Method for determining the charging capacity of a battery

Abstract

The invention describes a method for determining the capacity (C) of a battery (1), wherein an identifier (8) is attached to each of a first plurality of electrode foils (2), wherein a second plurality of individual electrodes (4s) are produced from the first plurality of electrode foils (2) in such a way that each individual electrode (4s) is identifiable at least batch-wise by means of the associated identifier (8), wherein geometric data (dG) and / or material-related data (dM) and / or process-related data (dP) are recorded for each of the second plurality of individual electrodes (4s) during their production, and are assigned to the respective individual electrode (4s) by means of the identifier (8) of the associated electrode foil (2), wherein a single-layer capacity (Cs) is determined for each of the said individual electrodes (4s) on the basis of the respective geometric data (dG) and / or material-related data (dM) and / or process-related data (dP).and wherein a capacity (C) of a battery (1), which is formed on the basis of the second plurality of individual electrodes (4s), is determined on the basis of the associated single-layer capacitances (Cs).

Description

[0001] The invention relates to a method for determining the capacity of a battery, in particular a battery for a motor vehicle (motor vehicle).

[0002] In the production of batteries, especially lithium (Li)-ion batteries, accurately determining the battery's capacity—that is, the amount of charge and therefore energy that can be drawn from the battery—is of paramount importance. Particularly for electric vehicles, where the highest possible volumetric charge density is desired, the usual fluctuations that occur during production processes cannot be ignored. Therefore, manufacturers typically test the capacity of all batteries again before delivery.

[0003] However, testing the capacity of each individual battery produced requires significant investment by the manufacturer in appropriate test benches, both in terms of the actual testing equipment and the space required. Such a test, in which the battery is usually charged and discharged (possibly several times) while the amount of charge absorbed and discharged is recorded, can take several hours for each battery, negatively impacting the cost structure of production.

[0004] To shorten the testing of manufactured batteries' capacity, various approaches exist. One such approach involves not fully charging and discharging the battery for testing, but rather performing only parts of this process, for example, omitting the complete discharge and extrapolating the missing data. However, a real time saving is only achieved if the charging process is also shortened by extrapolating the missing data (e.g., by measuring the corresponding open-circuit voltages). Such a procedure, however, initially leads to significant losses in the precision of determining a battery's capacity.

[0005] Accordingly, the capacity of a delivered battery cannot be adequately guaranteed (also considering the fluctuations that occur during the manufacturing process). As an improvement to this approach, an attempt is being made to collect corresponding charging curves for a large number of batteries using the "partial" charging process described above, and to create an artificial intelligence (AI)-based model from these curves. This model will be used to verify the extrapolations for battery capacity resulting from the charging curves of the partial charging processes by comparing them with actual capacity measurements, and from which training data (with associated error data) for the model can be obtained.

[0006] A similar approach is proposed in CN 114 660 462 A, which describes an AI-based model for predicting battery performance. This model uses data such as voltage, state of health, temperature, and other model-specific information from a large number of batteries to train the model. Based on this information, the model can then determine the available battery performance for a given battery.

[0007] One problem with these AI-based models, which use real information from batteries (such as a partial charging curve or data on temperature and voltage during charging / discharging) to estimate the behavior of a specific battery through appropriate training, is the requirement for a usually very complex training phase, in which the capacity of all batteries must actually be measured to enable error feedback of the model.

[0008] This significantly reduces the potential savings in time and resources, and thus the potential benefit of the model. Furthermore, even with extensive model training, sufficient accuracy in predicting capacity is still not guaranteed, as the model parameters may, for intrinsic reasons, simply not allow for such a precise prediction to the desired extent.

[0009] DE 10 2022 125 877 A1 relates to capacity-based quality monitoring and control in battery manufacturing.

[0010] JP 2012 - 256 528 A describes a method for a battery manufacturing apparatus for a battery in which a separator is placed between a positive electrode plate and a negative electrode plate and an electrode plate group formed by lamination or winding in the laminated state is inserted into a battery casing to inject a predetermined amount of electrolyte.

[0011] The invention is therefore based on the objective of providing a method for determining the capacity of a battery that is as precise as possible and requires as little time and investment as possible.

[0012] The aforementioned problem is solved according to the invention by a method for determining the capacity of a battery, in particular a lithium-ion battery, wherein an identifier is attached to each of a first plurality of electrode foils, wherein a second plurality of individual electrodes are produced from the first plurality of electrode foils in such a way that each individual electrode can be identified at least batch-wise by reference to the associated identifier, wherein geometric data and / or material-related data and / or process-related data are recorded for each of the second plurality of individual electrodes during their production, and are assigned to the respective individual electrode by reference to the identifier of the associated electrode foil, wherein for each of the said individual electrodes, based on the respective geometric data and / or material-related data and / or process-related data, in particular by means of a first mathematical model,a single-layer capacitance is determined, and wherein a battery capacity formed on the basis of the second plurality of individual electrodes is determined on the basis of the associated single-layer capacitances, in particular by means of a second mathematical model. Advantageous and partly inventive embodiments are the subject of the dependent claims and the following description.

[0013] An electrode foil, in this context, refers specifically to a foil that is processed into a single electrode—that is, a single cathode or anode layer—by means of a suitable coating, particularly with electrochemically active material, and possibly further processing steps such as rolling / calendering, heating, and appropriate cutting. The term "electrode foil" encompasses both the substrate to be coated (i.e., an aluminum foil for a cathode layer or a copper foil for an anode layer) and the substrate in its subsequent processing steps up to the final production of the single electrode (i.e., the coated substrate, the coated and rolled substrate, etc.).

[0014] An electrode foil can be defined, in particular, as a uniquely identifiable section of a continuous roll of foil, such that successive sections, each with different identifiers, can be considered distinct electrode foils. However, an electrode foil can also be defined as a suitably cut piece of foil for the production of individual electrodes (cathode or anode layers).

[0015] The production of a second plurality of individual electrodes from the first plurality of electrode foils includes, in particular, processing the said first plurality of electrode foils—which may consist, in particular, of appropriately cut foil pieces, each bearing an identifier, or of individual sections of a continuous foil roll identifiable by their respective identifiers—into a second plurality of individual electrodes. In this process, exactly one individual electrode can be produced from each electrode foil through the processing steps carried out on it; that is, each individual electrode has its own identifier. Alternatively, a preferably small to manageable plurality of individual electrodes can be produced from one electrode foil, which shall be referred to here as a "batch" of individual electrodes.In the latter case, the belonging of an individual electrode to the relevant batch can preferably be recognized via the respective identifier of the electrode foil in question, thereby making the individual electrode identifiable batch by batch.

[0016] The acquisition of geometric, material, and / or process-related data for a single electrode during its production includes, in particular, the collection of said data by performing corresponding measurements on the associated electrode foil during its processing into a single electrode, i.e., during the individual processing steps or at intervals. For the processing step of coating the electrode foil with electrochemically active material (from which the respective electrically active layer of the anode or cathode is formed), this can also include the process of mixing the coating components. In particular, measurements of process parameters can also be performed to acquire said data (e.g., the distance between rollers for a rolling or calendering process, the temperature of a furnace for heating coated electrode foils, etc.).

[0017] The geometric data of a single electrode includes, in particular, data on its dimensions (i.e., length and width), but also data on the geometry of its coating with active material, such as the coating thickness or, if applicable, the coating edge width, which specifically characterizes the width of the transition from coated to uncoated electrode foil. In particular, if the aforementioned data is only recorded for a single electrode (such as the dimensions), it can be averaged for batch identification of individual electrodes to assign them to the respective batch, or a maximum, minimum, or median value can be used.

[0018] The material-related data of a single electrode includes, in particular, data that characterize the electrochemically active material with which the electrode sequence is coated to produce a single electrode, i.e., in particular a volume- or mass-related density of charge carriers, a specific capacitance, etc.

[0019] The process-related data of a single electrode include, in particular, coefficients that depend on individual processing steps and that can be determined, in particular, by means of appropriate simulations or a (manageable) number of prior measurements. Such coefficients may depend, for example, on the density after a rolling or calendering process or on a coating mixture. In particular, these coefficients, as process-related data, indicate the effect of the associated process on the capacity of the associated single electrode, and in particular, the coefficients may each take on values ​​from intervals of [0.85; 1.15], preferably [0.9; 1.1], especially preferably [0.95; 1.05] (whereby different intervals may apply as possible value ranges for different coefficients).

[0020] A single-layer capacity refers in particular to the contribution that a single electrode (cathode or anode layer) makes to the capacity of the battery, and / or the capacity (i.e., in particular, the maximum amount of charge carriers that can be absorbed or released) of the single electrode in question.

[0021] This single-layer capacity is now determined for each individual electrode based on geometric, material-related, and / or process-related data, preferably using a corresponding initial mathematical model that incorporates the respective data and may optionally include further estimated values ​​provided as external parameters, which can be progressively adjusted in an optimization procedure to be described later. The aforementioned data, which were acquired during, between, or after the individual processing steps of the electrode foil, are identified using the identifier attached to the respective electrode foil (i.e., the electrode number).(an overhanging foil flap with a printed barcode and / or QR code and / or RFID tag) of the associated single electrode, thus ensuring the use of the correct geometric, material-related and / or process-related values ​​for calculating the respective single-layer capacity.

[0022] Based on the individual layer capacitances of the electrodes, and in particular their sum, the capacity of the finished battery is determined. This battery is manufactured from the aforementioned individual electrodes, preferably by stacking them accordingly. During the battery's assembly, a liquid electrolyte can be injected into a casing enclosing the stack of individual electrodes. A further parameter or coefficient can be determined for this injection process, which can be considered in the first mathematical model of the individual layer capacitance mentioned above. However, the battery can also be manufactured as a solid electrolyte battery, in which case the injection process is omitted, and therefore no corresponding parameters need to be considered in the first mathematical model.

[0023] This advantageously exploits the fact that the capacitance of the battery's electrode stack, formed from the individual electrodes, is essentially linear in the individual layer capacitances of the individual electrodes, possibly up to a temperature factor. Furthermore, the individual layer capacitances can be determined using a suitable initial mathematical model based on parameters that can be captured during the production process without significant additional effort.

[0024] Preferably, the battery capacity is determined by summing the individual layer capacitances of the second plurality of individual electrodes. This is particularly advantageous due to the parallel connection of the individual layer capacitances by corresponding current paths, each leading to a common anode or cathode terminal of the battery. In particular, a second mathematical model can be used here, which, in addition to the sum of the individual layer capacitances, incorporates one or more further parameters, such as a temperature coefficient, which is particularly dependent on the number of individual electrodes, and a heat transfer characteristic of the waste heat generated by the individual electrodes. The aforementioned dependence of the temperature coefficient on the number of individual electrodes can be determined in advance, particularly by means of (a manageable number of) measurements.

[0025] Advantageously, geometric data such as length and width and / or coating thickness and / or edge area coefficient are recorded, and / or material-related data such as active material density and / or material-specific capacity, and / or process-related data such as mixing coefficient and / or rolling density coefficient and / or moisture coefficient and / or coating edge width.

[0026] The length and width of the individual electrode thus define its surface area, whereby, as a first approximation, a linear dependence of the single-layer capacitance on the area can generally be assumed (especially up to correction terms). The coating thickness indicates the thickness of the coating on the electrode foil and thus on the individual electrode with electrochemically active material, whereby, again, a linear dependence of the single-layer capacitance on the thickness, i.e., the thickness of the coating, can generally be assumed, assuming otherwise identical coating parameters (especially identical mixture and density / pressure). However, the coating thickness can also be included as an implicit value in the active material density if the active material density is related to an area (and not a volume). In this case, the coating thickness does not need to be measured separately. The same applies here.The aforementioned geometric data can preferably be specified in cm or other units of length.

[0027] The active material density preferably indicates the mass fraction of electrochemically active material present per unit area or per unit volume in the coating, and thus preferably also contributes linearly to a model of the single-layer capacitance. The active material density can preferably be expressed in g / cm². 2 or also in g / cm³ 3 (or equivalent units). The material-specific capacity preferably indicates the capacity or charge of the active material in the coating, which can vary, for example, across different batches of supplied or provided active material, and can be expressed in mAh / g (or equivalent units). The material-specific capacity thus preferably also enters the single-layer capacity model linearly.

[0028] The aforementioned assumption of the linear dependence of the single-layer capacitance preferably also applies to the coating edge width, i.e., to a strip-shaped area of ​​the electrode foil (and thus of the single electrode) which marks the transition between coated and uncoated electrode foil.

[0029] The mixing coefficient preferably describes the effect of mixing the electrochemically active material with other additives, particularly those resulting from the process, such as binders and / or solvents (but also conductive particles), which are added before coating, on the capacitance. The rolling density coefficient preferably describes the effect that different densities resulting from rolling and / or calendering have on the single-layer capacitance. The surface area coefficient preferably describes the influence of edge effects of the stacked individual electrodes on the capacitance of the finished battery, which depends on the surface area ratio (i.e., the ratio of the surface areas relevant to the edge effects to the total area of ​​the respective individual electrode). The humidity coefficient preferably describes the influence of ambient humidity during the production process on the single-layer capacitance.

[0030] The aforementioned coefficients can be determined, in particular, in a series of preliminary individual measurements and / or iteratively adjusted during the production process by randomly testing individual finished batteries and comparing the test result with the capacity value of the respective battery determined using the first mathematical model of the single-layer capacities, and making corresponding adjustments to the aforementioned coefficients. The mixing coefficient, the surface area coefficient, the moisture coefficient, and the rolling density coefficient can each, in particular, take values ​​from intervals of [0.85; 1.15], preferably [0.9; 1.1], and especially preferably [0.95; 1.05] (where different intervals can be considered possible value ranges for different coefficients).

[0031] Advantageously, the length and width, and especially the surface area coefficient, of a given individual electrode are recorded during or immediately before a stacking process of individual electrodes, and / or the coating thickness is recorded during or immediately after a coating process of the electrode foil. Recording a specific parameter immediately before (or after) a particular processing step of the electrode foil generally refers to recording before (or after) the processing step in question, but after (or before) a further preceding (or subsequent) processing step. The coating process of the electrode foil here refers specifically to the actual application of one or more mixtures (and, if applicable, auxiliary materials such as solvents, etc.) to the electrode foil.In particular, the coating thickness can be determined using laser measurement. The acquisition of a coefficient here refers specifically to the acquisition of the variables underlying the coefficient (i.e., geometric and / or process parameters).

[0032] It is further advantageous to determine the material-specific capacity based on a mixture of components for the coating process, and / or to measure the active material density during or immediately after the coating process. In particular, the material-specific capacity during the preparation of the mixture for the coating process can be determined based on individual volume and / or weight fractions of the reactants used. The active material density can be determined by means of an absorption measurement, e.g., absorption spectroscopy, which, for example, measures the absorption of beta radiation by the coating.

[0033] In a further advantageous embodiment, the mixing coefficient is determined based on the mixture of components for the coating process, and / or the coating edge width is measured, in particular by microscopy, during or immediately after a coating process of the electrode foil, and / or the rolling density coefficient is measured during or immediately after a rolling process of the coated electrode foil. For the determination of the aforementioned coefficients, the corresponding physical or chemical variables on which the respective coefficient depends are determined at the specified time (i.e., during / after the respective processing step). The dependence of the respective coefficient on the corresponding physical or chemical quantities is preferably determined beforehand in the manner already described.The moisture coefficient is preferably determined after the binders, solvents and other volatile components of the coating material have evaporated, preferably by measuring the humidity in the ambient air surrounding the production plant in question.

[0034] Advantageously, the battery is formed using the second plurality of individual electrodes, wherein the second plurality of individual electrodes are stacked into an electrode stack in a stacking process, the electrode stack is enclosed in a shell, and an electrolyte is injected into the shell. During said injection of the electrolyte, or immediately, an electrolyte injection coefficient is recorded, which is then assigned as further process-related data to the respective individual electrodes or to the electrode stack. This includes, in particular, that the individual electrodes, i.e., the individual anode and cathode layers, are stacked alternately, and that the enclosure of this stack by the shell does not yet include individual anode or cathode contacts for the corresponding contacting. The electrolyte injection coefficient preferably describes effects of the electrolyte or...The effect of moisture on the capacity, particularly the single-layer capacity, can be determined in advance, as already described, through appropriate individual measurements and / or models, as well as through continuous optimization of the models based on real sample measurements. The electrolyte injection coefficient can then be included as a factor in the single-layer capacity model, or as a common factor in the capacity of the "complete" battery (i.e., "before" a sum of the aforementioned single-layer capacities).

[0035] Particularly preferably, the single-layer capacitance Cs for each individual electrode is determined on the basis of a linear relation of the associated geometric data, i.e. preferably the length x and the width y as well as the boundary area coefficient Ed and / or the material-related data, i.e. preferably the active material density md and the material-specific capacitance as, and / or the process-related data, i.e. preferably the coating edge width yr, the mixing coefficient Em, the rolling density coefficient Er, the moisture coefficient Eh and optionally the electrolyte injection coefficient E-in.

[0036] According to a first mathematical model, the single-layer capacitance Cs is then preferably Cs=Fc⋅as⋅md⋅x⋅(y−yr / 2), wherein the coefficient factor Fc is preferably formed from the product of the coefficients involved, in particular the mixing coefficient Em, the rolling density coefficient Er, the surface area coefficient Ed, the moisture coefficient Eh and optionally the electrolyte injection coefficient E-in as Fc=Em⋅Er⋅Ed⋅Eh⋅E−in.

[0037] According to a second mathematical model, the battery capacity is then the sum of the individual layer capacities Cs, possibly multiplied by a temperature coefficient Eth, which characterizes the heat transfer through the individual electrodes.

[0038] Preferably, each individual electrode of the second plurality is generated from its own electrode foil of the first plurality. This means, in particular, that each individual electrode is assigned its own identifier of the associated electrode foil, which allows the relevant data to be recorded with particular precision, since, in particular, no interpolation or averaging of data at the electrode foil level is required for multiple individual electrodes.

[0039] Advantageously, a QR code and / or a barcode is applied as an identifier to a protruding tab on the electrode foil and / or to an uncoated recess in the electrode foil. This approach is easy to implement from a process engineering perspective and ensures a high degree of reliability in the recognition of the respective identifier during the individual processing steps of the associated electrode foil.

[0040] The invention further describes a method for optimizing the determination of a battery's capacity, wherein the capacity of a plurality of batteries is determined according to the method described above, the capacity of at least one of these batteries is measured, and at least one parameter for determining the single-layer capacity of the respective individual electrodes is adjusted based on the measured capacity. In particular, at least one of the coefficients of the process-related data can be adjusted as a parameter. The measurement of the battery's capacity includes, in particular, a measurement based on a charging or discharging process.

[0041] The advantages proposed for the above-mentioned procedure for determining capacity and for its further development can, mutatis mutandis, be applied analogously to the procedure for its optimization.

[0042] An embodiment of the invention is explained in more detail below with reference to the drawings. The drawings schematically show: Fig. 1 in a flowchart a procedure for determining the capacity of a battery based on single-layer capacities.

[0043] In Fig.Figure 1 is a flowchart illustrating the process for determining the capacity C of a battery 1. To manufacture the battery 1, a first plurality of electrode foils 2 are processed into a second plurality of individual electrodes 4s (cathode and anode layers), and the battery 1 is formed from these. During the various processing steps S1-S9, geometric data dG, material-related data dM, and process-related data dP are recorded to determine the capacity C of the battery 1. Based on these data, the individual layer capacitances Cs for the individual electrodes 4s are determined in a manner to be described later. Finally, the capacity C of the finished battery 1 is determined from the individual layer capacitances Cs.

[0044] In a first processing step S1, a mixture 6 is prepared from various starting materials 5, which include an electrochemically active material 5a. For the fabrication of cathode layers as single electrodes 4s, NCM, LFP, LMFP, NCA, LMO, or mixtures of these materials can be used as the electrochemically active material 5a. For the fabrication of anode layers as single electrodes 4s, graphite, carbon, silicon, a mixture of silicon and carbon, and / or metallic lithium can be used as the electrochemically active material 5a. From the composition of the mixture, a material-specific capacitance as and, if applicable, a mixing coefficient Em as process-related data dP can be obtained as material-related data dM.The material-specific capacitance as describes in particular the capacitance and / or charge carrier density of the electrochemically active material 5a of the coating per unit weight, while the mixing coefficient Em characterizes in particular the influences of process-related additions to the electrochemical material (such as binder and / or solvents) on the single-layer capacitance Cs.

[0045] In a next processing step S2, the electrode foil 2 (e.g., a copper foil for the anode layers and, for example, an aluminum foil for the cathode layers) is provided and each is provided with an identifier 8 (e.g., a tab with a QR code), whereby, as already described, each identifier 8 is assigned to a single electrode foil 2 (and a connected electrode foil 2 is considered as different pieces of the electrode foil 2 based on their different identifiers 8).

[0046] In the next processing step S3, the respective electrode foil 2 is coated with the mixture 6, whereby an active material density md (as material-related data dM) and a coating edge width yr (as process-related data dP) are recorded in the manner already described, which together with the material-specific capacitance as and the mixing coefficient Em of the mixture 6 can be uniquely assigned to the electrode foil 2 (i.e., in particular, the piece marked with the identifier 8) using the identifier 8.

[0047] In the subsequent processing step S4, the coated electrode foil 2 is rolled and / or calendered, whereby the coating density is measured. Based on this, a rolling density coefficient Er is determined as process-related data dM, which can also be uniquely assigned to the electrode foil 2 using the identifier 8. After rolling in processing step S4, the coated and rolled electrode foil is heated ("baked") in processing step S5 to bake out solvents in the coating of the mixture 6 (and, in the case of a solid electrolyte not shown here, for sintering). In this process, a humidity coefficient Eh can also be determined as further process-related data dP based on the ambient air humidity.

[0048] In the subsequent processing step S6, the electrode foil 2 is cut to form the individual electrodes 4s. Parameters can be recorded during cutting, from which a boundary area coefficient Ed is determined as geometric data dG. Furthermore, immediately after cutting in processing step S6, or during subsequent stacking in processing step S7, the dimensions, i.e., the length x and the width y of the individual electrodes 4s, can be recorded as geometric data dG. The boundary area coefficient Ed and the length x and width y can also be uniquely assigned to the electrode foil 2 using the identifier 8.

[0049] After the individual electrodes 4s are stacked to form an electrode stack 10 in processing step S7, the stack is processed into a battery cell 12 in a subsequent processing step S8, and in particular, enclosed by a casing 14. In a subsequent processing step S9, an electrolyte 16 for the battery 1 is injected into the casing 14, and parameters for an electrolyte injection coefficient E-in (as process-related data dP) are recorded. The casing 14 is then sealed, and the final manufacturing steps (not shown in detail) are carried out to complete the production of the battery 1.

[0050] Based on the aforementioned geometric data dG (as, md), the material-related data dM (x, y, yr) and the process-related data dP (Ed, Em, Er, E-in), each assigned via the corresponding identifier 8, the single-layer capacitance Cs is now calculated for each individual electrode 4s according to equation (i). Cs=Fc⋅as⋅md⋅x⋅(y−yr / 2) with Fc = Em · Er · Eh · Ed · E-in. The battery capacity C is then the sum of the individual layer capacitances Cs.

[0051] Preferably, the respective capacities of individual specimens of the battery 1 manufactured as described can be tested (i.e. by charging / discharging), and the results can be compared with those according to equation (i) in order to optimize the determination according to equation (i), and in particular to adjust the coefficients of the coefficient factor Fc.

[0052] Although the invention has been illustrated and described in detail by the preferred embodiment, the invention is not limited by the disclosed examples and other variations can be derived by the person skilled in the art without leaving the scope of protection of the invention. Reference symbol list 1 battery 2 Electrode foil 4s single electrodes 5 starting materials 5a electrochemically active material 6 Mixture 8 Identifier 10 electrode stacks 12 battery cells 14 case 16 Electrolyte as material-specific capacity C capacity Cs single-layer capacity dG geometric data dM material-related data dP process-related data Ed boundary area coefficient Eh humidity coefficient Em mixing coefficient The rolling density coefficient E-in electrolyte injection coefficient md active material density S1-S9 processing steps x length y width yr coating edge width

Claims

[1] Method for determining the capacity (C) of a battery (1), - wherein an identifier (8) is attached to each of a first plurality of electrode foils (2), - wherein a second plurality of individual electrodes (4s) is produced from the first plurality of electrode foils (2) in such a way that each individual electrode (4s) is identifiable at least batch-wise by means of the associated identifier (8), - wherein geometric data (dG) and / or material-related data (dM) and / or process-related data (dP) are recorded for the second plurality of individual electrodes (4s) during their production, and are assigned to the respective individual electrode (4s) based on the identifier (8) of the associated electrode foil (2), - wherein for each of the said individual electrodes (4s) a single-layer capacitance (Cs) is determined based on the respective geometric data (dG) and / or material-related data (dM) and / or process-related data (dP), and - wherein a capacity (C) of a battery (1) formed on the basis of the second plurality of single electrodes (4s) is determined on the basis of the associated single-layer capacities (Cs). [2] Method according to claim 1, wherein the capacity (C) of the battery (1) is determined by means of a sum of the respective single-layer capacities (Cs) of the second plurality of single electrodes (4s). [3] Method according to claim 1 or claim 2, - where geometric data (dG) include a length (x) and a width (y) and / or a coating thickness and / or an edge area coefficient (Ed), and / or - where material-related data (dM) include an active material density (md) and / or a material-specific capacity (as), and / or - where process-related data (dP) include a mixing coefficient (Em) and / or a rolling density coefficient (Er) and / or a coating edge width (yr) and / or a moisture coefficient (Eh). [4] Method according to claim 3, wherein for a particular single electrode (4s) - the length (x) and width (y) and / or the surface area coefficient (Ed) are recorded during a stacking process (S7) of single electrodes (4s) or immediately before it, and / or - the coating thickness is recorded during a coating process (S3) of the electrode foil or immediately afterwards. [5] Method according to claim 3 or claim 4, wherein for a relevant single electrode (4s) - the material-specific capacity (as) is determined based on a mixture (6) of components for the coating process (S3), and / or - the active material density (md) is recorded during the coating process (S3) or immediately afterwards. [6] Method according to any one of claims 3 to 5 wherein for a particular single electrode (4s) - the mixing coefficient (Em) is determined based on the mixture (6) of components for the coating process (S3), and / or - the coating edge width (yr) is measured during a coating process (S3) of the electrode foil or immediately afterwards, and / or - the rolling density coefficient (Er) is recorded during a rolling process (S4) of the coated electrode foil (2) or immediately afterwards. [7] Method according to any one of the preceding claims, wherein the battery (1) is formed on the basis of the second plurality of single electrodes (4s), and in this respect - the second plurality of individual electrodes (4s) is stacked in a stacking process (S7) to form an electrode stack (10), - the electrode stack (10) is enclosed in a shell (14), and - an electrolyte (16) is injected into the shell (14), wherein during said injection of the electrolyte (16) or immediately afterwards an electrolyte injection coefficient (E-in) is recorded, which is further process-related data (dP) assigned to the individual electrodes (4s) concerned, or which is assigned to the electrode stack (10). [8] Method according to one of the preceding claims, wherein the single-layer capacitance (Cs) for each individual electrode (4s) is determined on the basis of a linear relation of the associated geometric data (dG) and / or material-related data (dM) and / or process-related data (dP). [9] Method according to one of the preceding claims, wherein each individual electrode (4s) of the second plurality is produced from a separate electrode foil (2) of the first plurality. [10] Method according to one of the preceding claims, wherein a QR code and / or a barcode is applied as an identifier (8) on a protruding tab on the electrode foil (2) and / or on an uncoated recess of the electrode foil (2). [11] Method for optimizing a determination of the capacity (C) of a battery (1), wherein a capacity is determined for a plurality of batteries (1) according to the method of one of the preceding claims, wherein the capacity (C) of at least one of these batteries (1) is measured, and wherein at least one parameter is adjusted to determine a single-layer capacity (Cs) of the respective single electrodes (4s) based on the measured capacity (C).

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