Method for ageing-dependent diagnosis of a battery cell for an energy storage device for a motor vehicle, computer program and / or computer-readable medium, a data-processing device, and a motor vehicle

Abstract

The invention relates to a method for ageing-dependent diagnosis of a battery cell for an energy storage device for a motor vehicle, wherein the method comprises: detecting a relationship between a voltage difference and a charge state of the battery cell, wherein the voltage difference is defined by a charge open circuit voltage characteristic curve based on charging of the battery cell and a discharge open circuit voltage characteristic curve based on discharging the battery cell; determining a reference charge state on the basis of the relationship between the voltage difference and the charge state; and determining a diagnostic indicator for ageing-dependent diagnosis of the battery cell, taking into account the reference charge state and the relationship between the voltage difference and the charge state.

Description

[0001] Method for age-dependent diagnosis of a battery cell for an energy storage device for a motor vehicle, computer program and / or computer-readable medium, a data processing device and a motor vehicle

[0002] The present disclosure relates to a method for age-dependent diagnosis of a battery cell for an energy storage device for a motor vehicle. The disclosure also relates to a computer program and / or computer-readable medium, a data processing device, and a motor vehicle.

[0003] Such an energy storage device typically comprises a plurality of battery cells or cells connected in parallel and / or series, thus forming a high-voltage storage device, also known as a traction battery. The energy storage device is configured to discharge the battery cells and provide electrical energy to operate the motor vehicle and / or to provide electrical energy externally to the vehicle, for example, via a charging station. The energy storage device is configured to be supplied with electrical energy via the charging station and / or through recuperation during a journey in order to charge the battery cells of the energy storage device.

[0004] Accurate modeling of the high-voltage storage system is crucial for its safe, sustainable, and efficient use. Such high-voltage storage systems, or the cells they comprise, for example, lithium-ion cells, lose capacity over their service life, and their resistance increases, a process known as aging. This can ultimately reduce the range and performance of the vehicle when the cells are used in a motor vehicle. The capacity and resistance, or changes in them, can thus be incorporated into an estimate of the battery cell's condition.

[0005] For a state estimation to characterize the state of the cells and / or the energy storage device, an open-circuit voltage (OCV) and / or an open-circuit potential (OCP) are typically used, i.e., a relationship between a cell's open-circuit voltage or an electrode potential and the cell's state of charge. This can be used, in particular, to estimate the state of charge (SOC) and / or the aging or health status (SOH) of the cell and / or the energy storage device. The open-circuit voltage can also be used to determine a charging strategy for charging the energy storage device or the cells.

[0006] Methods for determining the state of health and for reconstructing a resting voltage characteristic are known from the state of the art (see CR Birkl, MR Roberts, E. McTurk, PG Bruce, DAHowey, „Degradation diagnostics for lithium ion cells“, Journal of Power Sources, Ausgabe 341 , 2017, Seiten 373-386; Matthieu Dubarry, Cyril Truchot, Bor Yann Liaw, „Synthesize battery degradation modes via a diagnostic and prognostic model“, Journal of Power Sources, Ausgabe 219, 2012, Seiten 204-216; Julius Schmitt, Mathias Rehm, Alexander Karger, Andreas Jossen, „Capacity and degradation mode estimation for lithium-ion batteries based on partial charging curves at different current rates“, Journal of Energy Storage, Ausgabe 59, 2023, Artikel 106517; Sijia Yang, Caiping Zhang, Jiuchun Jiang, Weige Zhang, Yang Gao, Linjing Zhang, „A voltage reconstruction model based on partial charging curve for state-of-health estimation of lithium-ion batteries“, Journal of Energy Storage, Ausgabe 35, 2021 , Seite 102271).

[0007] However, the cells may have a different cell chemistry and / or structure, which increases the complexity of modeling. For example, battery cells with lithium iron phosphate as the cathode material (so-called LFP cells) exhibit a comparatively flat open-circuit voltage characteristic in some sections, as well as a hysteresis of the open-circuit voltage characteristic.

[0008] Hysteresis describes the fact that the open-circuit voltages of the discharge voltage curve, or discharge-open-circuit voltage characteristic, differ from the charge voltage curve, or charge-open-circuit voltage characteristic. Thus, there is a closed-circuit voltage curve for charging and discharging, i.e., a so-called charging branch, which describes the open-circuit voltage curve during charging, and a discharge branch, which describes the open-circuit voltage curve during discharging. The difference between the "discharge branch" and the transition from the "discharge branch" to the "charge branch," or vice versa, represents a major modeling challenge, since this transition, or hysteresis, manifests itself differently depending on the history and boundary conditions. In addition, various aging effects generally alter the course of the open-circuit voltage characteristic.

[0009] In general, there are a variety of methods for determining states of charge, including those of LFP cells, e.g. Coulomb counting, methods using artificial intelligence (AI) and combined methods (see, for example, Yujie Wang, Jiaqiang Tian, ​​Zhendong Sun, Li Wang, Ruilong Xu, Mince Li, Zonghai Chen, “A comprehensive review of battery modeling and state estimation approaches for advanced battery management systems”, Renewable and Sustainable Energy Reviews, Volume 131, 2020, 110015, ISSN 1364-0321 , https: / / doi.Org / 10.1016 / j.rser.2020.110015).

[0010] Battery cells with silicon components in the anodes can also exhibit hysteresis, which can be even greater than the hysteresis of high-voltage storage devices with silicon-free electrodes (see Julius Schmitt, Markus Schindler, Andreas Oberbauer, Andreas Jossen; "Determination of degradation modes of lithium-ion batteries considering aging-induced changes in the half-cell open-circuit potential curve of silicon-graphite", Journal of Power Sources, Issue 532, 2022, page 231296). Furthermore, the silicon can become inactive with the ageing of the battery cell, and thus a change in the silicon component results in a change in hysteresis with the ageing of the cell. In cell chemistry with silicon-graphite anodes, the description and identification of aging, and thus the SOH estimation, are complicated by the comparatively rapid degradation of the silicon component and the different aging behavior of graphite and silicon active materials.

[0011] Hysteresis can negatively impact currently used state-of-charge determination methods, leading, for example, to inaccuracies in determining the state of charge. Thus, methods for reconstructing an OCV characteristic curve and determining the state of charge and / or state of health using known procedures may be difficult to apply to energy storage devices with LFP cells and / or cells with silicon-containing anodes. Measurement inaccuracies impact the quality of common state-of-charge and state-of-health determinations, since, for example, an incorrect state-of-charge determination cannot be compensated for using a clear OCV-SOC relationship, as is the case with other cell types. This can have a direct impact on the vehicle's range prediction and lead to an unexpected vehicle breakdown.In addition, incorrect state of charge determination can negatively impact the aging or health determination and can lead to premature activation of protective functions and / or reduced charging performance. Therefore, as well as the aging of the battery cells, recalibration of the state of charge and health determination is recommended to account for measurement inaccuracies and aging influences.

[0012] To recalibrate LFP cells, for example, it is known to fully charge the energy storage device and thus sample a unique voltage characteristic of the battery cells. However, it cannot be assumed without further ado that a user will fully charge the energy storage device for recalibration. Therefore, it cannot be guaranteed that recalibration is possible. However, recalibration should be possible for every user and every charging behavior.

[0013] Models and methods for determining the state of health use, for example, empirical functions dependent on the history of cell parameters, data-based algorithms, K1, and / or equivalent circuit diagrams. For example, knowledge of an open-circuit voltage characteristic is used to infer the current capacity value using a look-up table and thus determine information about the state of health. A fundamental problem, however, is the close coupling between the determination of the state of charge and the determination of the state of health. Thus, an accurate determination of the state of charge is difficult if the current state of health is unknown.

[0014] Patent application DE 102023 118 717.1, which was not yet published on the filing date of the present disclosure, describes a method for characterizing a hysteresis of a battery cell of an energy storage device for an electrically driven motor vehicle, the method comprising: charging the battery cell and detecting a charging cell voltage to model a charging voltage characteristic; temporarily discharging the battery cell and detecting a discharging cell voltage to model a discharging voltage characteristic; and determining the hysteresis between the charging voltage characteristic and the discharging voltage characteristic based on the charging cell voltage and the discharging cell voltage.

[0015] Against the background of this prior art, one object of the present disclosure is to provide a method suitable for enriching the prior art and improving at least the above-mentioned aspects of the prior art. In particular, the object of the disclosure is to enable a precise and reliable diagnosis of the state of health and / or the state of charge of a battery cell exhibiting a rest voltage characteristic hysteresis.

[0016] The problem is solved by the features of the independent claims. The subclaims contain further developments of the disclosure.

[0017] According to one aspect of the disclosure, the object is achieved by a method for age-dependent diagnosis of a battery cell for an energy storage device for a motor vehicle, the method comprising: detecting a relationship between a voltage difference and a state of charge of the battery cell, wherein the voltage difference is defined by a charging-open-circuit voltage characteristic curve related to charging of the battery cell and a discharging-open-circuit voltage characteristic curve related to discharging of the battery cell; determining a reference state of charge based on the relationship between the voltage difference and the state of charge; and determining a diagnostic indicator for age-dependent diagnosis of the battery cell, taking into account the previously determined reference state of charge and the previously detected relationship between the voltage difference and the state of charge.

[0018] The disclosure recognizes that it is possible to use the hysteresis behavior of battery cells as characteristic information, since the hysteresis changes with the cell's charge and health status. Thus, the battery cell's condition can be determined based on the hysteresis.

[0019] The relationship between the voltage difference and the battery cell's state of charge can be understood as a functional dependence on a parameter describing the hysteresis, namely the voltage difference between the charging resting voltage characteristic and the discharging resting voltage characteristic, and the state of charge. A reference state of charge can be determined in advance based on this relationship, as the relationship has a characteristic curve. The reference state of charge can be defined based on a characteristic feature of the curve. The relationship between the voltage difference and the state of charge depends on the cell's aging state.Based on the reference state of charge and the aging-dependent relationship between the voltage difference and the state of charge, the diagnostic indicator for the aging-dependent diagnosis of the battery cell can then be determined and optionally output, for example, from a software component and / or to a data storage device. The diagnostic indicator can provide direct information about the condition of the battery cell and / or its components and / or be further processed, for example, to perform recalibration.

[0020] The disclosure thus enables hysteresis effects to be used to diagnose the battery cell, for example, by linking the voltage difference with a corresponding state of charge to recalibrate a state of charge estimator for, for example, LFP cells but also other cell chemistries with open-circuit voltage hysteresis, to determine silicon degradation in cells with silicon-containing anodes, and / or to improve the SOH estimation. For the latter, for example, a parameter space or solution space for a measured partial voltage curve for reconstructing an open-circuit voltage characteristic of an aged cell based on half-cell potentials can be restricted with a given diagnostic indicator. The diagnostic indicator can be used as an additional boundary condition to achieve faster convergence and a higher probability of finding a global optimum in such a reconstruction.The disclosure can prevent premature activation of protective functions and / or limitation of charging performance due to incorrect aging determination.

[0021] Optionally, the reference state of charge is determined based on the voltage difference and a corresponding charge difference according to the relationship. In other words, the characterization of a hysteresis-related voltage difference and the reference state of charge is carried out based on the change in the hysteresis-related voltage difference at a start and end point of the charge input or the charge difference. It was recognized that a charge change by a charge difference and a corresponding change in the state of charge also result in a certain change in the voltage difference of the hysteresis. The change in the voltage difference and the corresponding charge difference form a tuple that can be characteristic of the state of the battery cell. The charge difference can be used to simultaneously determine a start state of charge and an end state of charge, each of which can be defined as the reference state of charge.The diagnostic indicator can be determined based on the charge difference and the change in the voltage difference.

[0022] Optionally, the battery cell is an LFP cell. It has been recognized that characteristic changes in hysteresis occur, particularly in LFP cells when new (beginning of life, BOL) but also during aging. Therefore, diagnosis based on hysteresis can be effectively achieved.

[0023] Optionally, the reference state of charge is determined based on an extremum and / or plateau of the relationship between the voltage difference and the state of charge. It has been recognized that hysteresis can typically exhibit a characteristic curve with one or more local extrema and / or a global extrema. In LFP cells, a global extrema in particular can be characteristic of the state of the cathode. In cells with silicon-containing anodes, one of the local extrema can be characteristic of the state of the anode. The reference state of charge can be defined as the position of the extremum on the state of charge axis. Optionally, the battery cell comprises a silicon-graphite anode. The battery cell thus comprises a silicon-containing anode.It was recognized that the hysteresis can be exploited to determine the silicon degradation and to improve the SOH estimation, because the hysteresis is comparatively large in the battery cell with the silicon-graphite anode and changes with aging due to the degradation of the silicon in the anode.

[0024] Optionally, the diagnostic indicator describes a position and / or, particularly in the case of silicon-containing anodes, a shift in the extreme value and / or plateau of the voltage difference. It was recognized that the relationship between the voltage difference typically exhibits a local minimum, which indicates the mechanisms of lithium ion incorporation into the active material of the anode, for example, the incorporation of the ions in graphite and silicon. However, with age, silicon degrades faster than graphite, which can lead to a shift in the extreme value. The same can apply to a slightly broadened extreme value, which can then be interpreted as a plateau. Alternatively or additionally, the diagnostic indicator characterizes the health status of the battery cell. It was recognized that the diagnostic indicator can indicate the health status of one of the electrodes and thus also of the battery cell.The diagnostic indicator can characterize the health status of a battery cell anode, particularly in the case of a silicon-graphite anode (see above). Alternatively or additionally, the diagnostic indicator can characterize a degradation mode of a battery cell anode. The diagnostic indicator can characterize a degradation mode of the anode as a parameter describing the degradation of the silicon-containing active material of the anode.

[0025] Optionally, the method comprises: recalibrating a state of charge estimator for determining the state of charge of the battery cell based on the diagnostic indicator. It was recognized that the diagnostic indicator can be used to recalibrate an estimate of the state of charge. Alternatively or additionally, the method comprises: determining an aging state of the battery cell, a state of health of an anode and / or a degradation mode of an anode based on the diagnostic indicator. It was recognized that the diagnostic indicator can in particular indicate a state of health and / or degradation mode of an electrode and can thus be taken into account when determining the aging state or state of health of the cell. According to one aspect of the disclosure, a computer program and / or a computer-readable medium is provided. The computer program and / or the computer-readable medium comprise instructions that are executed when the program orThe instructions by a data processing device cause the device to perform the method according to the disclosure and / or steps thereof. Optionally, the computer program and / or the computer-readable medium comprises instructions which, when the program or instructions are executed by a data processing device, cause the device to perform the method steps described as advantageous or optional in order to achieve an associated technical effect.

[0026] According to one aspect of the disclosure, a data processing device for a motor vehicle is provided. The data processing device is configured to perform the method described above. Optionally, the data processing device is configured to perform a method step described as advantageous or optional and / or to implement a method feature in order to achieve an associated technical effect.

[0027] According to one aspect of the disclosure, a motor vehicle comprising the data processing device described above is provided. Optionally, the data processing device of the motor vehicle and / or the motor vehicle is configured to perform a method step described as advantageous or optional and / or to implement a method feature in order to achieve an associated technical effect.

[0028] In the following, one embodiment is described with reference to the figures.

[0029] Fig. 1 schematically shows a motor vehicle according to one aspect of the disclosure;

[0030] Fig. 2 schematically shows a hysteresis of a battery cell associated with a method according to one aspect of the disclosure;

[0031] Fig. 3 shows schematically a relationship between a hysteresis-related voltage difference and a state of charge of a battery cell;

[0032] Fig. 4 shows schematically a relationship between a hysteresis-related voltage difference and a state of charge of a battery cell;

[0033] Fig. 5 schematically shows a flow diagram of a method according to one aspect of the disclosure; and

[0034] Fig. 6 shows a schematic representation of a computer program and / or computer-readable medium according to one aspect of the disclosure. Figure 1 schematically shows a motor vehicle 50 according to one aspect of the disclosure. For better illustration, Figure 1 is divided into two sections (A) and (B), wherein each of the sections (A) and (B) shows an embodiment of the motor vehicle 50. The following description applies, unless otherwise stated, to the respective motor vehicle 50 according to each of the sections (A) and (B). The motor vehicle 50 is a land vehicle. The motor vehicle 50 is a passenger car.

[0035] The motor vehicle 50 has an energy storage device 55 and an electric drive 52. The energy storage device 55 has a plurality of battery cells 56, which and their number are shown only schematically.

[0036] The energy storage device 55 or the battery cells 56 are configured to be supplied with electrical energy in order to charge the battery cells 56, i.e. to increase a state of charge SOC of the battery cells 56. The energy storage device 55 or the battery cells 56 are configured to provide electrical energy for operating the motor vehicle 50 and / or the electric drive 52, wherein the battery cells 56 are discharged, i.e. the state of charge SOC of the battery cells 56 decreases. During charging and discharging as well as over time, i.e. due to calendar effects, the battery cells 56 can age, i.e. the battery cells 56 can be characterized by a state of health SOH that changes over time and / or with the use of the energy storage device 55.

[0037] Each of the battery cells 56 has an anode 57, a cathode 58, and an electrolyte, along with an electrically insulating separator 59 between the anode 57 and cathode 58 (see schematic indexing of the battery cell 56 at the bottom left). The electrolyte is designed to transport charge carriers, in particular lithium ions. The battery cells 56 of the energy storage device 55 have a hysteresis H (see, for example, Figure 2).

[0038] The battery cell 56 according to section (A) is a battery cell 56 with lithium iron phosphate as the cathode material, i.e., a so-called LFP cell 56a. The cathode 58 comprises lithium iron phosphate.

[0039] The battery cell 56 according to section (B) comprises a silicon-graphite anode 57a, i.e., a silicon-containing anode 57. The anode 57 comprises graphite and silicon. The state of the silicon-graphite anode 57a can be described by a state of health SOH_A of the anode 57.

[0040] The motor vehicle 50 according to Figure 1 has a data processing device 51. The data processing device 51 is, for example, a battery control module and is configured to control and monitor the operation of the energy storage device 55. For this purpose, the data processing device 51 is configured, for example, to define a current profile with a current for charging the energy storage device 55 and to measure the cell voltage U of one of the battery cells 56 (see Figure 2).

[0041] Figure 1 also shows a charging station 91 and a vehicle-external network 90. ​​The charging station 91 and the motor vehicle 50 are designed to be connected to each other electrically and communicatively.

[0042] Energy storage device 55 for charging the battery cells 56 is supplied with electrical energy from the vehicle-external network 90 via the charging station 91. The charging station 91 can, for example, be a wall box or wall charging station and / or a public and / or private charging point.

[0043] For charging, the data processing device 51 can detect a charging request 75 for charging the battery cell 56 and transmit it to the charging station 91. The charging request 75 is specified, for example, by a user and / or by the manufacturer for diagnostic purposes. The charging request 75 is detected by a user interface (not shown) and / or via a communication interface 53 of the motor vehicle 50. Alternatively, the charging request 75 can be generated by the data processing device 51 itself for diagnostic purposes.

[0044] The data processing device 51 is configured to determine the hysteresis H (see Figure 2). For example, the data processing device 51 can measure relaxed cell voltages U before and / or after charging and / or discharging, or after the elapse of a relaxation time in which overvoltages can dissipate, which correspond to the open-circuit voltage of the battery cells 56 and / or approximate the open-circuit voltage. For example, the data processing device 51 is configured to carry out the method described in patent application DE 10 2023 118 717.1, which was not yet published on the filing date of the present disclosure, to determine the hysteresis H and / or the method described in patent application DE 10 2023 118 719.8, which was not yet published on the filing date of the present disclosure, to reconstruct a closed-circuit voltage characteristic curve.

[0045] The data processing device 51 is configured to determine the state of charge (SOC) and the state of deterioration (SOH) based on measured variables. For this purpose, the data processing device 51 is configured to implement a state of charge estimator 80 for determining the state of charge (SOC) and a state of deterioration estimator (not shown) for determining the state of deterioration (SOH).

[0046] The data processing device 51 is configured to determine a diagnostic indicator DI (see Figures 3 and 4). Furthermore, the data processing device 51 is configured to characterize the degradation modes relating to aging SOH using the diagnostic parameters LAM_NE, LAM_PE, LLI. The diagnostic parameter LAM_NE is a loss parameter of the active material of the negative electrode. The diagnostic parameter LAM_NE can be calculated as the quotient of the decrease in the capacity attributed to the negative electrode and the capacity attributed to the negative electrode in the reference state, for example, the new state. The diagnostic parameter LAM_PE is a loss parameter of the active material of the positive electrode. The diagnostic parameter LAM_PE can be calculated as the quotient of the decrease in the capacity attributed to the positive electrode and the capacity attributed to the positive electrode in the reference state.The diagnostic parameter LLI is a loss parameter of lithium. The diagnostic parameter LLI can be calculated as the quotient of the loss of the capacity attributed to lithium and the capacity attributed to lithium in the reference state.

[0047] The motor vehicle 50 or the data processing device 51 is configured to carry out the method 100 described with reference to Figure 5. For this purpose, the data processing device 51 has a data memory 54. The data memory 54 is configured to store readable information for reading and processing by the data processing device 51. For example, a relationship between the hysteresis H and a state of charge SOC (see Figures 3 and / or 4) for various health states SOH can be stored, for example as a look-up table.

[0048] Alternatively or additionally, the data processing device 51 can be connected to the

[0049] Communication interface 53 must be connected via communication technology.

[0050] The data processing device 51 can transmit information for evaluation to a vehicle-external server (not shown) or a backend via the communication interface 53, wherein the server is configured to carry out steps of the method 100 according to Figure 5.

[0051] Figure 2 schematically shows a hysteresis H of a battery cell 56 associated with a method 100 according to one aspect of the disclosure, i.e., a relationship between an open-circuit voltage OCV and a state of charge SOC of the battery cell 56. Such a battery cell 56 is described with reference to Figure 1. Figure 2 is described with reference to Figure 1.

[0052] Figure 2 illustrates the hysteresis behavior of the open-circuit voltage OCV of a battery cell 56 as a function of the state of charge SOC. Overvoltages are neglected in Figure 2 for better illustration.

[0053] The open-circuit voltage (OCV) shown generally increases with increasing SOC and decreases with decreasing SOC. The open-circuit voltage (OCV) exhibits a hysteresis H, i.e., it is protocol-dependent, or rather, dependent on the history of the SOC.

[0054] The voltage characteristic curve has a charging open-circuit voltage characteristic curve UKL and a discharging open-circuit voltage characteristic curve UKL. The charging open-circuit voltage characteristic curve UKL approximates and / or corresponds to an open-circuit voltage OCV of the battery cell 56 that can be achieved during charging. The discharging open-circuit voltage characteristic curve UKE approximates and / or corresponds to an open-circuit voltage OCV of the battery cell 56 that can be achieved during discharging. There is a difference referred to as hysteresis H between the charging open-circuit voltage characteristic curve UKL and the discharging open-circuit voltage characteristic curve UKE. The arrows illustrate the protocol dependence of the voltage characteristic curve: during charging, the charging open-circuit voltage characteristic curve UKL is sampled, and during subsequent discharging, the discharging open-circuit voltage characteristic curve UKE is sampled.At a minimum state of charge (SOC) of, for example, 0% and a maximum state of charge (SOC) of, for example, 100%, the charge-off-voltage characteristic curve (UKL) and the discharge-off-voltage characteristic curve (UKE) coincide at certain points. The difference between the charge-off-voltage characteristic curve (UKL) and the discharge-off-voltage characteristic curve (UKE) influences the performance of battery cell 56.

[0055] The hysteresis H, i.e., the charge-off-voltage characteristic UKL and the discharge-off-voltage characteristic UKE, can be sampled by repeated temporary charging and discharging, as illustrated by the arrows. The temporary discharging is carried out over a predetermined discharge state-of-charge range SOC-.

[0056] During charging, the charging open-circuit voltage characteristic UKL is first sampled and the state of charge SOC increases. Then, discharging occurs, whereby the state of charge SOC decreases through the state of charge range SOC-defined. During discharging, the discharge open-circuit voltage characteristic UKE is sampled. Charging occurs again, during which the charging open-circuit voltage characteristic UKL is again sampled and the state of charge SOC increases again. Charging and discharging are repeated until the diagnostic and / or charging process is completed and, optionally, a requested state of charge SOC is reached. Cell voltages U are measured, i.e. voltage points are sampled, on the discharge open-circuit voltage characteristic UKE and the charging open-circuit voltage characteristic UKL. The cell voltages U correspond to relaxed voltage points (i.e., open-circuit voltage OCV).For this purpose, a predetermined time, for example a relaxation time of approximately 1 hour, is provided after the temporary charging and / or discharging, after which the relaxed voltage point is recorded. During the relaxation time, overvoltages can be reduced so that the relaxed voltage point corresponds to a resting voltage of the battery cell 56 and / or approximates the resting voltage.

[0057] Instead of the state of charge SOC, another quantity can be plotted, such as a charge, which can be calculated based on the state of charge SOC and vice versa.

[0058] Figure 3 schematically shows a relationship 65 between a hysteresis-induced voltage difference DH and a state of charge SOC of a battery cell 56. Such a battery cell 56 and / or features thereof are described with reference to Figures 1 and 2. Figure 3 is described with reference to Figures 1 and 2.

[0059] Figure 3 illustrates the hysteresis H of an LFP cell 56a, which is characteristic of a state of health SOH (see section (A) of Figure 1). The open-circuit voltage OCV of such a battery cell 56 depends on the history as described with reference to Figure 2. The voltage difference DH changes with the state of charge SOC, as shown in Figure 3. The voltage difference DH at a specific state of charge SOC is the difference between the open-circuit voltage OCV of the charging branch and the open-circuit voltage OCV of the discharging branch, each at the state of charge SOC. The voltage difference DH has a global extremum 66 or maximum. The extremum 66 corresponds to a state of charge SOC of approximately 30%. The voltage difference DH defining the extremum 66 and the state of charge SOC at the extremum 66 can change with the precise cell balancing (tuning of the cathode 58 relative to the anode 57) and the aging of the anode 57 and cathode 58 and in particular the state of the cathode 58.

[0060] Figure 3 illustrates, with a vertically aligned double arrow, a voltage difference DH, which corresponds to a charge difference DQ, illustrated with a horizontally aligned double arrow. The charge difference DQ results from an initial state of charge SOC_A and a final state of charge SOC_E that differs from the initial state of charge SOC_A. The initial state of charge SOC_A, the final state of charge SOC_E, or a state of charge difference between the initial state of charge SOC_A and the final state of charge SOC_E is defined as a reference state of charge SOC_R. The reference state of charge SOC_R is thus determined or specified based on the relationship 65 between the voltage difference DH and the state of charge SOC by the voltage difference DH indicated by the vertically aligned double arrow.

[0061] A diagnostic indicator DI for the age-dependent diagnosis of the battery cell 56 is defined taking into account the reference state of charge SOC_R and the relationship 65 between the voltage difference DH and the state of charge SOC. In particular, the diagnostic indicator DI is defined by the voltage difference DH and the associated charge difference DQ and indicates an average gradient of the curve shown in Figure 3. The average gradient of the curve according to Figure 3 can vary with respect to the charge difference DQ and the initial state of charge SOC_A and changes with the ageing state SOH. The average gradient, based on a constant charge difference DQ for a given ageing state SOH, is stored in the data memory 54, for example, as a look-up table for various reference state of charge SOC_R.This allows the diagnostic indicator DI to be compared as the average increase in a charge difference DQ in the look-up table for an ageing state SOH assumed to be known in order to precisely determine the initial state of charge SOC_A, the final state of charge SOC_E or the state of charge difference and thus to recalibrate the state of charge estimator 80.

[0062] Figure 4 shows schematically a relationship between a hysteresis-related

[0063] Voltage difference DH and a state of charge SOC of a battery cell 56. Such a battery cell 56 and / or features thereof are described with reference to Figures 1 and 2.

[0064] Figure 4 is described with reference to Figures 1 and 2.

[0065] Figure 4 illustrates the hysteresis H characteristic of a battery cell 56 with a silicon-graphite anode 57a (see section (B) of Figure 1) for a state of health SOH. The open-circuit voltage OCV of such a battery cell 56 depends on the history as described with reference to Figure 2. The voltage difference DH changes with the state of charge SOG, as shown in Figure 4. The voltage difference DH at a specific state of charge SOG is the difference between the open-circuit voltage OCV of the charging branch and the open-circuit voltage OCV of the discharging branch, each at the state of charge SOC.

[0066] The voltage difference DH has a local extremum 66 or minimum. The extremum 66 is the first local minimum as the state of charge SOC increases and corresponds to a state of charge SOC of approximately 30%. The state of charge SOC at the extremum 66 defines the reference state of charge SOC_R, which can thus be determined based on the relationship 65 between the voltage difference DH and the state of charge SOC. The voltage difference DH defining the extremum 66 and the state of charge SOC at the extremum 66 can change with the precise cell balancing (tuning of the cathode 58 relative to the anode 57) and the aging of the anode 57 and cathode 58, and in particular with the condition of the silicon-graphite anode 57a.

[0067] A diagnostic indicator DI for the age-dependent diagnosis of the battery cell 56 is defined taking into account the reference state of charge SOC_R and the relationship 65 between the voltage difference DH and the state of charge SOC. The reference state of charge SOC_R is determined, particularly in a battery cell 56 with a silicon-graphite anode 57a, based on the extremum 66 and / or a plateau 67 of the relationship 65 between the voltage difference DH and the state of charge SOC.

[0068] The reference state of charge SOC_R can be determined at different aging states SOH and stored in the data memory 54 for comparison. The diagnostic indicator DI characterizes a position and / or shift S of the extremum 66 and / or plateau 67 at different aging states SOH. The prerequisite for this is that the state of charge SOC (i.e. the position) associated with the detected extremum 66 and / or plateau 67 for the different aging states can be precisely determined by another means. Alternatively, the necessary charge throughput until the extremum 66 and / or plateau 67 is reached from a constant reference point, for example a state of charge SOC of 0%, can be used. The diagnostic indicator DI characterizes, for example, the shift S of the extremum 66 and / or plateau 67 in the form of the charge throughput compared to a new state.Since the extreme value 66 is due to the degradation of silicon, the diagnostic indicator DI characterizes the state of health SOH of the battery cell 56, in particular of the anode 57. In particular, the diagnostic indicator DI defines a degradation mode LAM_NE relating to the anode 57 of the battery cell 56 in relation to the silicon content. It is assumed that the increased hysteresis H up to a state of charge SOC of approximately 30% is exclusively due to the lithiation or delithiation of the silicon content in the anode 57. The graphite content of the silicon-graphite anode 57a is inactive until then or only becomes active after complete lithiation or delithiation of the silicon content at an SOC > 30%. Accordingly, the decrease or compression of the hysteresis H for an SOC < 30% (see Figure 4) indicates the degradation mode LAM_NE in relation to the silicon content of the silicon-graphite anode 57a.

[0069] Figure 5 schematically shows a flowchart of a method 100 according to one aspect of the disclosure. The method 100 according to Figure 5 is a method 100 for aging-dependent diagnosis of a battery cell 56 for an energy storage device 55 for a motor vehicle 50. Such a motor vehicle 50, such an energy storage device 55, such a battery cell 56, and / or features thereof are described with reference to Figures 1 to 4. Figure 5 is described with reference to Figures 1 to 4.

[0070] The method 100 according to Figure 5 comprises: detecting 110 a relationship 65 between a voltage difference DH and a state of charge SOC of the battery cell 56, wherein the voltage difference DH is defined by a charging open-circuit voltage characteristic UKL related to charging of the battery cell 56 and a discharging open-circuit voltage characteristic UKL related to discharging of the battery cell 56. Such a relationship 65 and an associated hysteresis H are described with reference to Figures 2 to 4.

[0071] The method 100 according to Figure 5 comprises: determining 120 a reference state of charge SOC_R based on the relationship 65 between the voltage difference DH and the state of charge SOC (see description of Figures 3 and 4). The method 100 comprises: determining 130 a diagnostic indicator DI (see description of Figures 1, 3 and 4) for the age-dependent diagnosis of the battery cell 56, taking into account the reference state of charge SOC_R and the relationship 65 between the voltage difference DH and the state of charge SOC.

[0072] The determination 120 of the reference state of charge SOC_R is carried out, in particular in the case of an LFP cell 56a, on the basis of the voltage difference DH and a charge difference DQ associated with the relationship 65 (see Figure 3).

[0073] The reference state of charge SOC_R is determined, particularly in a battery cell 56 with a silicon-graphite anode 57a, based on an extremum 66 and / or plateau 67 of the relationship 65 between the voltage difference DH and the state of charge SOC (see Figure 4). The diagnostic indicator DI describes a position and / or a shift S of the extremum 66 and / or plateau 67.

[0074] The diagnostic indicator DI characterizes a state of health SOH of the battery cell 56, in particular of the anode 57 and / or a degradation mode LAM_NE concerning the anode 57 of the battery cell 56 based on the silicon content of the silicon-graphite anode.

[0075] The method 100 includes: recalibrating 140a a state of charge estimator 80 to determine the state of charge SOC of the battery cell 56 based on the diagnostic indicator DI.

[0076] The method 100 includes: determining 140b an aging state SOH of the battery cell 56 and / or a health state SOH_A of an anode 57 and / or a degradation mode LAM_NE of an anode 57 of the battery cell 56 based on the diagnostic indicator DI. The degradation mode LAM_NE is based on the silicon content of the silicon-graphite anode 57a.

[0077] As an optional feature of the method 100, it is ensured that there is sufficient charging and / or diagnostic time to detect 110 the relationship 65 between the voltage differences DH due to the hysteresis and the respective state of charge SOC and / or the charge difference DQ of the battery cell 56.

[0078] As an optional feature, the outside temperature and / or cell temperature is determined, at which the relationship 65 between the voltage difference DH and the state of charge SOC of the battery cell 56 is recorded. The outside temperature and / or cell temperature influences the hysteresis H and can be considered as an additional parameter in the look-up table.

[0079] The person skilled in the art will recognize that the method 100 according to Figure 5 can also be performed in a different order than that shown. In particular, it is possible for steps of the method 100 to be interchanged, shifted, and / or performed simultaneously.

[0080] An example for implementing the method 100 can be: A user of the motor vehicle 50 wishes the motor vehicle 50 to carry out a diagnostic mode relating to the voltage difference DH overnight. For this purpose, the motor vehicle 50 must remain plugged into a wall box, for example, for a specific time of at least 12 hours. First, a check is carried out to determine whether all boundary conditions (outside temperature, available time, known aging state SOH, etc.) are met. If the conditions are met, the method 100 starts and generates charge differences DQ and voltage differences DH using the OCV hysteresis charging method according to the patent application DE 10 2023 118 717.1, which was not yet published on the filing date of the present disclosure. Using the look-up table in the motor vehicle 50, the starting charge state SOC_S and the final charge state SOC_E orThe reference state of charge (SOC_R) can be determined. This state of charge information is used to update corresponding dependent functions in the motor vehicle 50. Alternatively or additionally, the position and / or shift S of the hysteresis curve can be used to infer degradation of the silicon content within the anode 57. This information is processed together with the relaxed voltage points and the charge differences DQ in order to infer the aging state (SOH) and the degradation modes. The aging state (SOH) and the diagnostic parameters LAM_NE, LAM_PE, LLI can be used to update corresponding functions in the motor vehicle.

[0081] Figure 6 shows a schematic representation of a computer program and / or computer-readable medium 200 according to one aspect of the disclosure. The computer program and / or computer-readable medium 200 comprises instructions (not shown) which, when the program or instructions are executed by a data processing device 51, cause the data processing device 51 to perform the method 100 and / or the steps of the method 100 according to Figure 5. The instructions can be present as program code in any code or in any language, in particular in a code suitable for controlling and / or monitoring motor vehicles 50 and / or their energy storage devices 55. The computer program and / or computer-readable medium 200 can be or comprise any digital data storage device, such as a USB stick, a hard disk, a CD-ROM, an SD card, or an SSD card.The computer program does not necessarily have to be stored on such a computer-readable storage medium, but can also be accessible via the Internet or otherwise.

[0082] Reference symbol (part of the description)

[0083] 50 motor vehicles

[0084] 51 Data processing device

[0085] 52 drive

[0086] 53 Communication interface

[0087] 54 data storage

[0088] 55 Energy storage device

[0089] 56 battery cells

[0090] 56a LFP cell

[0091] 57 Anode

[0092] 57a Silicon-graphite anode

[0093] 58 Cathode

[0094] 59 Separator

[0095] 65 Context

[0096] 66 Extremum

[0097] 67 Plateau

[0098] 75 loading request

[0099] 80 State of charge estimation

[0100] 90 vehicle-external network

[0101] 91 charging stations

[0102] 100 procedures

[0103] 110 Capturing a connection

[0104] 120 Determining a reference state of charge

[0105] 130 Determining a diagnostic indicator

[0106] 140a Recalibration

[0107] 140b Determining an aging state

[0108] 200 Computer program and / or computer-readable medium

[0109] DI Diagnostic indicator DH Voltage difference of hysteresis

[0110] DQ charge difference

[0111] H Hysteresis

[0112] LAM_NE diagnostic parameters, loss parameters of the negative electrode active material

[0113] LAM_PE diagnostic parameters, loss parameters of the active material of the positive electrode

[0114] LLI diagnostic parameters, lithium loss parameters

[0115] OCV Open-circuit voltage SOG State of charge

[0116] SOG- discharge state of charge range

[0117] SOC_A Initial state of charge

[0118] SOC_E Final state of charge

[0119] SOC_R Reference state of charge SOH Health status, health status of a battery cell

[0120] SOH_A Health status of an anode

[0121] U voltage, cell voltage

[0122] UKE discharge open-circuit voltage characteristic

[0123] UKL charging quiescent voltage characteristic

Claims

Claims 1. A method (100) for the age-dependent diagnosis of a battery cell (56) for an energy storage device (55) for a motor vehicle (50), the method (100) comprising: - detecting (110) a relationship (65) between a voltage difference (DH) and a state of charge (SOC) of the battery cell (56), wherein the voltage difference (DH) is defined by a charging rest voltage characteristic (UKL) related to charging of the battery cell (56) and a discharging rest voltage characteristic (UKE) related to discharging of the battery cell (56); - determining (120) a reference state of charge (SOC_R) based on the relationship (65) between the voltage difference (DH) and the state of charge (SOC); and - Determining (130) a diagnostic indicator (DI) for age-dependent diagnosis of the battery cell (56) taking into account the reference state of charge (SOC_R) and the relationship (65) between the voltage difference (DH) and the state of charge (SOC).

2. The method (100) according to claim 1, wherein - the determination (120) of the reference state of charge (SOC_R) is carried out on the basis of the voltage difference (DH) and a charge difference (DQ) associated with the relationship (65).

3. The method (100) of claim 1 or 2, wherein the battery cell (56) is an LFP cell (56a).

4. The method (100) according to claim 1, wherein - the reference state of charge (SOC_R) is determined based on an extremum (66) and / or plateau (67) of the relationship (65) between the voltage difference (DH) and the state of charge (SOC).

5. The method (100) of claim 4, wherein the battery cell (56) comprises a silicon-graphite anode (57a).

6. The method (100) according to claim 4 or 5, wherein the diagnostic indicator (DI) describes a position and / or a displacement (S) of the extremum (66) and / or plateau (67), the diagnostic indicator (DI) describes a state of health (SOH) of the battery cell (56) characterized, the diagnostic indicator (DI) characterizes a state of health (SOH_A) of an anode (57) of the battery cell (56) and / or the diagnostic indicator (DI) characterizes a degradation mode (LAM_NE) of an anode (57) of the battery cell (56).

7. The method (100) according to any one of the preceding claims, wherein the method (100) comprises: - recalibrating (140a) a state of charge estimator (80) for determining the state of charge (SOC) of the battery cell (56) based on the diagnostic indicator (DI) and / or - Determining (140b) an aging state (SOH) of the battery cell (56) and / or a health state (SOH_A) of an anode (57) and / or a degradation mode (LAM_NE) of an anode (57) based on the diagnostic indicator (DI).

8. Computer program and / or computer-readable medium (200) comprising instructions which, when the program or instructions are executed by a data processing device (51), cause the device (51) to carry out the method (100) and / or the steps of the method (100) according to one of claims 1 to 7.

9. Data processing device (51) for a motor vehicle (50), wherein the data processing device (51) is configured to carry out the method (100) according to one of claims 1 to 7.

10. Motor vehicle (50) comprising the data processing device (51) according to claim 9.

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