Battery pack capacity estimation method and device and storage medium

Abstract

The invention discloses a battery pack capacity estimation method and device and a storage medium, and belongs to the technical field of lithium batteries, and the method comprises the steps: obtaining the charging data of a to-be-detected battery pack; iC curve fitting is carried out on each single battery in the battery pack to be detected according to the charging data, the accumulated charging electric quantity from a feature point to the end of charging is obtained according to the fitted IC curve, and the feature point represents the extreme value state or turning state of a related charging variable; taking the charging voltage curve of the single battery reaching the charging cut-off voltage in the battery pack as a reference to obtain the residual charging electric quantity corresponding to each single battery; obtaining the corresponding capacity of each single battery according to the accumulated charging electric quantity from the feature point to the end of charging, the residual charging electric quantity and the pre-obtained accumulated charging electric quantity before the feature point; the capacity of the battery pack is obtained according to the capacity distribution of the single batteries, the capacity of the battery pack can be estimated online with low calculation amount, and the method is suitable for energy storage batteries and power batteries.

Description

Technical Field

[0001] The present invention belongs to the technical field of lithium batteries, and in particular relates to a battery pack capacity estimation method, device and storage medium. Background Art

[0002] Energy, a major pillar of life on Earth, is also the foundation for the continuous development of human society. With the development of industry and the advancement of the times, environmental challenges and energy shortages have become increasingly prominent, leading people to pay more attention to the development and research of new energy technologies.

[0003] Energy storage technology converts energy into a storable form and releases it to supply energy when needed. It plays a crucial role in resolving the mismatch between energy supply and demand and improving the flexibility, reliability, and efficiency of energy systems. Batteries, as energy carriers, are a key component of energy storage.

[0004] Energy storage systems typically connect battery cells in series and parallel to form battery packs to increase battery power and capacity. However, due to differences between cells, they require balancing management. Therefore, it is necessary to accurately estimate the capacity of each cell in the battery pack so that effective active or passive balancing can be performed in advance, thereby improving the capacity performance of the energy storage system and extending the service life of the energy storage cabinet. In addition, by estimating the capacity of each cell in the battery pack and combining it with SOC (State of Charge) estimation, the total capacity of the battery pack can be estimated. When a battery experiences significant capacity decay, it may cause safety issues such as internal short circuits. Therefore, by analyzing the changes in battery pack capacity, it is beneficial to reduce risks during the use of the energy storage system and improve safety.

[0005] There are three main methods for estimating the capacity of individual cells in a battery pack: experimental, modeling, and data analysis. The first method directly measures the capacity of the battery pack by performing charge and discharge tests on it, but this method requires long test times and high energy consumption. The second method, such as the Chinese patent application with publication number CN110780204A, predicts the capacity of each individual cell by building an equivalent circuit model of the battery pack. The modeling method has the advantage of being able to estimate the battery pack capacity online and adapt to different operating conditions. However, the disadvantage is that the accuracy and reliability of the model need to be verified, and the complexity of the model may affect computational efficiency. The third method, such as the Chinese patent application with publication number CN116859270A, uses the charge and discharge curves of the battery pack during its service life to analyze and model the extracted features using machine learning algorithms or statistical models to estimate the capacity. The data analysis method has the advantage of being able to use a large amount of historical data for capacity estimation and can adapt to different battery types and operating conditions. However, the disadvantage is that the quality and quantity of the data significantly affect the estimation results. Summary of the Invention

[0006] The purpose of the present invention is to provide a battery pack capacity estimation method, device and storage medium, which use the single cells in the battery pack that have reached the charging cut-off voltage in advance as a reference to estimate the capacity of each single cell in the battery pack online, reducing the amount of computation required for capacity estimation. The method is applicable to both energy storage batteries and power batteries and has a wide range of applications.

[0007] To achieve the above object, the present invention is implemented by adopting the following technical solutions:

[0008] In a first aspect, the present invention provides a battery pack capacity estimation method, comprising:

[0009] Obtain charging data of the battery pack under test;

[0010] Performing IC curve fitting on each single battery in the battery pack to be tested based on the charging data, and obtaining the cumulative charged capacity from a characteristic point to the end of charging based on the fitted IC curve, wherein the characteristic point represents an extreme value state or a turning point state of a related charging variable;

[0011] The remaining charge capacity of each battery cell is obtained by using the charge voltage curve of the battery cell that has reached the charge cut-off voltage as a reference;

[0012] Obtain the capacity of each battery cell based on the cumulative charge from the characteristic point to the end of charging, the remaining charge, and the cumulative charge before the characteristic point obtained in advance, wherein the cumulative charge before the characteristic point is obtained based on the historical operating data of battery cells with the same process;

[0013] The battery pack capacity is obtained based on the capacity distribution of each single battery.

[0014] By dividing the single-cell capacity estimation into three stages: the capacity accumulation from the start of charging to the characteristic point, from the characteristic point to the end of charging, and from the end of charging to the charging cut-off voltage, and using the charging voltage curve of the single-cell that has reached the charging cut-off voltage as a reference to obtain the remaining charging capacity of the single-cell, the capacity of each single cell in the battery pack can be estimated more accurately, thereby obtaining the capacity of the entire battery pack. This comprehensively considers various key parameters and characteristics of the battery in the charging process, makes full use of historical data and real-time data, and improves the accuracy and reliability of capacity estimation.

[0015] Optionally, the charging data of the battery pack to be tested includes: state of charge, external current and external voltage of each single cell in the battery pack to be tested, wherein the external current and external voltage are data within the range where the lower limit of the state of charge is not higher than 35% and the upper limit reaches 100%.

[0016] By limiting the range of charging data to a state of charge of no more than 35% and an upper limit of 100%, data segments that are important for capacity estimation can be effectively screened out, ensuring the relevance and validity of the analyzed data, reducing data noise and interference from abnormal data, and improving the accuracy and efficiency of subsequent processing and analysis.

[0017] Optionally, performing IC curve fitting on each single battery in the battery pack to be tested according to the charging data includes:

[0018] Segment the current and voltage data between 40% and 65% of the state of charge;

[0019] A third-order Gaussian fit was used to fit the captured current and voltage data.

[0020] By fitting the IC curve and selecting data in the state of charge range of 40%-65% for third-order Gaussian fitting, the characteristics of the battery in the key charging stage can be effectively extracted, characteristic points such as the charging voltage platform demarcation point can be accurately identified, and the cumulative charging capacity from the characteristic point to the end of charging can be calculated. The high-precision characteristics of Gaussian fitting are fully utilized, the fitting effect of the battery charging voltage-curve is improved, and the accuracy of characteristic point identification and cumulative charging capacity calculation is thereby improved.

[0021] Optionally, obtaining the cumulative charging capacity from the characteristic point to the end of charging according to the fitted IC curve includes:

[0022] According to the fitted IC curve, find the peak and valley points of the charging current as characteristic points;

[0023] The ampere-hour integration is performed from the peak and valley points of the charging current to calculate the cumulative charging capacity from the characteristic point to the end of charging.

[0024] The charging voltage platform dividing point is identified as a characteristic point by fitting the IC curve, and the cumulative charging capacity is calculated by integration starting from this characteristic point. This improves the accuracy of characteristic point identification and can more accurately grasp the capacity changes of the battery in the critical charging stage.

[0025] Optionally, the obtaining of the remaining charge capacity corresponding to each single cell by using the charging voltage curve of the single cell that has reached the charging cut-off voltage in the battery pack as a reference includes:

[0026] Completing the charging voltage curves of other single cells in the battery pack according to the charging voltage curve of the single cell that has reached the charging cut-off voltage;

[0027] According to the completed charging voltage curve, the remaining charging capacity corresponding to each single battery is obtained.

[0028] The charging voltage curve of the single battery which has reached the charging cut-off voltage is set as a reference curve, and the end of the charging voltage curve of the single battery which is not fully charged is interpolated and completed, so as to calculate the residual charging capacity, solve the problem of inconsistent charging state of each single battery in the battery pack, avoid the deviation of the overall capacity estimation caused by the inconsistency of the battery pack, improve the accuracy and reliability of the capacity estimation of the whole battery pack, and ensure that the capacity estimation result can truly reflect the actual state of the battery pack.

[0029] Optionally, the completion of the charging voltage curve of the other single battery according to the charging voltage curve of the single battery which has reached the charging cut-off voltage in the battery pack comprises:

[0030] The charging voltage curve of the single battery which has reached the charging cut-off voltage is set as a reference curve, and the end of the charging voltage curve of the single battery which is not fully charged is interpolated and completed, so as to calculate the residual charging capacity, solve the problem of inconsistent charging state of each single battery in the battery pack, avoid the deviation of the overall capacity estimation caused by the inconsistency of the battery pack, improve the accuracy and reliability of the capacity estimation of the whole battery pack, and ensure that the capacity estimation result can truly reflect the actual state of the battery pack.

[0031] By adopting the interpolation completion method to complete the previous constant current charging section of the end of the charging voltage curve of the single battery which has not reached the charging cut-off voltage, the completion accuracy can be ensured, the completion process can be simplified, the calculation efficiency can be improved, and the completed charging voltage curve is more in line with the actual charging characteristics of the battery by using the charging voltage curve information of the known single battery, which provides a strong guarantee for the accurate calculation of the residual charging capacity.

[0032] Optionally, the residual charging capacity corresponding to each single battery is obtained according to the completed charging voltage curve, comprising:

[0033] The residual charging capacity of each single battery from the current state of charge to the charging cut-off voltage is calculated by integrating the ampere-hour from the point corresponding to the current state of charge according to the completed charging voltage curve.

[0034] Based on the completed charging voltage curve, the residual charging capacity is calculated by integrating from the point corresponding to the current state of charge, which can more accurately reflect the actual residual charging demand of the single battery under the current state.

[0035] Optionally, the method for obtaining the cumulative charging capacity before the feature point comprises:

[0036] The full charging cycle experiment is performed on the battery single under the same process, and the voltage and current data of the battery single in the full charging cycle process are measured and recorded;

[0037] The IC curve is fitted according to the recorded voltage and current data, and the feature point is determined on the IC curve;

[0038] Calculate the cumulative charged power from the start of charging to the characteristic point, and obtain the cumulative charged power before the characteristic point.

[0039] By conducting full-charge experiments on battery cells using the same process and recording voltage and current data in detail to fit the IC curve, we can accurately determine the characteristic points and calculate the cumulative charged capacity before the characteristic points. This makes full use of historical data to ensure the accuracy and reliability of the entire estimation method.

[0040] In a second aspect, the present invention provides a battery capacity estimation device, comprising:

[0041] Charging data acquisition module for testing: used to obtain charging data of each single battery of the battery pack under test;

[0042] A module for acquiring the cumulative charged power from the characteristic point to the end of charging is used to perform IC curve fitting on each single battery in the battery pack under test based on the charging data, and to acquire the cumulative charged power from the characteristic point to the end of charging based on the fitted IC curve, wherein the characteristic point represents the extreme value state or turning point state of the relevant charging variable;

[0043] Remaining charge capacity acquisition module: used to obtain the remaining charge capacity corresponding to each single cell in the battery pack by using the charging voltage curve of the single cell that has reached the charging cut-off voltage as a reference;

[0044] Single cell total capacity acquisition module: used to obtain the capacity of each single cell based on the cumulative charged power from the characteristic point to the end of charging, the remaining charged power, and the cumulative charged power before the characteristic point obtained in advance, wherein the cumulative charged power before the characteristic point is obtained based on the historical operating data of battery cells with the same process;

[0045] Battery pack total capacity acquisition module: used to obtain the battery pack capacity based on the capacity distribution of each single battery.

[0046] In a third aspect, the present invention provides a computer storage medium having a computer program stored thereon. When the computer program is executed by a processor, the battery pack capacity estimation method as described in any one of the first aspects is implemented.

[0047] Compared with the prior art, the application has the beneficial effects that: by obtaining the cumulative charging capacity before the feature point from the historical operation data, and obtaining the remaining charging capacity by taking the charging curve of the battery monomer that reaches the charging cutoff in advance as a reference, combining the two with the actually calculated cumulative charging capacity after the feature point, the capacity value of each monomer battery in the battery pack is finally calculated, all stages and key parameters in the battery charging process are comprehensively considered, the historical data and real-time data are fully utilized, the problem of inconsistent charging states of each monomer battery in the battery pack is solved, the accuracy and reliability of the battery pack capacity estimation are improved, accurate data support is provided for the performance evaluation, health state monitoring and subsequent management and maintenance of the battery pack, an important technical means is provided for the performance evaluation and management of the battery pack, and the application is suitable for various types of lithium ion battery packs, including energy storage batteries and power batteries and different application scenarios, and has wide applicability and good compatibility; by performing IC curve fitting and feature point analysis in a specific SOC interval, the data processing amount and fitting calculation complexity are reduced, the operation amount is reduced, and the calculation efficiency is improved. BRIEF DESCRIPTION OF DRAWINGS

[0048] Figure 1 Fig. 1 shows a flow chart of a battery pack capacity estimation method in an embodiment of the application;

[0049] Figure 2 Fig. 2 shows a flow chart of a battery pack capacity estimation method in an embodiment of the application;

[0050] Figure 3 Fig. 3 shows a battery pack charging capacity diagram based on charging stage division in an embodiment of the application;

[0051] Figure 4 Fig. 4 shows a current and monomer voltage data diagram during energy storage system charging in an embodiment of the application;

[0052] Figure 5 Fig. 5 shows an IC curve diagram fitted based on full charging cycle experimental data in an embodiment of the application;

[0053] Figure 6 Fig. 6 shows six monomer local IC curve diagrams based on energy storage data in an embodiment of the application, wherein Fig. (a) is a local IC curve diagram of monomer one, Fig. (b) is a local IC curve diagram of monomer two, Fig. (c) is a local IC curve diagram of monomer three, Fig. (d) is a local IC curve diagram of monomer four, Fig. (e) is a local IC curve diagram of monomer five, and Fig. (f) is a local IC curve diagram of monomer six;

[0054] Figure 7 Fig. 7 shows a cumulative charging capacity diagram at the feature point based on IC curve estimation in an embodiment of the application;

[0055] Figure 8 FIG2 is a schematic diagram of an operation based on charging voltage curve completion in one embodiment of the present invention, wherein FIG3 is a schematic diagram of the entire charging voltage curve after completion, and FIG4 is a schematic diagram of an enlarged portion of the completed curve; FIG5 is a schematic diagram of an operation based on charging voltage curve completion in one embodiment of the present invention, wherein FIG6 is a schematic diagram of the entire charging voltage curve after completion, and FIG7 is a schematic diagram of an enlarged portion of the completed curve;

[0056] Figure 9 FIG2 is a schematic diagram showing the estimation result of the remaining charge capacity of each cell based on the completion of the charging voltage curve in one embodiment of the present invention;

[0057] Figure 10 FIG2 is a schematic diagram showing the estimated capacity of each single battery cell based on an energy storage system in an embodiment of the present invention. DETAILED DESCRIPTION

[0058] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solutions of the present invention and are not intended to limit the scope of protection of the present invention.

[0059] Example 1

[0060] like Figure 1 As shown, this embodiment provides a battery pack capacity estimation method, including:

[0061] Obtain charging data of each single cell of the battery pack to be tested;

[0062] Performing IC curve fitting on each single battery in the battery pack to be tested based on the charging data, and obtaining the cumulative charged capacity from a characteristic point to the end of charging based on the fitted IC curve, wherein the characteristic point represents an extreme value state or a turning point state of a related charging variable;

[0063] The remaining charge capacity of each battery cell is obtained by using the charge voltage curve of the battery cell that has reached the charge cut-off voltage as a reference;

[0064] Obtain the capacity of each battery cell based on the cumulative charge from the characteristic point to the end of charging, the remaining charge, and the cumulative charge before the characteristic point obtained in advance, wherein the cumulative charge before the characteristic point is obtained based on the historical operating data of battery cells with the same process;

[0065] The battery pack capacity is obtained based on the capacity distribution of each single battery.

[0066] By utilizing the cumulative charged capacity and remaining charge capacity before and after the characteristic point, a reasonable estimate of the charge capacity of the single cell at each stage is made, achieving accurate estimation of the capacity of each single cell in the battery pack. At the same time, the amount of calculation is reduced and the calculation efficiency is improved. The capacity can be estimated in real time or near real time during the operation of the battery pack, reducing the dependence on long-term offline testing, facilitating the timely discovery of capacity attenuation and inconsistency problems of single cells in the battery pack, and improving the accuracy of the capacity estimation of each single cell, thereby providing reliable data support for performance evaluation, balancing management and health status monitoring of the battery pack.

[0067] Example 2

[0068] Based on Example 1, this example also makes the following design.

[0069] like Figure 2 As shown, the battery pack capacity estimation method is specifically divided into the following steps:

[0070] First, obtain historical operating data for battery packs from completed energy storage or power battery projects. This data should include both normal battery operation and battery failure data, collected by the BMS (Battery Management System). Features in the data should include, but are not limited to, the charge and discharge voltages of each battery cell in the battery pack, system current, temperature, SOC (State of Charge), and SOH (State of Health).

[0071] S1: Based on multiple full charge and discharge cycle experiments with 100% DOD (Depth of Discharge), voltage and current tests are performed on battery cells using the same process under constant current charging. The voltage and current data during the process are measured and recorded, and the IC curve is fitted. By analyzing the cumulative charged capacity before the characteristic point, it is found that the cumulative charged capacity before the characteristic point is basically stable. Based on the data obtained from multiple full charge and discharge cycle experiments, the cumulative charged capacity before a characteristic point is calculated. Among them, the characteristic point on the IC curve is the peak and valley point, which corresponds to the platform dividing point of the charging voltage curve.

[0072] S11: For IC curve fitting, select third-order Gaussian fitting, which can effectively filter voltage noise and reflect the characteristics of the charge capacity-voltage curve. The specific implementation steps are as follows:

[0073] Third-order Gaussian fitting refers to modeling the data using a linear combination of three Gaussian functions. The expression of each Gaussian function is:

[0074]

[0075] Among them, x represents the input IC data, is the amplitude of the kth peak, is the center of the k-th peak, is the standard deviation of the kth peak. The IC curve has three distinct peaks, so a third-order Gaussian fit is a good way to fit the IC curve. In Matlab, call the curve fitting toolbox cftool, input the voltage and capacity information, and fit the nine parameters of the third-order Gaussian fit function.

[0076] Since the capacity decay of lithium iron phosphate battery is basically reflected after the characteristic point, the capacity change of the battery is analyzed through the characteristic point. Figure 5 As shown in the figure, an IC curve diagram of a typical battery is drawn based on full charge cycle experimental data.

[0077] S2: Extract the current and voltage data of the charging stage from the energy storage cabinet or power battery operation data, including SOC, external current and external voltage of each battery cell, and require the charging range to be: the starting SOC of charging is less than 35% and continues until it is fully charged. Figure 4 As shown, the voltage and system current data of each cell of 384 battery cells in a battery pack are given.

[0078] S3: In order to improve the fitting effect, the charging data is intercepted, and the current and voltage data in the SOC range of 40%-65% are selected. The intercepted current and voltage are fitted to the battery voltage-capacity using the third-order Gaussian fitting method in step S11, and the IC curve is drawn. The IC curves of the first six cells in series in the battery pack are as follows: Figure 6 As shown, the minimum point is the location of the characteristic point. The cumulative charged power before the characteristic point based on the IC curve is calculated. The cumulative charged power before the characteristic point estimated based on the IC curve is as follows: Figure 7 shown.

[0079] S31: The cumulative charged capacity is calculated using the ampere-hour integration method. The ampere-hour integration method (Ah integration) is the core method for calculating the cumulative charge / discharge capacity of the battery. Its essence is to achieve power statistics by integrating the current time. The calculation formula is as follows:

[0080]

[0081] Where I is the current data, and Δt represents the current time.

[0082] S4: Analyze the battery pack voltage and find the battery cells that have reached the cut-off voltage in the battery pack. When a cell in the battery pack reaches the charge cut-off voltage, select the charge voltage curve of the battery as the reference curve and complete the charge voltage curves of other cells that have not reached the charge cut-off voltage. Figure 8 As shown, for the current situation of constant voltage charging at the charging end, the charging voltage curve is completed in the previous constant current charging section to estimate the remaining charging capacity. Figure 9 The figure shows the remaining charge capacity estimation result based on the completion of the charging voltage curve.

[0083] S41: Charging voltage curve completion Select the last constant current charging section and perform the completion operation. Compare the voltage of the partially charged single battery at the end of charging with the voltage of the reference single battery. After finding the corresponding position, perform a translation operation. If alignment is not possible, interpolation processing is required. It is assumed that the remaining charging voltage curve of the partially charged single battery is consistent with the reference charging voltage curve. The interpolation formula is:

[0084]

[0085] Among them, Cap is the calculated capacity value of the corresponding interpolation point, U end is the charging terminal voltage of the battery to be estimated, U2 is the reference voltage greater than U end The first value of Cap2 is the corresponding cumulative charge, and U1 is the reference voltage less than U end Cap1 is the first value of the battery, Cap0 is the corresponding cumulative charge capacity at the end of charging.

[0086] S5: If Figure 3 As shown, the capacity of each battery cell is calculated by combining the characteristic points of the IC curve analysis with the remaining charge capacity estimated based on the charging voltage curve complement.

[0087] S51: Based on the IC curve, find the characteristic point and calculate the cumulative charged power from the characteristic point to the end of charging.

[0088] S52: Based on S3, the charging voltage curve is completed to calculate the corresponding remaining charge capacity. The cumulative charge capacity of each cell from the characteristic point to the end of charging and the remaining charge capacity are accumulated to obtain the cumulative charge capacity of each battery cell after the characteristic point.

[0089] S53: Add the cumulative charged electricity of each battery cell after the characteristic point obtained in step S52 and the cumulative charged electricity before the characteristic point obtained in step S1 to obtain the capacity value of each battery cell in the battery pack.

[0090] The above steps are performed when the system SOC completes a full charge and the initial charging SOC is less than 40%.

[0091] S6: As Figure 10 As shown, the capacity of each single battery based on an energy storage system estimate is accumulated to obtain the battery pack capacity.

[0092] This embodiment estimates the capacity of each battery cell by completing the IC curve and the charging voltage curve based on the similarity principle of the charging voltage curve. This simple model can estimate the capacity of each battery cell online. It is primarily used for lithium-ion battery pack SOH inconsistency analysis, providing data for performance analysis of lithium-ion battery packs and ensuring the performance and normal operation of the battery pack. Furthermore, considering that the characteristic point is located near 50%, there is no need to perform a Gaussian fit on the voltage-to-accumulated capacity over the entire charging cycle. Instead, the fit only needs to be performed within the system SOC range of 40%-65%. This significantly reduces the computational load, eliminates noise generated during the IC curve fitting process, and improves the accuracy of the characteristic point location. Furthermore, at the end of the current charging cycle, this embodiment estimates the remaining charge capacity based on the completed charging voltage curve. Considering that the last charging cycle is constant power charging, the completion operation is performed at the last constant current charging cycle. The estimated capacity of each battery cell in this cycle can be used for balancing during subsequent discharge and charging cycles.

[0093] Example 3

[0094] This embodiment provides a battery capacity estimation device, including:

[0095] Charging data acquisition module for testing: used to obtain charging data of each single battery of the battery pack under test;

[0096] A module for acquiring the cumulative charged power from the characteristic point to the end of charging is used to perform IC curve fitting on each single battery in the battery pack under test based on the charging data, and to acquire the cumulative charged power from the characteristic point to the end of charging based on the fitted IC curve, wherein the characteristic point represents the extreme value state or turning point state of the relevant charging variable;

[0097] Remaining charge capacity acquisition module: used to obtain the remaining charge capacity corresponding to each single cell in the battery pack by using the charging voltage curve of the single cell that has reached the charging cut-off voltage as a reference;

[0098] Single cell total capacity acquisition module: used to obtain the capacity of each single cell based on the cumulative charged power from the characteristic point to the end of charging, the remaining charged power, and the cumulative charged power before the characteristic point obtained in advance, wherein the cumulative charged power before the characteristic point is obtained based on the historical operating data of battery cells with the same process;

[0099] Battery pack total capacity acquisition module: used to obtain the battery pack capacity based on the capacity distribution of each single battery.

[0100] Example 4

[0101] This embodiment provides a computer storage medium having a computer program stored thereon. When the computer program is executed by a processor, the battery pack capacity estimation method described in any step of Embodiment 2 is implemented.

[0102] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware. Furthermore, the present application may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to magnetic disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0103] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 a process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0104] These computer program instructions may also be stored in a computer readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0105] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operational steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing the instructions executed on the computer or other programmable device for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 A step that specifies a function in one or more boxes.

[0106] The embodiments of the present invention are described above in conjunction with the accompanying drawings, but the present invention is not limited to the above-mentioned specific implementation methods. The above-mentioned specific implementation methods are merely illustrative and not restrictive. Under the guidance of the present invention, ordinary technicians in this field can also make many forms without departing from the scope of protection of the purpose of the present invention and the claims, which are all protected by the present invention.

Claims

1. A battery pack capacity estimation method, characterized in that: include: Obtain charging data of the battery pack under test; Performing IC curve fitting on each single battery in the battery pack to be tested based on the charging data, and obtaining the cumulative charged capacity from a characteristic point to the end of charging based on the fitted IC curve, wherein the characteristic point represents an extreme value state or a turning point state of a related charging variable; The remaining charge capacity of each battery cell is obtained by using the charging voltage curve of the battery cell that has reached the charging cut-off voltage as a reference; Obtain the capacity of each battery cell based on the cumulative charge from the characteristic point to the end of charging, the remaining charge, and the cumulative charge before the characteristic point obtained in advance, wherein the cumulative charge before the characteristic point is obtained based on the historical operating data of battery cells with the same process; The battery pack capacity is obtained based on the capacity distribution of each single battery.

2. The battery capacity estimation method according to claim 1, wherein: The charging data of the battery pack to be tested includes the state of charge, the external current, and the external voltage of each single cell in the battery pack to be tested, wherein the external current and the external voltage are data within the range of the state of charge lower limit not higher than 35% and the upper limit reaching 100%.

3. The battery capacity estimation method according to claim 1, wherein: The performing IC curve fitting on each single battery in the battery pack to be tested according to the charging data includes: Segment the current and voltage data between 40% and 65% of the state of charge; A third-order Gaussian fit was used to fit the captured current and voltage data.

4. The battery capacity estimation method according to claim 1, wherein: The step of obtaining the cumulative charging capacity from the characteristic point to the end of charging according to the fitted IC curve includes: According to the fitted IC curve, find the peak and valley points of the charging current as characteristic points; The ampere-hour integration is performed from the peak and valley points of the charging current to calculate the cumulative charging capacity from the characteristic point to the end of charging.

5. The battery capacity estimation method according to claim 1, wherein: The method of using the charging voltage curve of a single battery that has reached the charging cut-off voltage in the battery pack as a reference to obtain the remaining charging capacity corresponding to each single battery includes: Completing the charging voltage curves of other single cells in the battery pack according to the charging voltage curve of the single cell that has reached the charging cut-off voltage; According to the completed charging voltage curve, the remaining charging capacity corresponding to each single battery is obtained.

6. The battery capacity estimation method according to claim 5, characterized in that: The method of completing the charging voltage curves of other single cells in the battery pack according to the charging voltage curve of the single cell that has reached the charging cut-off voltage includes: The charging voltage curve of the single battery that has reached the charging cut-off voltage is used as a reference curve, and the charging voltage curves of other single batteries that have not reached the charging cut-off voltage are interpolated and completed at the front constant current charging section of the charging end.

7. The battery capacity estimation method according to claim 5, characterized in that: The method of obtaining the remaining charge capacity of each single battery according to the completed charging voltage curve includes: Based on the completed charging voltage curve, ampere-hour integration is performed from the point corresponding to the current state of charge to calculate the remaining charging capacity required for each single battery from the current state of charge to the charging cut-off voltage.

8. The battery capacity estimation method according to claim 1, wherein: The method for obtaining the cumulative amount of electricity charged before the characteristic point includes: Conduct full charge cycle experiments on battery cells produced under the same process, and measure and record the voltage and current data of the battery cells during the full charge cycle. Fit the IC curve based on the recorded voltage and current data, and determine the characteristic points on the IC curve; Calculate the cumulative charged power from the start of charging to the characteristic point, and obtain the cumulative charged power before the characteristic point.

9. A battery capacity estimation device, characterized in that: include: Charging data acquisition module for testing: used to obtain charging data of each single battery of the battery pack under test; A module for acquiring the cumulative charged power from the characteristic point to the end of charging is used to perform IC curve fitting on each single battery in the battery pack under test based on the charging data, and to acquire the cumulative charged power from the characteristic point to the end of charging based on the fitted IC curve, wherein the characteristic point represents the extreme value state or turning point state of the relevant charging variable; Remaining charge capacity acquisition module: used to obtain the remaining charge capacity corresponding to each single cell in the battery pack by using the charging voltage curve of the single cell that has reached the charging cut-off voltage as a reference; Single cell total capacity acquisition module: used to obtain the capacity of each single cell based on the cumulative charged power from the characteristic point to the end of charging, the remaining charged power, and the cumulative charged power before the characteristic point obtained in advance, wherein the cumulative charged power before the characteristic point is obtained based on the historical operating data of battery cells with the same process; Battery pack total capacity acquisition module: used to obtain the battery pack capacity based on the capacity distribution of each single battery.

10. A computer storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the battery capacity estimation method according to any one of claims 1 to 8 is implemented.

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