Method for diagnosing a battery cell

Abstract

A method for diagnosing a battery cell for an energy storage device for a motor vehicle, wherein the method comprises: detecting a request to change a state of charge of the battery cell from an initial state of charge to an end state of charge within a time period; determining a plurality of charging strokes corresponding to a difference between the end state of charge and the initial state of charge and an associated plurality of partial charging time periods corresponding to the time period, wherein the partial charging time periods each include a partial charging time, a relaxation time and an entropy measuring time; outputting a control signal to change the state of charge of the battery cell based on the plurality of charging strokes and the plurality of partial charging time periods, wherein a change in temperature is impressed in each case on the battery cell in the respective entropy measuring times of the partial charging time periods; and detecting a respective change in voltage associated with the respective change in temperature for the entropy measuring times of the partial charging time periods.

Description

[0001]23-3141 1 Method for diagnosing 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. The present disclosure relates to a method for diagnosing 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. Such an energy storage device typically comprises a plurality of battery cells or cells connected in parallel and / or in series and thus forms 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 supply electrical energy externally to the vehicle, for example, via a charging station.to provide, and 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. Accurate modeling of the high-voltage storage device is crucial for its safe, sustainable, and efficient use. Such a high-voltage storage device or the cells it comprises, for example, lithium-ion cells, lose capacity over their service life and their resistance increases, which is known as aging. As a result, when the cells are used in a motor vehicle, the range and performance of the vehicle can ultimately be reduced. The capacity and resistance, or changes therein, can thus be incorporated as information into an estimation of the battery cell's condition. For a condition estimation to characterize the condition of the cells and / or the energy storage device, aAn open-circuit voltage (OCV) and / or a half-cell potential (OCP) are used, i.e. a relationship between a cell's open-circuit voltage or an electrode potential and the cell's state of charge. This allows, in particular, the state of charge (SOC) and / or the aging or health state (SOH) of the cell and / or the energy storage device to be estimated. The open-circuit voltage characteristic can also be used to determine a charging strategy for charging the energy storage device or the cells. Information about a current state of health can be defined as the currently available capacity compared to the capacity when new. The state of health is of exceptional importance for the operating strategy of a vehicle, in particular for the design of the charging strategy for theSOC estimation and safety. However, a degradation of the state of health or aging exhibits a complex path dependency: the battery cell can age due to various mechanisms, for example, due to temperatures and / or power demands. Such mechanisms can be described by the construct of degradation modes (see CR Birkl, MR Roberts, E. McTurk, PG Bruce, DA Howey, Degradation diagnostics for lithium ion cells, Journal of Power Sources, Issue 341, 2017, pages 373-386). Degradation modes model the physico-chemical aging mechanisms and can be characterized by parameters that describe, for example, a loss of active material from an electrode and / or charge carriers such as lithium. These degradation modes can be used to estimate how the storage device will behave in the future and when the end of its service life will be reached. To characterize theThe development and provision of generalizable, accurate, and reliable estimation algorithms and methods is desirable for the assessment of battery health and aging. A promising methodology is a voltage curve reconstruction model based on measured half-cell potentials in a new state. Methods that use such a reconstruction refer to complete charging curves (see, for example, Matthieu Dubarry, Cyril Truchot, Bor Yann Liaw, "Synthesize battery degradation modes via a diagnostic and prognostic model," Journal of Power Sources, Issue 219, 2012, pages 204-216). Here, voltage curves of an aged cell are measured at low charging rates, so-called C-rates, where a C-rate is equal to a current divided by a nominal capacity, i.e., the current rate has the unit 1 / h or, in general, a rate and indicates reciprocally how quickly the battery is fully charged with a certain current. For example, aA cell is fully charged in half an hour at a C-rate of 2; at a C-rate of 0.5, a cell is fully charged in two hours. Half-cell potential curves measured in the new state are shifted and compressed to reconstruct the measured voltage curve of the aged cell in such a way that any error between an aged voltage curve reconstructed from the half-cell potential curves measured in the new state and the measured voltage curve of the aged cell is minimal. This can also be applied to partial charging curves and even at higher C-rates (see, for example, 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, Issue 59, 2023, Article 106517). The patent application DE 102022129208.8, which was not yet published on the filing date of the present disclosure, describes aAn alternative method, the so-called DeltaQ method, is used. It is then possible to use relaxed voltage points together with a summed charge throughput to reconstruct the voltage curve. This is a comparatively low-effort method for estimating the aging state, since by specifying the amount of charge introduced, the space of possible solutions for the voltage curve can be reduced to such an extent that a higher accuracy in the SOH estimation can be achieved. However, it can be more difficult to achieve accurate results in the degradation mode estimation. In this case, already available data can be used for the application of the DeltaQ method, for example, relaxed voltage points recorded when the vehicle is parked and / or after charging. A separate "reference charging mode" may thus be dispensable. Furthermore, it is clear from patent application DE, which was not yet published on the filing date of the disclosure.102023126708.6., it is known to control charging processes in such a way that a plurality of input data can be effectively obtained for the DeltaQ method. This allows the already available data set to be supplemented by a plurality of data points in order to improve the quality of the estimation or reconstruction. Another methodology is based on data-based SOH estimations. There are many possibilities for using correlative features that relate calculated variables to the state of health. Previous data-based methods preferably use features that can be extracted from current, voltage, and / or temperature. Rule-based methods also usually use a correlation between a change in the resting voltage characteristic and aging to estimate the state of health. 23-3141 4 It is also known from the prior art to use entropy or pseudo-entropy information to estimate the state of health.See Wu, Jossen; "Entropy-induced temperature variation as a new indicator for state of health estimation of lithium-ion cells"; Electrochimica Acta; Issue 276; 2018; pages 370-376. A quantity derived from the entropy-induced temperature change is used as a correlative quantity. Reversible entropy changes can also be used to determine an increase in resistance; see Singh, Tjahjowidodo, Boulon, Feroskhan; "Framework for measurement of battery state-of-health (resistance) integrating overpotential effects and entropy changes using energy equilibrium"; Energy; Issue 239; Part A; 2022. Page 121942. Furthermore, patent application DE 102023108451.8, which was not yet published on the filing date of the present disclosure, describes a control device and a method for determining a measure of the aging state of a battery cell, in other words, the use of pseudo-entropy information for SOH estimation. With the Delta-Q method,Despite their strengths, several parameter combinations, i.e., combinations of shifting and compressing the half-cell potentials, can lead to the same result. Similarly, depending on the aging path, a pseudo-entropy progression can lead to several health states. Both methods or approaches can thus have several mathematically correct solutions, which, however, do not represent the cell physico-chemically correctly. Against the background of this prior art, one object of the present disclosure is to provide a method that is 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 provide an improved and more physico-chemically accurate characterization of a battery cell of an energy storage device for a motor vehicle. This object is achieved by the features of the independent claims. The subclaims haveFurther developments of the disclosure to the content. According to one aspect of the disclosure, the object is achieved by a method for diagnosing a battery cell for an energy storage device for a motor vehicle, the method comprising: detecting a request to change a state of charge of the battery cell from an initial state of charge to a final state of charge within a period of time; determining a plurality of charging strokes corresponding to a difference between the final state of charge and the initial state of charge and an associated plurality of partial charging periods corresponding to the period of time, wherein the partial charging periods each comprise a partial charging time, a relaxation time, and an entropy measurement time; outputting a control signal for changing the state of charge of the battery cell based on the plurality of charging strokes and the plurality of partial charging periods, wherein the battery cell is assigned atemperature change is imposed; and recording a voltage change corresponding to the respective temperature change for the entropy measurement times of the partial charging periods. It was recognized that it is possible to combine information, for example, from a reconstruction of a resting voltage curve using relaxed voltage points and from a pseudo-entropy curve in such a way that a possible solution space for a resting voltage curve is restricted and thus the probability of finding a resting voltage curve that is both mathematically and physico-chemically correct is increased. For this purpose, an intelligent charging mode is proposed that can provide the necessary input variables for both types of information. In order to record predefined measuring points with relaxed voltages, a diagnostic, charging and / or discharging process terminated by the period can be used. It was recognized that various relaxed voltages can be approached as measuring pointsor can be adjusted if sufficient time is available for the process. For this purpose, it is proposed to subdivide the change in the state of charge into the majority of charging cycles and to provide a relaxation period between each charging cycle, during which the energy storage device or the cells are not charged, but rather relax into a resting state by reducing overvoltages and / or approximate the resting state by relaxation. This makes it possible to record a resting voltage or open-circuit voltage as the cell voltage. Several measuring points can thus be approached after the charging cycles, where the storage device is relaxed for a certain period of time over the relaxation period. These relaxed measuring points or ends of the relaxation periods are distributed over the amount of charge introduced and / or retrieved by changing the state of charge and meet the criteria for using the measuring points to diagnose theEnergy storage device, in particular for applying the DeltaQ method. In particular, the open-circuit voltage curve can be sampled over a state of charge or voltage range. These measurement points can thus be used to reconstruct the open-circuit voltage characteristic curve using the DeltaQ method and ultimately to estimate the 23-3141 6 state of health and / or the degradation modes. The number of measurement points and the SOC range can be selected such that a fit of the open-circuit voltage characteristic curve is possible with the smallest possible error. The method according to the disclosure thus offers a predefined, reproducible, comparable, and low-effort recording of these relaxed voltage points or measurement points. In addition, it is proposed to provide entropy measurement times between the charging cycles, during which the energy storage device or the battery cell is subjected to a temperature change.Temperature changes alter the thermodynamics in the battery cell, which is reflected in the voltage change associated with the temperature change. The temperature change and the voltage change can be used to determine entropy or pseudo-entropy information. By providing multiple entropy measurement times, an entropy curve can be determined. Finally, both pieces of information, i.e. the relaxed voltage points and the entropy curve, can be combined to limit the possible solution space for the open-circuit voltage curve and increase the probability of a physico-chemically correct solution for the open-circuit voltage curve. Optionally, within a partial charge period, the entropy measurement time is arranged after the partial charge time and after the relaxation time. It was recognized that after the relaxation time, overvoltages are at least partially reduced and thus a largely constant voltage isA well-defined starting point can be used to record the voltage change. Optionally, the state of charge is constant during the entropy measurement time. This ensures that the resulting voltage change is essentially due to the temperature change and thus to the thermodynamics of the battery cell. Alternatively or additionally, for the same reason, a charge input during the entropy measurement time is zero. Optionally, the respective entropy measurement time has a duration of up to 1 h and / or the temperature change is in the range of 15 °C to 50 °C. The optional duration of up to 1 h allows sufficient time for imposing the temperature change and, optionally, for reversing the temperature change, i.e., bringing about a second temperature change opposite to the 23-3141 7 temperature change. In addition, the period is so short that the temperature change can be imposed several times, for example, overnight.can be. The duration can be shorter than 1 hour and, depending on the application, longer than 1 hour. The temperature range of 15 °C to 50 °C enables a temperature change such that a sufficiently accurate voltage change occurs without causing damage and / or excessive aging of the battery cell due to excessively high temperatures. The temperature range can also be smaller or larger than specified, with the lower and / or upper limit of the temperature range being adaptable to the application. Optionally, the method comprises: determining, for the entropy measurement times of the partial charging periods, one piece of entropy information based on the respective temperature change and the voltage change. In this case, it was recognized that, in particular, separate entropy information can be determined for each of the entropy measurement times, for example from the ratio of the voltage change and the temperature change within the respective entropy measurement time.Since each entropy measurement period is scheduled after a charging cycle, the entropy information can represent an entropy curve that covers a range of charge states. Optionally, the method comprises: recording a cell voltage at each end of the relaxation time of one of the partial charging periods. The end of the relaxation time can thus be used as a measurement point. At the end of the relaxation time, a particularly reproducible and comparable sampling of the resting voltage is possible. Optionally, the method comprises: determining a voltage curve based on the cell voltage and the entropy information. In this case, a cell voltage and entropy information can be recorded in each of the partial charging periods. The cell voltage corresponds to a charge quantity. It was recognized that the charge or amount of charge can be determined as a charge quantity via the charging current and / or time. Based on the charge quantity, the charge state can be calculated andConversely. Patent application DE 102023108451.8 discloses a correlation between the state-of-charge-dependent pseudoentropy and the state of health. A change in the pseudoentropy can thus be directly mapped to a change in the state of health. Determining the voltage curve based on the cell voltage and the charge size can thus correspond to the DeltaQ method, with the entropy information or the entropy profile restricting a space of possible solutions for the voltage curve. 23-3141 8 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 which, upon execution of the program or instructions by a data processing device, cause the device to carry out 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 the instructions are executed by a data processing device, cause the data processing device to carry out the method steps described as advantageous or optional in order to achieve an associated technical effect. According to one aspect of the disclosure, a data processing device for a motor vehicle is provided. The data processing device is configured to carry out the method described above. Optionally, the data processing device is configured to carry out a method step described as advantageous or optional and / or to implement a method feature in order to achieve an associated technical effect. 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 carry out a method step described as advantageousor optionally to carry out a method step described and / or to implement a method feature in order to achieve an associated technical effect. In the following, one embodiment is described with reference to the figures. Fig. 1 schematically shows a motor vehicle according to one aspect of the disclosure; Fig. 2 schematically shows a charging curve for a method according to one aspect of the disclosure; Fig. 3 schematically shows a flow chart of a method according to one aspect of the disclosure; and Fig. 4 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. 23-3141 9 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 the number of which are only shown schematically.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, which changes over time and / or the use of the energy storage device 55. The battery cells 56 of the energy storage device 55 are characterized by a voltage curve 65, in particular an open-circuit voltage curve or rest voltage characteristic curveThe voltage curve 65 is a relationship between a voltage U and the state of charge SOC of the battery cell 56. The voltage curve 65 changes with the state of health SOH. 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 charging profile with a current I for charging the energy storage device 55 and to measure a cell voltage U of one of the battery cells 56. The data processing device 51 can thus charge the battery cells 56, in particular in a voltage-regulated manner. Figure 1 also shows a charging station 91 and a vehicle-external network 90. ​​The charging station 91 and the motor vehicle 50 are configured to be electrically and communicatively connected to one another.to be connected to each other. Thus, the energy storage device 55 can be supplied with electrical energy from the vehicle-external network 90 via the charging station 91 to charge the battery cells 56. 23-3141 10 The motor vehicle 50 or the data processing device 51 is configured to carry out the method 100 described with reference to Figure 3 and, for example, to define a charging curve 66 for charging the battery cells 56 or the energy storage device 55. Such a charging curve 66 is described with reference to Figure 2. Optionally, the method 100 described with reference to Figure 3 can be carried out, for example, with so-called bidirectional charging, wherein the state of charge SOC of the battery cells 56 decreases and energy from the energy storage device 55 is fed into the network 90 via the charging station 91. Alternatively or additionally, it is possible to use a diagnostic mode in which the state of charge SOC is measured before andaccording to method 100 is the same. For this purpose, the data processing device 51 according to Figure 1 is configured to detect a request 75 for a change in the state of charge SOC of the battery cell 56, for example, a charging request. The request 75 is specified, for example, by a user and / or by the manufacturer for diagnostic purposes. The request 75 is detected by a user interface (not shown) and / or via a communication interface (not shown). Alternatively, the request 75 can be created by the data processing device 51 itself for diagnostic purposes. The request 75 defines the change in the state of charge from an initial state of charge SOC_S to a final state of charge SOC_E within a time period TL (see Figure 2). The data processing device 51 is configured to output a control signal 76 for the scheduled change in the state of charge SOC of the battery cells 56. The control signal 76 isfor example, transmitted to the charging station 91 in order to be able to change the state of charge SOC. The data processing device 51 is configured to detect a cell voltage U and to determine a voltage curve 65, in particular an open-circuit voltage curve, based on entropy information EI or an entropy curve (see Figure 2), the cell voltage U and a charge quantity Q corresponding to the cell voltage U, for example a charge input DQ. Based on the voltage curve 65, the data processing device 51 can determine the state of health SOH. Additionally or alternatively, the data processing device 51 can determine parameters relating to aging mechanisms based on the voltage curve 65. 23-3141 11 Figure 2 schematically shows a charging curve 66 for a method 100 according to one aspect of the disclosure. Such a charging curve 66 can be determined by a data processing device 51 according to Figure 1 in order to change theState of charge SOC, for example, as a scheduled charge. Figure 2 is described with reference to Figure 1. Figure 2 shows in section (A) the charging curve 66 as a relationship between a cell voltage U and time t. A period of time TL is available for a charging process. A charging curve 66 with a solid line illustrates a charging process according to the prior art. While the comparatively long period of time TL is available, according to the prior art, the energy storage device 55 is charged in a comparatively short period of time. The energy storage device 55 is charged from an initial state of charge SOC_S or an initial voltage U_S to a final state of charge SOC_E or a final voltage U_E, in which or at which the energy storage device 55 remains after charging until the end of the period TL. The charging curve 66 for the scheduled charging according to the method 100 according toFigure 3 is illustrated in Figure 2 (A) by a dashed line. Charging is broken down into a plurality of charging strokes LH corresponding to the difference between the final state of charge SOC_E and the initial state of charge SOC_S, and a corresponding plurality of partial charging periods PTL corresponding to the time period TL. Each of the charging strokes LH defines a partial charge, during which the state of charge SOC increases between the initial state of charge SOC_S and the final state of charge SOC_E by a value corresponding to the charging stroke LH. The cell voltage U also increases. The sum of the plurality of charging strokes LH is essentially, apart from overvoltages, equal to the difference between the final state of charge SOC_E and the initial state of charge SOC_S, or equal to the difference between the final voltage U_E and the initial voltage U_S. Each of the partial charging periods PTL comprises a partial charging time LZ, a relaxation time RZ, and an entropy measurement time EZ. The illustration shows thePartial charging times LZ, relaxation times RZ, and entropy measurement times EZ are defined by vertically arranged, dotted lines. The partial charging time LZ, relaxation time RZ, and entropy measurement time EZ are indexed in the second partial charging period PTL; the indexing of the partial charging time LZ, relaxation time RZ, and entropy measurement time EZ has been omitted in the other partial charging periods PTL for clarity. 23-3141 12 In the partial charging periods PTL, charging, i.e., the supply of energy to the battery cells 56, takes place during the partial charging time LZ. During the partial charging time LZ, the state of charge SOC and the voltage U increase, with an intermediate state of charge SOC_Z being reached at the end of the partial charging period. This results in overvoltages. After the partial charging time LZ of one of the partial charging periods PTL, aRelaxation time RZ. The relaxation time RZ enables relaxation of the cells 56, i.e., a decay of the overvoltages and thus an approximation of a resting voltage value. Each of the relaxation times RZ or each partial charging period PTL has an end E of a relaxation time RZ, as schematically illustrated by a cross. At the end E of the relaxation time RZ, the voltage U is recorded for diagnosis and / or to approximate the resting voltage characteristic. The end E of the relaxation time RZ is thus a measuring point. The sum of the majority of the partial charging periods PTL is equal to the period TL. After the relaxation time RZ of one of the partial charging periods PTL, an entropy measurement time EZ follows within the partial charging period PTL, i.e., before the next partial charging period PTL or between the relaxation time RZ of the partial charging period PTL and the partial charging times LZ of the adjacent partial charging period PTL. Within a partial charging period PTL, theEntropy measurement time EZ is arranged chronologically after the partial charging time LZ and after the relaxation time RZ. The entropy measurement time EZ is illustrated by a circle with a dashed line. The state of charge SOC during the entropy measurement time EZ is constant, i.e. equal to the intermediate charge state SOC_C, or a charge input DQ during the entropy measurement time EZ is zero. The entropy measurement time EZ enables entropy information EI to be determined, see Figure 2 (B). Figure 2 (B) shows a dependence of the cell voltage U on the temperature T, and not as a function of time t as in Figure 2 (A). To determine the entropy information EI, a temperature change DT is impressed on the battery cell 56 in each of the entropy measurement times EZ of the partial charging periods PTL. The temperature change DT causes a voltage change DU. For the entropy measurement times EZ of the partial charging periods PTL, a value corresponding to the respective temperature change DT isVoltage change DU is recorded. Based on the respective temperature change DT and the voltage change DU for the entropy measurement times EZ of the partial charging periods PTL, an item of entropy information EI is determined: for example, as the ratio between the 23-3141 13 voltage change DU and the temperature change DT, i.e. EI = DU / DT, where EI is then a pseudo-entropy at a constant state of charge SOC. The temperature profile according to Figure 2 (B) is purely exemplary. Optionally, the temperature T can be controlled such that the temperature T of the battery cell 56 at the beginning of an entropy measurement time EZ is equal to the temperature T of the battery cell 56 at the end of the entropy measurement time EZ. The sum of the majority of the partial charging periods PTL is equal to the period TL. The charging strokes LH, the partial charging periods PTL, the entropy measurement times EZ and the relaxation times RZ of the partial charging periods PTL are equal to each other, with the exception of the last charging stroke LH and the last partial charging periodPTL and the last relaxation time RZ. The data processing device 51 according to Figure 1 is configured to determine the plurality of charging strokes LH and the plurality of partial charging periods PTL based on an optimization with a predetermined minimum number of partial charging periods PTL and / or the associated relaxation times RZ and entropy measurement times EZ as a secondary condition. For example, a user connects their motor vehicle 50 to the in-house AC wallbox as charging station 91 and indicates in request 75 that they will not need the vehicle again for another 6 p.m. The current state of charge SOC is 20% and is the initial state of charge SOC_S, and the full state of charge as the final state of charge SOC_E is to be reached upon departure. The charging period TL is therefore 18 p.m. The request 75 is made, for example, in the evening at 6 p.m., and the scheduled charging thus ends the following day at 12 p.m. The scheduled charging is therefore carried out overnight. A full charge according to the state of theTechnology would, for example, require 6 hours (depending on storage size and charging power). According to the method 100 of Figure 3, however, after each charging stroke LH of 20%, the voltage U is relaxed for, for example, at least 2 hours as a relaxation time RZ in order to be able to use the voltage U measurable at the end E of the relaxation time RZ later in the DeltaQ method. After the relaxation time RZ, a pseudo-entropy measurement is carried out for an entropy measurement time EZ of, for example, 1 hour, ie, at a constant state of charge SOC, a temperature change DT is induced, for example, the energy storage device 56 is heated, and a voltage change DU is measured. This results in entropy information EI = DU / DT. In addition, the total charging time is 6h+4*(2+1)h = 18h, where 6h are defined as the charging times LZ, four times 2h as relaxation times RZ, and four times 1h as the entropy measurement time EZ. The charging strokes LH and the times are purely exemplary andmay differ from the example shown. Figure 3 schematically shows a flow diagram of a method 100 according to one aspect of the disclosure. The method 100 according to Figure 3 is a method 100 for diagnosing a battery cell 56 for an energy storage device 55 for a motor vehicle 50. Such a motor vehicle 50 is described with reference to Figure 1 and a charging curve 66 for charging such an energy storage device 55 is described with reference to Figure 2. Figure 3 is described with reference to Figures 1 and 2. The method 100 comprises: detecting 110 a request 75 to change a state of charge SOC of the battery cell 56 from an initial state of charge SOC_S to a final state of charge SOC_E within a time period TL. The method 100 comprises: determining 120 a plurality of charging strokes LH corresponding to a difference between the final state of charge SOC_E and the initial state of charge SOC_S and an associated plurality of charging strokes LH corresponding to the period TLPartial charging periods PTL, where the partial charging periods PTL each comprise a partial charging time LZ, a relaxation time RZ, and an entropy measurement time EZ. Within a partial charging period PTL, the entropy measurement time EZ is arranged chronologically after the partial charging time LZ and after the relaxation time RZ. The state of charge SOC is constant during the entropy measurement time EZ, or a charge input DQ is zero during the entropy measurement time EZ. The respective entropy measurement time EZ has a duration of up to 1 h and / or the temperature change DT is in the range from 15°C to 50°C. The method 100 comprises: outputting 130 a control signal 76 for changing the state of charge SOC of the battery cell 56 based on the plurality of charging strokes LH and the plurality of partial charging periods PTL, wherein a temperature change DT is impressed on the battery cell 56 in the respective entropy measurement times EZ of the partial charging periods PTL. The method 100 comprises: detecting 135 for the entropy measurement timesEZ of the partial charging periods PTL, in each case a voltage change DU corresponding to the respective temperature change DT. 15 The method 100 comprises: determining 136, for the entropy measurement times EZ of the partial charging periods PTL, in each case an item of entropy information EI based on the respective temperature change DT and the voltage change DU. The method 100 comprises: detecting 140 a cell voltage U at a respective end E of the relaxation time RZ of one of the partial charging periods PTL. The method 100 comprises: determining 150 a voltage curve 65 based on the cell voltages U and the entropy information EI. The person skilled in the art will recognize that the method 100 according to Figure 3 can also be carried out in a different order than that shown. In particular, it is possible for steps of the method 100 to be swapped, shifted and / or carried out simultaneously. Figure 4 shows a schematic representation of a computer program and / or computer-readable medium 200 according toone 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 carry out the method 100 and / or the steps of the method 100 according to Figure 3. The instructions can be present as a program code in any code or in any language, in particular in a code that is suitable for controlling and / or monitoring motor vehicles 50 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 transmitted via the Internet or otherwisebe available. 23-3141 16 Reference symbols (part of the description) 50 Motor vehicle 51 Data processing device 52 Drive 53 Communication interface 55 Energy storage device 56 Battery cell 65 Voltage curve 66 Charging curve 75 Request 76 Control signal 90 Vehicle-external network 91 Charging station 100 Method 110 Detecting a request 120 Determining 130 Outputting a control signal 135 Detecting a voltage change 136 Determining entropy information 140 Determining a cell voltage 150 Determining a voltage curve 200 Computer program and / or computer-readable medium DU Voltage change DQ Charge input DT Temperature change E End of a relaxation time EI Entropy information EZ Entropy measurement time I Current 23-3141 17 LH Charging stroke LZ Partial charging time PTL Partial charging period Q Charging quantity RZ Relaxation time SOH State of health SOC State of charge SOC_E Final state of charge SOC_S Initial state of charge SOC_Z Intermediate charge state t Time T Temperature TL Period U Cell voltage, voltage U_SInitial voltage U_E Final voltage

Claims

23-3141 18 claims 1. A method (100) for diagnosing a battery cell (56) for an energy storage device (55) for a motor vehicle (50), the method (100) comprising: - detecting (110) a request (75) to change a state of charge (SOC) of the battery cell (56) from an initial state of charge (SOC_S) to a final state of charge (SOC_E) within a time period (TL); - determining (120) a plurality of charging strokes (LH) corresponding to a difference between the final state of charge (SOC_E) and the initial state of charge (SOC_S) and an associated plurality of partial charging periods (PTL) corresponding to the time period (TL), the partial charging periods (PTL) each comprising a partial charging time (LZ), a relaxation time (RZ), and an entropy measurement time (EZ);- outputting (130) a control signal (76) for changing the state of charge (SOC) of the battery cell (56) based on the plurality of charging strokes (LH) and the plurality of partial charging periods (PTL), wherein a temperature change (DT) is impressed on the battery cell (56) in each of the respective entropy measuring times (EZ) of the partial charging periods (PTL);and - detecting (135) for the entropy measurement times (EZ) of the partial charging periods (PTL) a voltage change (DU) corresponding to the respective temperature change (DT).

2. The method (100) according to claim 1, wherein within a partial charging period (PTL), the entropy measurement time (EZ) is arranged chronologically after the partial charging time (LZ) and after the relaxation time (RZ).

3. The method (100) according to claim 1 or 2, wherein the state of charge (SOC) is constant during the entropy measurement time (EZ) and / or a charge input (DQ) is zero during the entropy measurement time (EZ).

4. The method (100) according to one of the preceding claims, wherein the respective entropy measurement time (EZ) has a duration of up to 1 h and / or the temperature change (DT) is in the range from 15°C to 50°C.

5. The method (100) according to any one of the preceding claims, wherein the method (100) comprises:; 23-3141 19 - Determining (136) a piece of entropy information (EI) for the entropy measurement times (EZ) of the partial charging periods (PTL) based on the respective temperature change (DT) and the voltage change (DU).

6. The method (100) according to any one of the preceding claims, wherein the method (100) comprises: - detecting (140) a cell voltage (U) at a respective end (E) of the relaxation time (RZ) of one of the partial charging periods (PTL).

7. The method (100) according to claims 5 and 6, wherein the method (100) comprises: - determining (150) a voltage curve (65) based on the cell voltages (U) and the entropy information (EI).

8. A computer program comprising instructions which, when 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.Computer-readable medium (200) comprising a computer program with instructions which, when the computer program is 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.

10. 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.

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

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