terminal, such as a smartphone, a tablet computer, a laptop computer, a touch screen, a game console, a personal computer (PC), a personal digital assistant (PDA), or the like. Alternatively, the electronic device may be a server.

[0140] like Figure 5 As shown, Figure 5 Schematic diagram of the structure of an electronic device provided in an embodiment of the present application. The electronic device 300 includes a processor 301 having one or more processing cores, a memory 302 having one or more computer-readable storage media, and a computer program stored in the memory 302 and executable on the processor. The processor 301 is electrically connected to the memory 302. It will be understood by those skilled in the art that the electronic device structure shown in the figure does not constitute a limitation of the electronic device, and may include more or fewer components than shown, or combine certain components, or arrange the components differently.

[0141] The processor 301 is the control center of the electronic device 300. It connects the various parts of the entire electronic device 300 using various interfaces and lines. It executes various functions of the electronic device 300 and processes data by running or loading software programs and / or units stored in the memory 302 and calling data stored in the memory 302. The processor 301 can be a processor CPU, a graphics processor GPU, a network processor (NP), etc., and can implement or execute the various methods, steps, and logic blocks disclosed in the embodiments of this application.

[0142] In the embodiment of the present application, the processor 301 in the electronic device 300 loads instructions corresponding to one or more application processes into the memory 302 according to the following steps, and the processor 301 runs the application stored in the memory 302 to implement various functions, such as:

[0143] Obtain a first differential voltage correlation relationship corresponding to a target battery to be evaluated, where the first differential voltage correlation relationship indicates a relationship between the voltage and battery capacity of the target battery; determine a first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship, where the first characteristic interval is determined based on the loss of active material in the target battery; and determine a first target battery capacity corresponding to the target battery based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery.

[0144] This solution can obtain a first differential voltage correlation relationship corresponding to the target battery to be evaluated, the first differential voltage correlation relationship indicating the relationship between the voltage and battery capacity of the target battery; determine a first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship, the first characteristic interval being determined based on the loss of active materials in the target battery; and determine a first target battery capacity corresponding to the target battery based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. Thus, by constructing a differential voltage correlation relationship for the target battery to be evaluated, the first characteristic interval corresponding to the target battery, which characterizes the battery degradation based on the loss of active materials in the battery, is determined based on the differential voltage correlation relationship. Furthermore, the first target battery capacity corresponding to the target battery is determined based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. This allows for battery capacity estimation without requiring high data acquisition accuracy and without requiring the battery to be fully charged and discharged. This further allows for accurate battery capacity estimation without requiring high data acquisition accuracy and time costs, thereby effectively improving the efficiency of battery capacity estimation.

[0145] Furthermore, various functions implemented by running the application stored in the memory 302 can also be described in the aforementioned embodiments and will not be repeated here.

[0146] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0147] Optional, such as Figure 5 As shown, the electronic device 300 further includes: a touch screen 303, a radio frequency circuit 304, an audio circuit 305, an input unit 306, and a power supply 307. Among them, the processor 301 is electrically connected to the touch screen 303, the radio frequency circuit 304, the audio circuit 305, the input unit 306, and the power supply 307 respectively. Those skilled in the art will understand that Figure 5 The electronic device structure shown in the figure does not constitute a limitation to the electronic device, and may include more or fewer components than shown in the figure, or combine certain components, or arrange the components differently.

[0148] The touch display screen 303 can be used to display a graphical user interface and receive user operations generated by the graphical user interface. The touch display screen 303 may include a display panel and a touch panel. Among them, the display panel can be used to display information input by the user or information provided to the user and various graphical user interfaces of the electronic device, and these graphical user interfaces can be composed of graphics, text, icons, videos and any combination thereof. Optionally, a liquid crystal display (LCD), an organic light emitting diode (OLED) or the like can be used to configure the display panel. The touch panel can be used to collect user touch operations on or near it (such as operations performed by the user using any suitable object or accessory such as a finger, stylus or the like on or near the touch panel), and generate corresponding operation instructions, and the operation instructions execute corresponding programs. Optionally, the touch panel may include two parts: a touch detection device and a touch controller. Among them, the touch detection device detects the user's touch direction, detects the signal brought by the touch operation, and transmits the signal to the touch controller; the touch controller receives the touch information from the touch detection device, converts it into the touch point coordinates, and then sends it to the processor 301, and can receive the command sent by the processor 301 and execute it. The touch panel can cover the display panel. When the touch panel detects a touch operation on or near it, it is transmitted to the processor 301 to determine the type of touch event, and then the processor 301 provides a corresponding visual output on the display panel according to the type of touch event. In an embodiment of the present application, the touch panel and the display panel can be integrated into the touch display screen 303 to realize the input and output functions. However, in some embodiments, the touch panel and the touch panel can be used as two independent components to realize the input and output functions. That is, the touch display screen 303 can also be used as part of the input unit 306 to realize the input function.

[0149] The radio frequency circuit 304 may be used to transmit and receive radio frequency signals, so as to establish wireless communication with a network device or other electronic devices through wireless communication, and to transmit and receive signals with the network device or other electronic devices.

[0150] The audio circuit 305 can be used to provide an audio interface between the user and the electronic device through a speaker and microphone. The audio circuit 305 can convert the received audio data into an electrical signal and transmit it to the speaker, which then converts it into a sound signal for output. On the other hand, the microphone converts the collected sound signal into an electrical signal, which is received by the audio circuit 305 and converted into audio data. The audio data is then output to the processor 301 for processing, and then sent to another electronic device through the radio frequency circuit 304, or the audio data is output to the memory 302 for further processing. The audio circuit 305 may also include an earphone jack to provide communication between external headphones and the electronic device.

[0151] The input unit 306 may be configured to receive input target video and generate keyboard, mouse, joystick, optical or trackball signal input related to user settings and function control.

[0152] Power supply 307 is used to supply power to various components of electronic device 300. Optionally, power supply 307 can be logically connected to processor 301 via a power management system, thereby enabling the power management system to manage charging, discharging, and power consumption. Power supply 307 can also include one or more DC or AC power supplies, a recharging system, a power failure detection circuit, a power converter or inverter, a power status indicator, and other arbitrary components.

[0153] although Figure 5 Not shown in the figure, the electronic device 300 may further include a camera, a sensor, a wireless fidelity module, a Bluetooth module, etc., which will not be described in detail here.

[0154] In the above embodiments, the descriptions of each embodiment have their own emphasis. For parts not described in detail in a particular embodiment, please refer to the relevant descriptions of other embodiments. It should be noted that the electronic device provided in the embodiments of this application and the method for battery capacity estimation in the above embodiments are based on the same concept. The specific implementation process is detailed in the above method embodiments and will not be repeated here.

[0155] As can be seen from the above, the electronic device provided in the embodiment of the present application can obtain a first differential voltage correlation relationship corresponding to the target battery to be evaluated, the first differential voltage correlation relationship indicating the relationship between the voltage and battery capacity of the target battery; determine a first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship, the first characteristic interval being determined based on the loss of active materials in the target battery; and determine a first target battery capacity corresponding to the target battery based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. In this way, by constructing a differential voltage correlation relationship for the target battery to be evaluated, the first characteristic interval corresponding to the target battery, which characterizes the battery degradation based on the loss of active materials in the battery, is determined based on the differential voltage correlation relationship, and the first target battery capacity corresponding to the target battery is determined based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. This can achieve battery capacity estimation without requiring high data acquisition accuracy and without requiring the battery to be fully charged and discharged, further achieving accurate battery capacity estimation without requiring high data acquisition accuracy and time costs, thereby effectively improving the efficiency of battery capacity estimation.

[0156] Those skilled in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be accomplished by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0157] To this end, an embodiment of the present application provides a computer-readable storage medium, which includes a computer program. When the computer program is run on an electronic device, the computer program is used to cause the electronic device to perform any of the battery capacity estimation methods provided in the embodiments of the present application. For example, the computer program can perform the following steps of the battery capacity estimation method:

[0158] Obtain a first differential voltage correlation relationship corresponding to a target battery to be evaluated, where the first differential voltage correlation relationship indicates a relationship between the voltage and battery capacity of the target battery; determine a first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship, where the first characteristic interval is determined based on the loss of active material in the target battery; and determine a first target battery capacity corresponding to the target battery based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery.

[0159] This solution can obtain a first differential voltage correlation relationship corresponding to the target battery to be evaluated, the first differential voltage correlation relationship indicating the relationship between the voltage and battery capacity of the target battery; determine a first characteristic interval corresponding to the target battery based on the first differential voltage correlation relationship, the first characteristic interval being determined based on the loss of active materials in the target battery; and determine a first target battery capacity corresponding to the target battery based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. Thus, by constructing a differential voltage correlation relationship for the target battery to be evaluated, the first characteristic interval corresponding to the target battery, which characterizes the battery degradation based on the loss of active materials in the battery, is determined based on the differential voltage correlation relationship. Furthermore, the first target battery capacity corresponding to the target battery is determined based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery. This allows for battery capacity estimation without requiring high data acquisition accuracy and without requiring the battery to be fully charged and discharged. This further allows for accurate battery capacity estimation without requiring high data acquisition accuracy and time costs, thereby effectively improving the efficiency of battery capacity estimation.

[0160] Furthermore, for the detailed steps of the above method steps, please refer to the description in the above embodiments, which will not be repeated here.

[0161] The specific implementation of the above operations can be found in the previous embodiments and will not be repeated here.

[0162] The computer-readable storage medium may include a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0163] Since the computer program stored in the computer-readable storage medium can execute any of the battery capacity estimation methods provided in the embodiments of the present application, the beneficial effects that can be achieved by any of the battery capacity estimation methods provided in the embodiments of the present application can be achieved. Please refer to the previous embodiments for details and will not be repeated here.

[0164] According to one aspect of the present application, a computer program product is also provided, including a computer program, which is stored in a computer-readable storage medium; when a processor of an electronic device reads the computer program from the computer-readable storage medium, the processor executes the computer program, so that the electronic device executes the methods provided in various optional implementations of the above embodiments.

[0165] In the above-described embodiments of the battery capacity estimation device, computer-readable storage medium, electronic device, and computer program product, the descriptions of each embodiment have different focuses. For portions not described in detail in a particular embodiment, reference can be made to the relevant descriptions of other embodiments. Those skilled in the art will clearly understand that, for the sake of convenience and brevity, the specific working processes and beneficial effects of the above-described battery capacity estimation device, computer-readable storage medium, computer program product, electronic device, and their corresponding units can be referred to in the description of the battery capacity estimation method in the above embodiments, and the details will not be repeated here.

[0166] The above is a detailed introduction to a battery capacity estimation method, device, electronic device, computer-readable storage medium and computer program product provided in the embodiments of the present application. Specific examples are used herein to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, based on the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A battery capacity estimation method, characterized in that: include: Obtaining a first differential voltage association relationship corresponding to a target battery to be evaluated, where the first differential voltage association relationship indicates a relationship between a voltage and a battery capacity of the target battery; determining a first characteristic interval corresponding to the target battery based on the first differential voltage association relationship, where the first characteristic interval is determined based on a loss of active material in the target battery; A first target battery capacity corresponding to the target battery is determined based on the first characteristic interval and a battery capacity estimation model corresponding to the target battery.

2. The battery capacity estimation method according to claim 1, wherein: The obtaining of a first differential voltage association relationship corresponding to a target battery to be evaluated includes: Acquire first voltage data of a target battery to be evaluated and first battery capacity data corresponding to the first voltage data; A first differential voltage association relationship of the target battery is established based on the first voltage data and the first battery capacity data.

3. The battery capacity estimation method according to claim 2, wherein: The step of establishing a first differential voltage association relationship of the target battery based on the first voltage data and the first battery capacity data includes: constructing a voltage curve based on the first voltage data and the first battery capacity data, wherein the ordinate of the voltage curve is voltage and the abscissa of the voltage curve is battery capacity; Performing differential processing on the voltage curve to obtain a first differential voltage correlation relationship of the target battery.

4. The battery capacity estimation method according to claim 1, wherein: The determining the first characteristic interval corresponding to the target battery based on the first differential voltage association relationship includes: determining a characteristic peak in the first differential voltage correlation relationship; Determining a first characteristic peak and a second characteristic peak among the characteristic peaks; A first characteristic interval corresponding to the target battery is determined based on the first characteristic peak and the second characteristic peak.

5. The battery capacity estimation method according to claim 4, wherein: Determining the first characteristic peak and the second characteristic peak from the characteristic peaks includes: Obtaining a battery capacity value corresponding to the characteristic peak in the first differential voltage association relationship; Calculating the distance between the characteristic peaks based on the battery capacity value; A first characteristic peak and a second characteristic peak are determined among the characteristic peaks based on the distance.

6. The battery capacity estimation method according to claim 1, wherein: The battery capacity estimation model includes a mapping relationship between a battery capacity difference and a target battery capacity. Determining a first target battery capacity corresponding to the target battery based on the first characteristic interval and the battery capacity estimation model corresponding to the target battery includes: Obtaining a first target battery capacity difference corresponding to the first characteristic interval in the first differential voltage association relationship; A first target battery capacity corresponding to the target battery is determined based on the first target battery capacity difference and a mapping relationship between the battery capacity difference and the target battery capacity indicated by a battery capacity estimation model.

7. The battery capacity estimation method according to any one of claims 1 to 6, characterized in that: The method further comprises: Acquire second voltage data of a plurality of batteries at different degradation stages and second battery capacity data corresponding to the second voltage data, where the type of the batteries is the same as that of the target battery; constructing a second differential voltage association relationship corresponding to the battery based on the second voltage data and the second battery capacity data; determining a second characteristic interval corresponding to the battery based on the second differential voltage association relationship; A battery capacity estimation model is constructed based on the second target battery capacities of the plurality of batteries in the fully charged state and the second characteristic intervals.

8. The battery capacity estimation method according to claim 7, wherein: The constructing a battery capacity estimation model based on the second target battery capacities of the plurality of batteries in the fully charged state and the second characteristic intervals includes: Acquire a plurality of second target battery capacities of the batteries in a fully charged state, and second target battery capacity differences of the second characteristic intervals in the second differential voltage association relationship; Curve fitting is performed based on the second target battery capacity differences corresponding to the plurality of batteries and the second target battery capacity to obtain a battery capacity estimation model.

9. An electronic device, characterized in that: The battery capacity estimating method comprises a processor and a memory, wherein the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the battery capacity estimating method according to any one of claims 1 to 8.

10. A computer-readable storage medium, characterized in that The invention comprises a computer program, and when the computer program is run on an electronic device, the computer program is used to enable the electronic device to execute the steps of the battery capacity estimation method according to any one of claims 1 to 8.

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