Method and device for estimating battery cell capacity

Abstract

The present application discloses a method and device for estimating the capacity of a battery cell, in which an energy storage system can estimate the low-end capacity, platform capacity, and terminal compensation capacity of a battery cell based on the soc_ocv curve and the charging cut-off voltage of the battery cell, and determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity, and terminal compensation capacity. For the battery cells in an incompletely charged electrical cabinet, the energy storage system can determine the capacity required to fully charge the battery cell after the charging of the battery cell is cut off, and adopt a three-stage capacity estimation method (low-end capacity, platform capacity, and terminal compensation capacity of the battery cell) to realize the capacity estimation of the battery cells in the incompletely charged electrical cabinet, thereby improving the accuracy of the capacity estimation of the battery cells in the incompletely charged electrical cabinet.

Description

Technical Field

[0001] The present application relates to the field of batteries, and in particular to a method and device for estimating the capacity of a battery cell. Background Art

[0002] Energy storage systems are equipped with multiple electrical cabinets, each containing multiple battery cells. These cells can store excess power, but they age over time, reducing their capacity and overall health. To ensure the safe and stable operation of energy storage systems, it's necessary to estimate the capacity of the battery cells.

[0003] However, it is difficult to estimate the capacity of battery cells in an incompletely charged electrical cabinet in the related art. Summary of the Invention

[0004] In view of the above problems, the present application provides a method and device for estimating the capacity of a battery cell, which can solve the problem in the related art that it is difficult to estimate the capacity of a battery cell in an electric cabinet that is not fully charged.

[0005] In a first aspect, a method for estimating battery cell capacity is provided, comprising:

[0006] Obtain the charging information and basic parameter information of the battery cell, the charging information includes the charging cut-off voltage of the battery cell, and the basic parameter information includes the state of charge (SOC)-open circuit voltage (OCV) curve of the battery cell;

[0007] Estimate the low-end capacity, platform capacity and terminal compensation capacity of the battery cell based on the soc_ocv curve and the charge cut-off voltage;

[0008] The estimated capacity of the battery cell is determined based on the low-end area capacity, platform area capacity and terminal area compensation capacity.

[0009] The embodiment of the present disclosure provides a method for estimating the capacity of a battery cell, in which the energy storage system can estimate the low-end capacity, platform capacity and terminal compensation capacity of the battery cell based on the soc_ocv curve and the charging cut-off voltage, and determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity and terminal compensation capacity. This achieves the capacity estimation of the battery cells in the partially charged electrical cabinet, and improves the accuracy of the capacity estimation of the battery cells in the partially charged electrical cabinet. In addition, this estimation method is simple and does not require complex decoupling calculations and more computing power resources. This method solves the problem that it is difficult to estimate the capacity of the battery cells in the partially charged electrical cabinet, and the problem that it is difficult to evaluate the consistency and difference of the capacity of different battery cells in the partially charged electrical cabinet. It also solves the problem that it is difficult to estimate the capacity of the partially charged electrical cabinet, and the problem that it is difficult to evaluate the consistency and difference of the capacity between different electrical cabinets.

[0010] Optionally, estimate the low-end capacity, platform capacity, and terminal compensation capacity of the battery cell based on the soc_ocv curve and the charge cut-off voltage, including:

[0011] Determine the low-end estimated voltage according to the soc_ocv curve, and determine the charging current from the low-end estimated voltage to the charging cut-off voltage according to the charging information;

[0012] The low-end capacity of the battery cell is estimated based on the low-end estimated voltage, the platform capacity of the battery cell is estimated based on the charging current, and the terminal compensation capacity of the battery cell is estimated based on the charging cut-off voltage.

[0013] Optionally, the terminal region compensation capacity of the cell is estimated based on the charge cut-off voltage, including:

[0014] Obtain the relationship model between the SOC and voltage of the battery cell;

[0015] Input the charge cut-off voltage and the full charge cut-off voltage of the battery cell into the relationship model to obtain the estimated SOC value of the battery cell;

[0016] The terminal area compensation capacity is determined based on the SOC estimate and the nominal capacity of the battery cell.

[0017] By determining the SOC estimation value of the battery cell through the relational model, the efficiency and accuracy of determining the SOC estimation value of the battery cell are improved, thereby improving the efficiency and accuracy of determining the compensation capacity of the terminal area.

[0018] Optionally, the relationship model is fitted according to the following steps:

[0019] Obtaining an estimated charging start voltage and an estimated charging end voltage of a target battery cell among multiple battery cells;

[0020] Determine the estimated current of the target cell from the estimated charging start voltage to the estimated charging end voltage;

[0021] The capacity of the target battery cell is estimated by using the ampere-hour integration method to estimate the estimated current and obtain the charging capacity from the estimated charging start voltage to the estimated charging end voltage.

[0022] The compensation capacity of the target battery cell is determined based on the estimated charging start voltage, the estimated charging end voltage, the charging capacity and the full charging cut-off voltage of the target battery cell, and the relationship between the compensation capacity and the estimated charging end voltage and the full charging cut-off voltage of the target battery cell is fitted to obtain a relationship model, thereby realizing the determination of the relationship model.

[0023] Optionally, determining the compensation capacity of the target battery cell according to the estimated charge start voltage, the estimated charge end voltage, the charge capacity, and the full charge end voltage of the target battery cell includes:

[0024] The unit charging capacity of the target battery cell is determined according to the estimated charging start voltage, the estimated charging end voltage and the charging capacity; the compensation capacity is determined according to the estimated charging end voltage, the full charging end voltage of the target battery cell and the unit charging capacity, thereby determining the compensation capacity of the target battery cell.

[0025] Optionally, the estimated charge cut-off voltage of the target battery cell is a maximum value of charge cut-off voltages of multiple battery cells.

[0026] Optionally, determine the low-end estimated voltage based on the soc_ocv curve, including:

[0027] Determine the SOC threshold of the low-end area of the battery cell;

[0028] The low-end estimated voltage is determined based on the low-end region SOC threshold and the soc_ocv curve. Determining the low-end estimated voltage based on the soc_ocv curve improves the efficiency of determining the low-end estimated voltage and the accuracy of the determined low-end estimated voltage.

[0029] Optionally, the low-end capacity of the cell is estimated based on the low-end estimated voltage, including:

[0030] Get the pre-configured cell ocv_capacity (capacity, cap) table;

[0031] Based on the estimated low-end voltage, the low-end capacity is obtained by querying the cell ocv_cap table.

[0032] The low-end area capacity is determined by querying the battery cell ocv_cap table, thereby improving the efficiency of determining the low-end area capacity and the accuracy of the determined low-end area capacity.

[0033] Optionally, estimate the cell's plateau capacity based on the charging current, including:

[0034] The ampere-hour integration method is used to estimate the capacity of the charging current, and the platform capacity of the battery cell from the low-end estimated voltage to the charging cut-off voltage is obtained, thereby determining the platform capacity of the battery cell.

[0035] Optionally, after determining the estimated capacity of the battery cell, the method further includes:

[0036] The state of health (SOH) value of a cell is determined based on its estimated capacity and nominal capacity, thereby determining the SOH value of cells in a partially charged cabinet. The energy storage system can then determine the SOH value of each cabinet based on the SOH values of multiple cells within that cabinet. This allows for accurate assessment of the consistency and variability of SOH values across cells within each cabinet, as well as across cabinets.

[0037] In a second aspect, a method for constructing a model for estimating cell capacity is provided, comprising:

[0038] Obtaining an estimated charging start voltage and an estimated charging end voltage of a target battery cell among multiple battery cells;

[0039] Determine the estimated current of the target cell from the estimated charging start voltage to the estimated charging end voltage;

[0040] The capacity of the target battery cell is estimated by using the ampere-hour integration method to estimate the estimated current and obtain the charging capacity from the estimated charging start voltage to the estimated charging end voltage.

[0041] The compensation capacity of the target battery cell is determined based on the estimated charging start voltage, the estimated charging end voltage, the charging capacity and the full charge cut-off voltage of the target battery cell, and the relationship between the compensation capacity and the estimated charging end voltage and the full charge cut-off voltage of the target battery cell is fitted to obtain a relationship model between the SOC and voltage of the battery cell, wherein the relationship model is used to determine the SOC estimation value of the battery cell, so as to determine the terminal area compensation capacity of the battery cell based on the SOC estimation value.

[0042] The energy storage system can determine the estimated SOC value of the battery cell based on this relationship model, and then determine the compensation capacity of the battery cell's end zone based on the estimated SOC value. For cells in a partially charged cabinet, the energy storage system can determine the compensation capacity required to fully charge the cell. Using a three-stage capacity estimation method (low-end zone capacity, platform zone capacity, and end zone compensation capacity), the system can estimate the capacity of the battery cells in the partially charged cabinet, improving the accuracy of the capacity estimation.

[0043] In a third aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a computer device, the computer device implements the battery cell capacity estimation method described in the above aspect.

[0044] In a fourth aspect, a computer-readable storage medium is provided, on which a computer program is stored. When the computer program is executed by a computer device, the computer device implements the model construction method for estimating the battery cell capacity described in the above aspect.

[0045] In a fifth aspect, an energy storage system is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the energy storage system implements the battery cell capacity estimation method described in the above aspects.

[0046] In a sixth aspect, a model building device is provided, comprising a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the model building device implements the model building method for estimating the cell capacity described in the above aspect.

[0047] In a seventh aspect, a battery cell capacity estimation device is provided, comprising:

[0048] A first acquisition module is used to acquire charging information and basic parameter information of the battery cell, the charging information includes the charging cut-off voltage of the battery cell, and the basic parameter information includes the soc_ocv curve of the battery cell;

[0049] The estimation module is used to estimate the low-end capacity, platform capacity and terminal compensation capacity of the battery cell according to the soc_ocv curve and the charging cut-off voltage, and determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity and terminal compensation capacity.

[0050] In an eighth aspect, a model building device for estimating cell capacity is provided, comprising:

[0051] A second acquisition module is used to obtain the estimated charging start voltage and the estimated charging end voltage of the target battery cell among the multiple battery cells;

[0052] A first determining module is used to determine the estimated current of the target battery cell from the estimated charging start voltage to the estimated charging end voltage;

[0053] The third acquisition module is used to estimate the capacity of the estimated current using the ampere-hour integration method to obtain the charging capacity of the target battery cell from the estimated charging start voltage to the estimated charging end voltage;

[0054] A fitting module is used to determine the compensation capacity of the target battery cell based on the estimated charging start voltage, the estimated charging end voltage, the charging capacity and the full charge cut-off voltage of the target battery cell, and fit the relationship between the compensation capacity and the estimated charging end voltage and the full charge cut-off voltage of the target battery cell to obtain a relationship model between the SOC and voltage of the battery cell, wherein the relationship model is used to determine the SOC estimation value of the battery cell, so as to determine the terminal area compensation capacity of the battery cell based on the SOC estimation value.

[0055] Additional aspects and advantages of the present disclosure will be given in part in the description below and in part will be obvious from the description below, or will be learned through practice of the present disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] Figure 1 is a flow chart of a battery cell capacity estimation method provided by an embodiment of the present disclosure;

[0057] Figure 2 is a flow chart of another battery cell capacity estimation method provided by an embodiment of the present disclosure;

[0058] Figure 3 is a flow chart of a relationship model fitting process provided by an embodiment of the present disclosure;

[0059] Figure 4 is a schematic diagram of a display interface of an energy storage system provided by an embodiment of the present disclosure;

[0060] Figure 5 is a structural diagram of an energy storage system provided by an embodiment of the present disclosure;

[0061] Figure 6 is a structural diagram of a model building device provided by an embodiment of the present disclosure;

[0062] Figure 7 is a block diagram of a battery cell capacity estimation device provided by an embodiment of the present disclosure;

[0063] Figure 8 is a block diagram of another battery cell capacity estimation device provided by an embodiment of the present disclosure;

[0064] Figure 9 This is a block diagram of a model building device for estimating battery cell capacity provided by an embodiment of the present disclosure. DETAILED DESCRIPTION

[0065] The following describes in detail embodiments of the present disclosure, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present disclosure, and should not be construed as limiting the present disclosure.

[0066] Energy storage systems typically have multiple electrical cabinets, each containing multiple battery cells. Each battery cell can store excess power, but over time, it ages, reducing its capacity and ultimately its health. To ensure the safe and stable operation of the energy storage system, it's necessary to estimate the battery cell capacity.

[0067] Related technologies typically use the DEKF algorithm to update model parameters in real time and estimate cell capacity online for cells in partially charged cabinets by monitoring constant current charging data between two fixed voltage characteristic points. However, this approach requires a complete charging curve at different aging stages. Since energy storage systems stop charging after a cabinet is fully charged, and other cabinets are not fully charged, this method cannot estimate the capacity of cells in partially charged cabinets. Consequently, it is difficult to assess the consistency and variability of the capacities of multiple cells in a partially charged cabinet, as well as the consistency and variability of the capacities of different cabinets.

[0068] Furthermore, this solution struggles to assess the SOH values of cells in partially charged cabinets, and the SOH values of partially charged cabinets. Consequently, it struggles to assess the consistency and variability of SOH values across cells within a cabinet, and across cabinets. Furthermore, this solution's calculations are complex and require significant computing power. Since energy storage systems often contain tens of thousands of cells, this solution is unsuitable for real-time online capacity estimation.

[0069] The present disclosure provides a method for estimating the capacity of a battery cell, in which an energy storage system can estimate the low-end capacity, platform capacity, and terminal compensation capacity of the battery cell based on the soc-ocv curve and the charge cut-off voltage of the battery cell, and determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity, and terminal compensation capacity. The low-end capacity can also be referred to as the low-end capacity, and the terminal compensation capacity can also be referred to as the terminal compensation capacity. The terminal compensation capacity refers to the capacity required to fully charge the battery cell after the charging of the battery cell is cut off.

[0070] For the battery cells in the electric cabinet that is not fully charged, the energy storage system provided by the embodiment of the present disclosure can determine the capacity required to compensate for fully charging the battery cell after the charging of the battery cell is terminated, and adopt a three-stage capacity estimation method (i.e., the low-end area capacity, platform area capacity and terminal area compensation capacity of the battery cell) to estimate the battery cell capacity, thereby realizing the capacity estimation of the battery cells in the electric cabinet that is not fully charged, and improving the accuracy of the capacity estimation of the battery cells in the electric cabinet that is not fully charged. This estimation method is simple and does not require complex decoupling calculations and more computing power resources, so the energy storage system can estimate the capacity of the battery cells online in real time. In addition, this method solves the problem that it is difficult to estimate the capacity of the battery cells in the electric cabinet that is not fully charged, and the problem that it is difficult to evaluate the consistency and difference of the capacity of different battery cells in the electric cabinet that is not fully charged. At the same time, it solves the problem that it is difficult to estimate the capacity of the electric cabinet that is not fully charged, and the problem that it is difficult to evaluate the consistency and difference of the capacity between different electric cabinets.

[0071] Figure 1 This is a flow chart of a cell capacity estimation method provided by an embodiment of the present disclosure. This method can be applied to energy storage systems, such as Figure 1 As shown, the method includes:

[0072] Step 101: Obtain charging information and basic parameter information of the battery cell.

[0073] The energy storage system can obtain charging information and basic parameter information of the battery cell, wherein the charging information may include the charging cut-off voltage of the battery cell, and the basic parameter information may include the soc_ocv curve of the battery cell.

[0074] Step 102: Estimate the low-end capacity, platform capacity, and terminal compensation capacity of the battery cell according to the soc_ocv curve and the charge cut-off voltage.

[0075] After obtaining the soc_ocv curve and charging cut-off voltage of the battery cell, the energy storage system can estimate the low-end capacity, platform capacity and terminal compensation capacity of the battery cell based on the soc_ocv curve and charging cut-off voltage.

[0076] Step 103: Determine the estimated capacity of the battery cell according to the low-end region capacity, the platform region capacity, and the terminal region compensation capacity.

[0077] After the energy storage system estimates the low-end capacity, platform capacity and terminal compensation capacity of the battery cell according to the soc_ocv curve and the charging cut-off voltage, it can determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity and terminal compensation capacity.

[0078] In summary, the embodiments of the present disclosure provide a method for estimating the capacity of a battery cell, in which the energy storage system can estimate the low-end capacity, platform capacity, and terminal compensation capacity of the battery cell based on the soc_ocv curve and the charging cut-off voltage, and determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity, and terminal compensation capacity. For the battery cells in the cabinet that are not fully charged, the energy storage system can determine the capacity required to fully charge the battery cell after the charging of the battery cell is cut off, and adopts a three-stage capacity estimation method (low-end capacity, platform capacity, and terminal compensation capacity of the battery cell) to realize the capacity estimation of the battery cell, thereby improving the accuracy of the capacity estimation of the battery cells in the cabinet that are not fully charged.

[0079] This simple estimation method eliminates the need for complex decoupling calculations and extensive computing resources, enabling the energy storage system to estimate cell capacity in real time online. Furthermore, it addresses the difficulty in estimating the capacity of cells in partially charged cabinets, as well as the difficulty in assessing the consistency and differences in the capacities of different cells within a partially charged cabinet. It also addresses the difficulty in estimating the capacity of partially charged cabinets, as well as the difficulty in assessing the consistency and differences in the capacities of different cabinets.

[0080] Figure 2 is a flow chart of another cell capacity estimation method provided by an embodiment of the present disclosure, which can be applied to energy storage systems, such as Figure 2 As shown, the method may include:

[0081] Step 201: Obtain charging information and basic parameter information of the battery cell.

[0082] In an embodiment of the present disclosure, the energy storage system may include multiple electrical cabinets, each of which may include multiple battery cells. After the energy storage system completes a charge, the energy storage system may store charging information and basic parameter information of each battery cell in each electrical cabinet during the charge process.

[0083] The charging information may include information such as the battery cell's charge cut-off voltage, charging duration, charging current, and full charge cut-off voltage. The basic parameter information may include the battery cell's SOC_OCV curve. The SOC of the battery cell can be used to characterize the available remaining capacity of the battery cell. The OCV refers to the voltage across the battery cell in an open circuit state.

[0084] Optionally, the energy storage system may obtain charging information and basic parameter information of the battery cell after the most recent charge at predetermined charging times, and estimate the capacity of the battery cell based on the obtained charging information and basic parameter information of the battery cell. The battery cell refers to each battery cell in multiple electrical cabinets.

[0085] In an embodiment of the present disclosure, after obtaining the charging information and basic parameter information of the battery cells, the energy storage system may perform preprocessing on the charging information and basic parameter information to ensure the quality of the data used to estimate the battery cell capacity. The preprocessing may include one or more of: deduplication, de-duplication, and anomaly filtering.

[0086] Step 202: Determine the SOC threshold of the low-end region of the battery cell, and determine the low-end estimated voltage according to the SOC threshold of the low-end region and the soc_ocv curve.

[0087] After obtaining the charging information and basic parameter information of the battery cell, the energy storage system can determine the low-end estimated voltage of the battery cell according to the soc_ocv curve.

[0088] Optionally, the energy storage system may determine a low-end SOC threshold of the battery cell, wherein the low-end SOC threshold may be pre-stored in the energy storage system, and for example, the low-end SOC threshold may be 30%.

[0089] After determining the low-end SOC threshold of the battery cell, the energy storage system can determine the low-end estimated voltage based on the low-end SOC threshold and the soc_ocv curve. It is understood that the multiple SOCs in the soc_ocv curve correspond one-to-one with the multiple OCVs, so the energy storage system can determine the low-end estimated voltage corresponding to the low-end SOC threshold from the soc_ocv curve.

[0090] Step 203: Obtain a pre-configured cell ocv_cap table, and obtain the low-end region capacity by querying the cell ocv_cap table based on the low-end estimated voltage.

[0091] In the disclosed embodiment, the energy storage system is pre-configured with a cell ocv_cap table. This table records multiple OCVs and multiple caps, with each OVV corresponding to each cap. After determining the low-end estimated voltage, the energy storage system can retrieve the pre-configured cell ocv_cap table and, based on the low-end estimated voltage, query the cell ocv_cap table to obtain the low-end capacity corresponding to the low-end estimated voltage.

[0092] Step 204 : Determine a charging current from the low-end estimated voltage to the charging cut-off voltage according to the charging information.

[0093] After obtaining the charging information of the battery cell, the energy storage system can also determine the charging current from the low-end estimated voltage to the charging cut-off voltage based on the charging information. The charging information can also include the charging current from the low-end estimated voltage to the charging cut-off voltage.

[0094] Step 205 : Use the ampere-hour integration method to estimate the capacity of the charging current, and obtain the plateau capacity of the battery cell from the low-end estimated voltage to the charging cut-off voltage.

[0095] After determining the charging current from the low-end estimated voltage to the charging cut-off voltage, the energy storage system can use the ampere-hour integration method to estimate the capacity of the charging current, thereby obtaining the plateau capacity of the battery cell from the low-end estimated voltage to the charging cut-off voltage. Optionally, the plateau capacity can meet the following requirements: The cap L For the low-end area capacity, the C N1 is the rated capacity of the battery cell, I1 is the charging current, η1 is the charging efficiency of the battery cell, and t1 is the charging time of the battery cell from the low-end estimated voltage to the charging cut-off voltage.

[0096] Step 206: Obtain a relationship model between the SOC and voltage of the battery cell.

[0097] After determining the low-end area capacity and the platform area capacity, the energy storage system can obtain the relationship model between the SOC and voltage of the battery cell.

[0098] In the disclosed embodiments, the relationship model may be constructed by the energy storage system or by a model-building device. If the relationship model is constructed by the model-building device, the energy storage system may obtain the relationship model from the model-building device when executing this step, or may obtain and store the relationship model from the model-building device before executing this step.

[0099] The following uses the energy storage system as an example to illustrate the relationship model. Figure 3 , the relationship model can be fitted according to the following steps:

[0100] A1. Obtain an estimated charging start voltage and an estimated charging end voltage of a target battery cell among multiple battery cells.

[0101] The energy storage system can obtain an estimated charging start voltage and an estimated charging end voltage of a target cell among the multiple cells, wherein the estimated charging end voltage of the target cell is the maximum charging end voltage of the multiple cells.

[0102] Optionally, the energy storage system can obtain the charge cut-off voltages of multiple battery cells, and determine the battery cell corresponding to the largest charge cut-off voltage among the multiple charge cut-off voltages as the target battery cell, and then the energy storage system can determine the charge cut-off voltage of the target battery cell as the charge cut-off estimated voltage of the target battery cell, and determine the charge start estimated voltage of the target battery cell based on the charge cut-off estimated voltage of the target battery cell and a preset voltage. The preset voltage is pre-stored in the energy storage system, and the charge start estimated voltage is greater than the preset voltage and less than the charge cut-off estimated voltage. For example, the preset voltage can be 3.5 volts (voltage, V).

[0103] In the disclosed embodiment, the multiple battery cells may be located in the same electrical cabinet. The charge cutoff voltage of the battery cell refers to the voltage of the battery cell after charging is completed. The target battery cell is the battery cell with the highest voltage in the electrical cabinet after charging is completed.

[0104] A2. Determine the estimated current of the target cell from the estimated charging start voltage to the estimated charging end voltage.

[0105] After obtaining the estimated charge start voltage and the estimated charge end voltage of a target cell among the multiple cells, the energy storage system can determine the estimated current of the target cell from the estimated charge start voltage to the estimated charge end voltage. Optionally, the charging information of the target cell may also include the estimated current of the target cell from the estimated charge start voltage to the estimated charge end voltage. The energy storage system can determine the estimated current of the target cell from the estimated charge start voltage to the estimated charge end voltage based on the charging information.

[0106] A3. Use the ampere-hour integration method to estimate the capacity of the estimated current and obtain the charging capacity of the target battery cell from the estimated charging start voltage to the estimated charging end voltage.

[0107] After determining the estimated current of the target battery cell from the estimated charging start voltage to the estimated charging end voltage, the energy storage system can use the ampere-hour integration method to estimate the capacity of the estimated current, thereby obtaining the charging capacity of the target battery cell from the estimated charging start voltage to the estimated charging end voltage.

[0108] In the embodiment of the present disclosure, the charging capacity can meet the following requirements: The cap is the capacity of the target cell when the voltage of the target cell is the estimated charging start voltage. N2 is the rated capacity of the target battery cell, I2 is the estimated current, η2 is the charging efficiency of the target battery cell, and t2 is the charging time of the target battery cell from the estimated charging start voltage to the estimated charging end voltage.

[0109] A4. Determine the compensation capacity of the target battery cell based on the estimated charge start voltage, the estimated charge end voltage, the charge capacity, and the full charge end voltage of the target battery cell.

[0110] After obtaining the charge capacity of the target cell from the estimated charge start voltage to the estimated charge end voltage, the energy storage system can determine the compensation capacity of the target cell based on the estimated charge start voltage, the estimated charge end voltage, the charge capacity, and the full charge end voltage of the target cell. The compensation capacity refers to the capacity required to fully charge the target cell after the charge end voltage is reached.

[0111] In an embodiment of the present disclosure, the energy storage system can determine the unit charging capacity of the target battery cell based on the estimated charging start voltage, the estimated charging end voltage and the charging capacity, where the unit charging capacity refers to the charging capacity corresponding to each volt of voltage, and determine the compensation capacity based on the estimated charging end voltage, the full charging end voltage and the unit charging capacity.

[0112] Optionally, the energy storage system may calculate a first voltage difference between the estimated charge cutoff voltage and the estimated charge start voltage, and determine the unit charge capacity of the target battery cell as the ratio of the charge capacity to the first voltage difference. The energy storage system may then calculate a second voltage difference between the full charge cutoff voltage and the estimated charge cutoff voltage, and determine the compensation capacity based on the product of the second voltage difference and the unit charge capacity.

[0113] A5. Fit the relationship between the compensation capacity, the charge cut-off estimated voltage, and the full charge cut-off voltage to obtain a relationship model.

[0114] In an embodiment of the present disclosure, the energy storage system can determine a target cell from each of the multiple electrical cabinets and, by executing steps A1 to A4, determine the compensation capacity, estimated charge cutoff voltage, and full charge cutoff voltage of the target cell in each electrical cabinet, thereby obtaining multiple compensation capacities, multiple estimated charge cutoff voltages, and multiple full charge cutoff voltages. The energy storage system can then fit the relationship between the multiple compensation capacities, multiple estimated charge cutoff voltages, and full charge cutoff voltages to obtain a relationship model.

[0115] Optionally, the energy storage system can determine the difference between the full charge cut-off voltage and the estimated charge cut-off voltage of each target battery cell to obtain multiple differential voltages. The energy storage system can then use a fitting algorithm to fit the relationship between the multiple compensation capacities and the multiple differential voltages, thereby obtaining a relationship model. The compensation capacity y in the relationship model can satisfy: y = k1×v + k2×v 2 +......+k n ×v n , the k i is the i-th coefficient of the relationship model, v is the differential voltage, n is a positive integer, and i is a positive integer less than or equal to n. Optionally, the fitting algorithm may be a least squares method.

[0116] Step 207: Input the charge cut-off voltage and the full charge cut-off voltage of the battery cell into the relationship model to obtain an estimated SOC value of the battery cell.

[0117] After obtaining the relationship model, the energy storage system can input the charge cut-off voltage and the full charge cut-off voltage of the battery cell into the relationship model, so that the relationship model can output the SOC estimation value of the battery cell.

[0118] Optionally, the energy storage system may input the difference between the full charge cut-off voltage and the charge cut-off voltage of the battery cell into the relationship model, whereby the relationship model may output an estimated SOC value of the battery cell.

[0119] Step 208: Determine the terminal region compensation capacity according to the estimated SOC value and the nominal capacity of the battery cell.

[0120] After obtaining the estimated SOC value of the battery cell, the energy storage system can determine the end-zone compensation capacity based on the estimated SOC value and the nominal capacity of the battery cell. Optionally, the energy storage system can determine the end-zone compensation capacity as the product of the estimated SOC value and the nominal capacity of the battery cell.

[0121] Step 209: Determine the estimated capacity of the battery cell according to the low-end region capacity, the platform region capacity, and the terminal region compensation capacity.

[0122] After determining the terminal area compensation capacity of the battery cell, the energy storage system can determine the estimated capacity of the battery cell based on the low-end area capacity, the platform area capacity and the terminal area compensation capacity, thereby accurately estimating the capacity of the battery cell.

[0123] Optionally, the energy storage system can determine the sum of the low-end area capacity, the platform area capacity and the terminal area compensation capacity as the estimated cell capacity, that is, the estimated cell capacity can meet the following requirements: cap L +cap ah +cap comp , the cap ah is the platform area capacity, cap compCompensate capacity for the terminal area.

[0124] Step 210: Determine the SOH value of the battery cell according to the estimated capacity of the battery cell and the nominal capacity of the battery cell.

[0125] After determining the estimated capacity of the battery cell, the energy storage system can determine the SOH value of the battery cell based on the estimated capacity of the battery cell and the nominal capacity of the battery cell, thereby accurately detecting the health status of the battery cell. Optionally, the energy storage system can determine the ratio of the estimated capacity of the battery cell to the nominal capacity of the battery cell as the SOH value of the battery cell, that is, the SOH value of the battery cell can meet the following requirements: C0 is the nominal capacity of the battery cell.

[0126] In the embodiment of the present disclosure, for each battery cell in each electrical cabinet, the energy storage system can determine the SOH value of the battery cell, thereby determining the health status of the battery cell, and if the SOH value of the battery cell is low, promptly replace the battery cell or perform maintenance on the battery cell.

[0127] In addition, the energy storage system can determine the SOH value of each electrical cabinet based on the SOH values of multiple battery cells in the cabinet, thereby accurately evaluating the consistency and difference of the SOH values of different battery cells in each electrical cabinet, as well as the consistency and difference of the SOH values of different electrical cabinets.

[0128] In addition, the battery cell capacity estimation method provided by the embodiment of the present disclosure is simple to calculate, does not require complex decoupling and more computing power resources, and under constant current conditions, can calculate the SOH value of a single battery cell and the SOH value of a cabinet under non-full charge conditions.

[0129] refer to Figure 4 The energy storage system can display a display interface 00, which includes an SOH monitoring button 30. After receiving a selection operation for the SOH monitoring button, the energy storage system can display a first display button 301 for each cabinet's SOH and a second display button 302 for the battery cell's SOH. After receiving a selection operation for the first display button 301, a schematic diagram of the SOH of each cabinet can be displayed. The horizontal axis of the schematic diagram can be the cabinet's serial number, and the vertical axis of the schematic diagram can be the cabinet's SOH value. This schematic diagram can intuitively show the consistency and differences in the SOH between different cabinets.

[0130] refer to Figure 4After receiving a selection operation on the second display button 302, the energy storage system can display buttons with serial numbers for multiple electrical cabinets. After receiving a selection operation on a serial number button for any electrical cabinet, a schematic diagram of the SOH and low-end capacity of the battery cells can be displayed. The horizontal axis of the schematic diagram can be the serial numbers of the multiple battery cells in the electrical cabinet, and the vertical axis can be an integer less than 1. This schematic diagram can intuitively show the consistency and difference in the SOH of the multiple battery cells in the electrical cabinet, as well as the consistency and difference in the low-end capacity of the multiple battery cells.

[0131] like Figure 4 As shown, the low-end capacity of the battery cell No. 1 is 0.076, and the S0H value is 0.946. The low-end capacity of the battery cell No. 2 is 0.07, and the S0H value is 0.94. The low-end capacity of the battery cell No. 3 is 0.05, and the S0H value is 0.921. The low-end capacity of the battery cell No. 4 is 0.049, and the S0H value is 0.919. The low-end capacity of the battery cell No. 5 is 0.063, and the S0H value is 0.933. The low-end capacity of the battery cell No. 6 is 0.053, and the S0H value is 0.923. The low-end capacity of the battery cell No. 7 is 0.049, and the S0H value is 0.919. The low-end capacity of the battery cell No. 8 is 0.057, and the S0H value is 0.928.

[0132] In the embodiment of the present disclosure, the display interface 00 may also be provided with an SOC error monitoring button, an energy efficiency button, a direct current resistance (DCR) monitoring button, a fault monitoring button, and other buttons. Upon receiving a selection operation for any of these buttons, the energy storage system may display corresponding interface information.

[0133] In summary, the embodiments of the present disclosure provide a method for estimating the capacity of a battery cell, in which the energy storage system can estimate the low-end capacity, platform capacity, and terminal compensation capacity of the battery cell based on the soc_ocv curve and the charging cut-off voltage of the battery cell, and determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity, and terminal compensation capacity. For the battery cells in the cabinet that are not fully charged, the energy storage system can determine the capacity required to fully charge the battery cell after the charging of the battery cell is cut off, and adopt a three-stage capacity estimation method (low-end capacity, platform capacity, and terminal compensation capacity of the battery cell) to realize the capacity estimation of the battery cells in the cabinet that are not fully charged, thereby improving the accuracy of the capacity estimation of the battery cells in the cabinet that are not fully charged.

[0134] Figure 3 This is a flow chart of a method for constructing a model for estimating cell capacity provided by an embodiment of the present disclosure. Figure 3 As shown, applied to a model building device, the method may include:

[0135] Step A1: Obtain an estimated charging start voltage and an estimated charging end voltage of a target battery cell among multiple battery cells.

[0136] Step A2: determining an estimated current of the target battery cell from the estimated charging start voltage to the estimated charging end voltage.

[0137] Step A3: Use the ampere-hour integration method to estimate the capacity of the estimated current to obtain the charging capacity of the target battery cell from the estimated charging start voltage to the estimated charging end voltage.

[0138] Step A4: determining the compensation capacity of the target battery cell according to the estimated charge start voltage, the estimated charge end voltage, the charge capacity, and the full charge end voltage of the target battery cell.

[0139] Step A5: Fit the relationship between the compensation capacity, the estimated charge cut-off voltage, and the full charge cut-off voltage of the target battery cell to obtain a relationship model.

[0140] The relationship model between the SOC and voltage of the battery cell is used to determine the estimated SOC value of the battery cell, so as to determine the terminal area compensation capacity of the battery cell according to the estimated SOC value.

[0141] Optionally, the model building device may send the relationship model to the energy storage system so that the energy storage system determines the SOC estimation value of the battery cell according to the relationship model, and determines the terminal area compensation capacity of the battery cell according to the SOC estimation value.

[0142] In summary, the embodiments of the present disclosure provide a model construction method for estimating the capacity of a battery cell, in which the model construction device can determine the compensation capacity of the target battery cell based on the estimated charging start voltage, the estimated charging end voltage, the charging capacity and the full charge cut-off voltage of the target battery cell, and fit the relationship between the compensation capacity and the estimated charging cut-off voltage and the full charge cut-off voltage of the target battery cell to obtain a relationship model between the SOC and voltage of the battery cell.

[0143] The energy storage system can thus determine the estimated SOC value of the battery cell based on this relationship model, and then determine the terminal compensation capacity of the battery cell based on the estimated SOC value. For batteries in a partially charged cabinet, the energy storage system can determine the compensation capacity required to fully charge the battery cell after charging is terminated. Using a three-stage capacity estimation method (low-end capacity, platform capacity, and terminal compensation capacity), this system can estimate the capacity of batteries in partially charged cabinets, improving the accuracy of capacity estimation for batteries in partially charged cabinets.

[0144] An embodiment of the present disclosure provides a computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a computer device, the computer device implements the battery cell capacity estimation method described in the above embodiment.

[0145] An embodiment of the present disclosure provides another computer-readable storage medium having a computer program stored thereon. When the computer program is executed by a computer device, the computer device implements the model construction method for estimating the battery cell capacity described in the above embodiment.

[0146] Figure 5 is a structural diagram of an energy storage system provided by an embodiment of the present disclosure, such as Figure 5 As shown, the energy storage system 50 includes a memory 501 and a processor 502. The memory 501 stores a computer program. When the computer program is executed by the processor 502, the energy storage system 50 implements the battery cell capacity estimation method according to the above embodiment.

[0147] Figure 6 is a structural diagram of a model building device provided by an embodiment of the present disclosure, such as Figure 6 As shown, the model building device 60 includes a memory 601 and a processor 602. The memory 601 stores a computer program. When the computer program is executed by the processor 602, the model building device 60 implements the model building method for estimating the cell capacity according to the above embodiment.

[0148] Figure 7 is a block diagram of a battery cell capacity estimation device provided by an embodiment of the present disclosure, such as Figure 7 As shown, the device may include:

[0149] The first acquisition module 701 is used to acquire charging information and basic parameter information of the battery cell, where the charging information includes the charging cut-off voltage of the battery cell, and the basic parameter information includes the soc_ocv curve of the battery cell.

[0150] The estimation module 702 is used to estimate the low-end capacity, platform capacity and terminal compensation capacity of the battery cell according to the soc_ocv curve and the charging cut-off voltage, and determine the estimated capacity of the battery cell according to the low-end capacity, platform capacity and terminal compensation capacity.

[0151] In summary, the embodiments of the present disclosure provide a device for estimating the capacity of a battery cell, in which the energy storage system can estimate the low-end capacity, platform capacity, and terminal compensation capacity of the battery cell based on the soc_ocv curve and the charging cut-off voltage, and determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity, and terminal compensation capacity. For the battery cells in the cabinet that are not fully charged, the energy storage system can determine the capacity required to fully charge the battery cell after the charging of the battery cell is cut off, and adopts a three-stage capacity estimation method (low-end capacity, platform capacity, and terminal compensation capacity of the battery cell) to realize the capacity estimation of the battery cells in the cabinet that are not fully charged, thereby improving the accuracy of the capacity estimation of the battery cells in the cabinet that are not fully charged.

[0152] Optionally, the estimation module 702:

[0153] The low-end estimated voltage is determined according to the soc_ocv curve, and the charging current from the low-end estimated voltage to the charging cut-off voltage is determined according to the charging information.

[0154] The low-end capacity of the battery cell is estimated based on the low-end estimated voltage, the platform capacity of the battery cell is estimated based on the charging current, and the terminal compensation capacity of the battery cell is estimated based on the charging cut-off voltage.

[0155] Optionally, the estimation module 702 is configured to:

[0156] Get the relationship model between the SOC and voltage of the battery cell.

[0157] The charge cut-off voltage and the full charge cut-off voltage of the battery cell are input into the relationship model to obtain the estimated SOC value of the battery cell.

[0158] The terminal area compensation capacity is determined based on the SOC estimate and the nominal capacity of the battery cell.

[0159] Optionally, the relationship model is fitted according to the following steps:

[0160] Obtain an estimated charge start voltage and an estimated charge end voltage of a target battery cell among multiple battery cells.

[0161] Determine the estimated current of the target cell from the estimated charge start voltage to the estimated charge end voltage.

[0162] The capacity of the target battery cell is estimated from the estimated current using the ampere-hour integration method to obtain the charging capacity of the target battery cell from the estimated charging start voltage to the estimated charging end voltage.

[0163] The compensation capacity of the target battery cell is determined according to the estimated charge start voltage, the estimated charge end voltage, the charge capacity and the full charge cut-off voltage of the target battery cell, and the relationship between the compensation capacity and the estimated charge end voltage and the full charge cut-off voltage of the target battery cell is fitted to obtain a relationship model.

[0164] Optionally, the estimation module 702 is configured to:

[0165] The unit charging capacity of the target battery cell is determined based on the estimated charging start voltage, the estimated charging end voltage, and the charging capacity.

[0166] The compensation capacity is determined based on the estimated charge cut-off voltage, the full charge cut-off voltage of the target battery cell, and the unit charge capacity.

[0167] Optionally, the estimated charge cut-off voltage of the target battery cell is a maximum value of charge cut-off voltages of multiple battery cells.

[0168] Optional, reference Figure 8 , the device may further include:

[0169] The second determining module 703 is configured to:

[0170] Determine the low-end SOC threshold of the battery cell.

[0171] The low-end estimated voltage is determined based on the low-end region SOC threshold and the soc_ocv curve.

[0172] Optionally, the estimation module 702 is configured to:

[0173] Get the pre-configured cell ocv_cap table.

[0174] Based on the estimated low-end voltage, the low-end capacity is obtained by querying the cell ocv_cap table.

[0175] Optionally, the estimation module 702 is configured to:

[0176] The ampere-hour integration method is used to estimate the capacity of the charging current and obtain the platform capacity of the battery cell from the low-end estimated voltage to the charging cut-off voltage.

[0177] Optionally, the second determining module 703 is further configured to:

[0178] After determining the estimated capacity of the battery cell, the SOH value of the battery cell is determined based on the estimated capacity of the battery cell and the nominal capacity of the battery cell.

[0179] In summary, the embodiments of the present disclosure provide a device for estimating the capacity of a battery cell, in which the energy storage system can estimate the low-end capacity, platform capacity, and terminal compensation capacity of the battery cell based on the soc_ocv curve and the charging cut-off voltage, and determine the estimated capacity of the battery cell based on the low-end capacity, platform capacity, and terminal compensation capacity. For the battery cells in an incompletely charged electrical cabinet, the energy storage system can determine the capacity required to compensate for fully charging the battery cell after the charging of the battery cell is cut off, and adopts a three-stage capacity estimation method (low-end capacity, platform capacity, and terminal compensation capacity of the battery cell) to realize the capacity estimation of the battery cells in the incompletely charged electrical cabinet, thereby improving the accuracy of the capacity estimation of the battery cells in the incompletely charged electrical cabinet.

[0180] Figure 9 is a block diagram of a model building device for estimating cell capacity provided by an embodiment of the present disclosure, such as Figure 9 As shown, the device may include:

[0181] The second acquisition module 901 is configured to acquire an estimated charging start voltage and an estimated charging end voltage of a target battery cell among the multiple battery cells.

[0182] The first determining module 902 is configured to determine an estimated current of a target battery cell from an estimated charging start voltage to an estimated charging end voltage.

[0183] The third acquisition module 903 is configured to estimate the capacity of the estimated current using an ampere-hour integration method, and obtain the charging capacity of the target cell from the estimated charging start voltage to the estimated charging end voltage.

[0184] The fitting module 904 is used to determine the compensation capacity of the target battery cell based on the estimated charging start voltage, the estimated charging end voltage, the charging capacity and the full charge cut-off voltage of the target battery cell, and fit the relationship between the compensation capacity and the estimated charging end voltage and the full charge cut-off voltage of the target battery cell to obtain a relationship model between the SOC and voltage of the battery cell, wherein the relationship model is used to determine the estimated SOC value of the battery cell, so as to determine the terminal area compensation capacity of the battery cell based on the estimated SOC value.

[0185] In summary, the embodiments of the present disclosure provide a model building device for estimating the capacity of a battery cell, in which the model building device can determine the compensation capacity of the target battery cell based on the estimated charging start voltage, the estimated charging end voltage, the charging capacity and the full charge cut-off voltage of the target battery cell, and fit the relationship between the compensation capacity and the estimated charging end voltage and the full charge cut-off voltage of the target battery cell to obtain a relationship model between the SOC and voltage of the battery cell.

[0186] The energy storage system can thus determine the estimated SOC value of the battery cell based on this relationship model, and then determine the terminal compensation capacity of the battery cell based on the estimated SOC value. For batteries in a partially charged cabinet, the energy storage system can determine the compensation capacity required to fully charge the battery cell after charging is terminated. Using a three-stage capacity estimation method (low-end capacity, platform capacity, and terminal compensation capacity), this system can estimate the capacity of batteries in partially charged cabinets, improving the accuracy of capacity estimation for batteries in partially charged cabinets.

[0187] It should be noted that the logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by an instruction execution system, apparatus, or device (such as a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device), or in conjunction with such instruction execution system, apparatus, or device. For the purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transmit a program for use by an instruction execution system, apparatus, or device, or in conjunction with such instruction execution system, apparatus, or device. More specific examples (non-exhaustive list) of computer-readable media include the following: an electrical connection portion having one or more wires (electronic device), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or processing it in another suitable manner if necessary, and then storing it in a computer memory.

[0188] It should be understood that various parts of the present disclosure can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0189] Throughout this specification, reference to terms such as "optional," "some embodiments," "examples," "specific examples," or "some examples" means that a specific feature, structure, material, or characteristic described in conjunction with that embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, schematic representations of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

[0190] In addition, the terms "first" and "second" used in the embodiments of the present disclosure are only used for descriptive purposes and should not be understood as indicating or implying relative importance, or implicitly indicating the number of technical features indicated in the embodiments. Therefore, the features defined in the embodiments of the present disclosure with terms such as "first" and "second" can explicitly or implicitly indicate that the embodiment includes at least one such feature. In the description of the present disclosure, the word "plurality" means at least two or two or more, such as two, three, four, etc., unless otherwise clearly and specifically defined in the embodiments.

[0191] Although the embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are illustrative and are not to be construed as limitations on the present disclosure. A person skilled in the art may change, modify, replace and vary the above embodiments within the scope of the present disclosure.

Claims

1. A method for estimating battery cell capacity, characterized in that: include: Obtaining charging information and basic parameter information of the battery cell, wherein the charging information includes the charging cut-off voltage of the battery cell, and the basic parameter information includes the soc_ocv curve of the battery cell; Estimating the low-end region capacity, platform region capacity, and terminal region compensation capacity of the battery cell according to the soc_ocv curve and the charge cut-off voltage; including obtaining a relationship model between the SOC and voltage of the battery cell; inputting the charge cut-off voltage and the full charge cut-off voltage of the battery cell into the relationship model to obtain an estimated SOC value of the battery cell; and determining the terminal region compensation capacity according to the estimated SOC value and the nominal capacity of the battery cell; The relationship model is obtained by fitting according to the following steps: obtaining the estimated charging start voltage and the estimated charging end voltage of the target battery cell among the multiple battery cells; determining the estimated current of the target battery cell from the estimated charging start voltage to the estimated charging end voltage; using the ampere-hour integration method to perform capacity estimation on the estimated current to obtain the charging capacity of the target battery cell from the estimated charging start voltage to the estimated charging end voltage; determining the compensation capacity of the target battery cell according to the estimated charging start voltage, the estimated charging end voltage, the charging capacity and the full charge cut-off voltage of the target battery cell, and fitting the relationship between the compensation capacity, the estimated charging end voltage and the full charge cut-off voltage of the target battery cell to obtain the relationship model; The estimated capacity of the battery cell is determined according to the low-end region capacity, the platform region capacity and the terminal region compensation capacity.

2. The method for estimating battery cell capacity according to claim 1, wherein: Estimating the low-end region capacity, the platform region capacity, and the terminal region compensation capacity of the battery cell according to the soc_ocv curve and the charge cut-off voltage includes: determining a low-end estimated voltage according to the soc_ocv curve, and determining a charging current from the low-end estimated voltage to the charging cut-off voltage according to the charging information; The low-end region capacity of the battery cell is estimated according to the low-end estimated voltage, the platform region capacity of the battery cell is estimated according to the charging current, and the terminal region compensation capacity of the battery cell is estimated according to the charging cut-off voltage.

3. The method for estimating battery cell capacity according to claim 1, wherein: Determining the compensation capacity of the target battery cell according to the estimated charge start voltage, the estimated charge end voltage, the charge capacity, and the full charge end voltage of the target battery cell includes: Determining a unit charging capacity of the target battery cell according to the estimated charging start voltage, the estimated charging end voltage, and the charging capacity; The compensation capacity is determined according to the charge cut-off estimated voltage, the full charge cut-off voltage of the target battery cell, and the unit charging capacity.

4. The method for estimating battery cell capacity according to claim 1, wherein: The estimated charge cut-off voltage of the target battery cell is a maximum value of the charge cut-off voltages of the plurality of battery cells.

5. The method for estimating battery cell capacity according to any one of claims 1 to 4, wherein: Determining a low-end estimated voltage according to the soc_ocv curve includes: Determining a low-end SOC threshold of the battery cell; The low-end estimated voltage is determined according to the low-end region SOC threshold and the soc_ocv curve.

6. The method for estimating battery cell capacity according to claim 2, wherein: Estimating the low-end region capacity of the battery cell according to the low-end estimated voltage includes: Get the pre-configured cell ocv_cap table; The low-end region capacity is obtained by querying the cell ocv_cap table according to the low-end estimated voltage.

7. The method for estimating battery cell capacity according to claim 2, wherein: Estimating the plateau capacity of the battery cell according to the charging current includes: The capacity of the charging current is estimated by using an ampere-hour integration method to obtain the platform capacity of the battery cell from the low-end estimated voltage to the charging cut-off voltage.

8. The method for estimating battery cell capacity according to any one of claims 1 to 4, characterized in that: After determining the estimated capacity of the battery cell, the method further includes: The SOH value of the battery cell is determined according to the estimated capacity of the battery cell and the nominal capacity of the battery cell.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores a computer program, and when the computer program is executed by a computer device, the computer device implements the battery cell capacity estimation method according to any one of claims 1 to 8.

10. An energy storage system, characterized in that: The system comprises a memory and a processor, wherein the memory stores a computer program, and when the computer program is executed by the processor, the energy storage system implements the battery cell capacity estimation method according to any one of claims 1 to 8.

11. A battery cell capacity estimation device, characterized in that: include: A first acquisition module is used to acquire charging information and basic parameter information of the battery cell, wherein the charging information includes a charging cut-off voltage of the battery cell, and the basic parameter information includes a soc_ocv curve of the battery cell; an estimation module, configured to estimate the low-end region capacity, the platform region capacity, and the terminal region compensation capacity of the battery cell according to the soc-ocv curve and the charge cut-off voltage, including obtaining a relationship model between the SOC and voltage of the battery cell; inputting the charge cut-off voltage and the full charge cut-off voltage of the battery cell into the relationship model to obtain an estimated SOC value of the battery cell; and determining the terminal region compensation capacity according to the estimated SOC value and the nominal capacity of the battery cell; The relationship model is obtained by fitting according to the following steps: obtaining the estimated charging start voltage and the estimated charging end voltage of the target battery cell among the multiple battery cells; determining the estimated current of the target battery cell from the estimated charging start voltage to the estimated charging end voltage; using the ampere-hour integration method to perform capacity estimation on the estimated current to obtain the charging capacity of the target battery cell from the estimated charging start voltage to the estimated charging end voltage; determining the compensation capacity of the target battery cell according to the estimated charging start voltage, the estimated charging end voltage, the charging capacity and the full charge cut-off voltage of the target battery cell, and fitting the relationship between the compensation capacity, the estimated charging end voltage and the full charge cut-off voltage of the target battery cell to obtain the relationship model; The estimated capacity of the battery cell is determined based on the capacity of the low-end area, the capacity of the platform area and the compensation capacity of the terminal area.

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