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

Abstract

A method for scheduled charging for diagnosis of a battery cell for an energy storage device for a motor vehicle, wherein the method comprises: registering a charging request for scheduled charging of the battery cell from an initial state of charge to a final state of charge within a charging period; 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 charging period, wherein each of the partial charging periods comprises a partial charging time and a relaxation time; and emitting a control signal for scheduled charging of the battery cell on the basis of the plurality of charging strokes and the plurality of partial charging periods.

Description

[0001] Method for scheduled charging for diagnosing a battery cell for an energy storage device for a motor vehicle, computer program and / or computer-readable medium, data processing device, motor vehicle

[0002] The present disclosure relates to a method for scheduled charging 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 for a motor vehicle, 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] Information about a battery's current state of health can be defined as the currently available capacity compared to the capacity when new. The state of health is of utmost importance for a vehicle's operating strategy, particularly for the design of the charging strategy, for SOC estimation, and for safety. However, degradation of the state of health, or aging, exhibits a complex path dependency: the battery cell can age due to various mechanisms, for example, triggered by 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, the 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 its service life will be reached.

[0007] To characterize health and aging, the development and provision of generalizable, accurate, and reliable estimation algorithms and methods is desirable. A promising methodology is a voltage curve reconstruction model based on measured half-cell potentials in the new state.

[0008] Methods that use such 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, the voltage curves of an aged cell are measured at low charging rates, so-called C-rates. A C-rate is equal to a current divided by a nominal capacity, i.e. the current rate has the unit 1 / h or generally a rate and indicates inversely how quickly the battery is fully charged with a certain current. For example, a cell is fully charged in half an hour at a C-rate of 2; at a C-rate of 1 / 2, 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 an error between an aged voltage curve reconstructed on the basis of the half-cell potential curves measured in the new state and the measured voltage curve of the aged cell is minimal.

[0009] This optimization or error minimization 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).

[0010] The aforementioned state-of-the-art methods utilize time-resolved signals to reconstruct the voltage curve. Thus, these voltage curves contain a wealth of information about the qualitative voltage profile, and an accurate relative fit of the half-cell potential curves can be achieved. This can have a positive impact on the estimation of degradation modes.

[0011] However, there are multiple solutions at different SOH values ​​that minimize the error function or cost function. A characteristic of these methods is that for a given charging curve, there can be multiple local optima, each of which can lead to a local minimum error. This makes it impossible to reliably reconstruct the voltage curve unambiguously.

[0012] Patent application DE 102022 129 208.8, which was not yet published on the filing date of the present disclosure, describes an alternative method, the so-called DeltaQ method. This method makes it possible to use relaxed stress points together with a summed charge throughput to reconstruct the stress 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 stress 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.

[0013] 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 an alternative, low-complexity, and reliable estimation of the state of health. This object is achieved by the features of the independent claims. The subclaims contain further developments of the disclosure.

[0014] According to one aspect of the disclosure, the object is achieved by a method for scheduled charging for diagnosing a battery cell for an energy storage device for a motor vehicle, the method comprising: detecting a charging request for the scheduled charging of the battery cell from an initial state of charge to a final state of charge within a charging period; 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 charging period, wherein each of the partial charging periods comprises a partial charging time and a relaxation time; and outputting a control signal for the scheduled charging of the battery cell based on the plurality of charging strokes and the plurality of partial charging periods.

[0015] A scheduled charging process can be used to record predefined measuring points with relaxed voltages. The charging process is limited in time by the charging period. It was recognized that various relaxed voltages can be approached or set as measuring points if sufficient time is available for charging. To this end, it is proposed to divide the charging process into a plurality of charging strokes and to provide a relaxation period between each charging stroke during which the energy storage device or the cells are not charged but relax into a resting state by dissipating overvoltages and / or approximate the resting state through relaxation. This makes it possible to record a resting voltage or open-circuit voltage as the cell voltage.

[0016] In other words, instead of fully charging the energy storage device and leaving it in the fully charged state for an extended period, it is proposed to stretch the charging process to the available duration or charging period, whereby several measuring points can be approached after each charging cycle, where the storage device is relaxed for a certain period of time using the relaxation time. These relaxed measuring points or the ends of the relaxation times are distributed across the amount of charge introduced by charging and sufficiently meet the criteria for using the measuring points to diagnose the energy 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 resting voltage characteristic using the Delta-Q method and ultimately to estimate the health status and / or degradation modes.

[0017] It was recognized that the number of usable measurement points for the DeltaQ method is limited by boundary conditions: there should be at least a certain number of measurement points to enable a reliable fit of the open-circuit voltage characteristic, for example, 5 or more measurement points, in particular 10 measurement points; furthermore, the measurement points should be within a specific SOC range to enable a fit of the open-circuit voltage characteristic with the lowest possible error; and the period between point acquisitions should not be too long to avoid a change in the open-circuit voltage characteristic due to degradation between point acquisitions. These boundary conditions can be reproducibly met with scheduled charging.The method according to the disclosure thus offers a predefined, reproducible and comparable as well as low-effort recording of these relaxed stress points or measuring points and thus an enormous potential for the broad application of this method to motor vehicles.

[0018] Optionally, the sum of the majority of partial charging periods is less than or equal to the charging period. This ensures that the scheduled charging can be completed within the charging period. A user of the motor vehicle is thus unaffected with regard to the charging duration. The sum of the majority of partial charging periods can be less than the charging period, which can lead to the cells remaining at an end point of the last relaxation time. Alternatively or additionally, the sum of the majority of charging strokes is equal to the difference between the final state of charge and the initial state of charge. This ensures that the scheduled charging can take place from the initial state of charge to the final state of charge. A user of the motor vehicle is thus unaffected with regard to the requested final state of charge.

[0019] Optionally, the charging strokes, the partial charging periods, and / or the relaxation times of the partial charging periods are equal to one another. This makes it possible to arrange possible measuring points equidistant in time within the charging period and / or equidistant in charge-related terms between the initial state of charge and the final state of charge in order to be able to comprehensively sample the open-circuit voltage curve. In other words, the charging strokes are optionally equal to one another. Alternatively or additionally, the partial charging periods are equal to one another. Alternatively or additionally, the relaxation times of the partial charging periods are equal to one another. In particular, for example, a first charging stroke, a first partial charging period, a final charging stroke, and a final partial charging period can nevertheless be different in order to enable advantageous temporal and / or charge-related equidistance between the remaining charging strokes and / or partial charging periods.

[0020] Optionally, the method comprises outputting charging information relating to the execution of the scheduled charging and perceptible to a user of the motor vehicle. It has been recognized that scheduled charging can require a considerable amount of time for the use of the motor vehicle. Therefore, outputting the charging information can be advantageous for the use of the motor vehicle. The charging information can include an estimate of the end time of charging. The charging information can include a request for confirmation of the scheduled charging by the user.

[0021] Optionally, determining the plurality of charging strokes and the plurality of partial charging periods includes optimization with a predetermined minimum number of partial charging periods and / or the associated relaxation times as a constraint. It was recognized that the charging requirement and / or the difference between the initial state of charge and the final state of charge, as well as the charging period, allow for various options for selecting the charging strokes and defining the partial charging periods. Furthermore, it was recognized that it can be crucial for the quality of the diagnosis that a certain minimum number of measuring points are approached in order to enable a voltage curve to fit with the lowest possible error and / or that a certain minimum time is defined as the relaxation time in order to reliably sample the open-circuit voltage characteristic curve.

[0022] Optionally, the method includes 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.

[0023] Optionally, the method comprises determining a voltage curve based on the cell voltage and a charge quantity corresponding to the cell voltage. It has been recognized that during charging, the charge or charge quantity can be determined as a charge quantity via the charging current and / or time. The charge quantity can be calculated based on the charge quantity and vice versa. Determining the voltage curve based on the cell voltage and the charge quantity can correspond to the DeltaQ method. In other words, the above description can be summarized as follows, with reference to a specific embodiment that is described as not limiting the present disclosure: The disclosure relates to an application of the Delta-Q method for estimating SOH and degradation modes through scheduled AC charging processes. Prior art methods and algorithms use time-resolved signals to reconstruct the voltage curve.Thus, these voltage curves contain a great deal of information about the qualitative voltage profile, and a precise relative fit of the half-cell potential curves can be achieved. This can have a positive effect on the degradation mode estimation. However, there are multiple solutions at different SOH values ​​that minimize the cost function. The DeltaQ methodology, on the other hand, offers a low-effort way to estimate the SOH, since by specifying the amount of charge introduced, the space of possible solutions is already reduced, allowing for greater accuracy in the SOH estimation. Furthermore, the filtering of usable data points per vehicle is strict: There should be at least 10 data points, a specific SOC range should be included, the period of data acquisition should not be too far in the past, etc.A predefined, low-effort recording of these relaxed voltage points offers enormous potential for the widespread application of this method to vehicles. To record predefined, relaxed voltage points, a scheduled AC charging process can be used if sufficient time is planned. This means that instead of leaving the storage system in a fully charged state for an extended period, the charging process is stretched to the full, available duration by approaching several voltage points after specific charging pulses and relaxing the storage system there for a while. These points are now evenly distributed over the amount of charge introduced and sufficiently fulfill the criteria for using the points. These points can be used to reconstruct the OCV with the Delta-Q method and ultimately to estimate the SOH and the degradation modes. For example, a user plugs their vehicle into their home AC wallbox and states that they will not need the vehicle again for 18 hours.The current state of charge is 20%, and the full charge level should be reached upon departure. A normal full charge would take, for example, 6 hours, depending on the storage capacity and charging power. However, every 20%, a voltage value is relaxed for at least 3 hours, for example, so that it can be used later in the Delta-Q method. This results in a total charging time of 6 hours + 4 * 3 hours = 18 hours. The application example can be expanded or modified as required with regard to relaxation time, SOC sampling points, etc.

[0024] 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, when the program or instructions are executed 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.

[0025] 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.

[0026] 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.

[0027] In the following, one embodiment is described with reference to the figures.

[0028] 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;

[0029] Fig. 3 schematically shows a flow diagram of a method according to one aspect of the disclosure; and

[0030] Fig. 4 shows a schematic representation of a computer program and / or computer-readable medium according to one aspect of the disclosure.

[0031] Figure 1 schematically shows a motor vehicle 50 according to one aspect of the disclosure.

[0032] 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 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 to operate 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 are characterized by a state of health SOH that changes with time and / or the use of the energy storage device 55.

[0033] The battery cells 56 of the energy storage device 55 can be characterized by a voltage curve 65, in particular an open-circuit voltage curve. The 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.

[0034] 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. Thus, the data processing device 51 can charge the battery cells 56, in particular in a voltage-controlled manner.

[0035] 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 each other. This allows the energy storage device 55 to be supplied with electrical energy from the vehicle-external network 90 via the charging station 91 to charge the battery cells 56.

[0036] 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 to define a charging curve 66 for the scheduled charging of the battery cells 56 or the energy storage device 55. Such a charging curve 66 is described with reference to Figure 2. For this purpose, the data processing device 51 according to Figure 1 is configured to detect a charging request 75 for a scheduled charging of the battery cell 56. 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 via a user interface (not shown) and / or via a communication interface (not shown). Alternatively, the charging request 75 can be created by the data processing device 51 itself for diagnostic purposes.

[0037] The data processing device 51 is configured to output charging information 77 relating to the execution of the scheduled charging and perceivable by a user of the motor vehicle 50. The charging information 77 is output on a user interface of the motor vehicle 50, via the charging station 91, and / or via the communication interface, for example, on a terminal device of the user.

[0038] The charging request 75 defines the charging from an initial state of charge SOC_S to a final state of charge SOC_E within a charging period TL. The charging can be defined using the charging curve 66 (see Figure 2).

[0039] The data processing device 51 is configured to output a control signal 76 for the scheduled charging of the battery cells 56. The control signal 76 is transmitted, for example, to the charging station 91 in order to be able to carry out the scheduled charging.

[0040] 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 the cell voltage U and a charge quantity Q corresponding to the cell voltage U. 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.

[0041] 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 carry out a scheduled charging. Figure 2 is described with reference to Figure 1. Figure 2 shows the charging curve 66 as a relationship between a cell voltage U and the time t. A charging period 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 charging period TL is available, according to the prior art, the energy storage device 55 is charged in a comparatively short period of time.In this case, the energy storage device 55 is charged from an initial charge state SOC_S or an initial voltage U_S to a final charge state 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 charging period TL.

[0042] The charging curve 66 for the scheduled charging according to the method 100 of Figure 3 is illustrated in Figure 2 by a dashed line. The charging is subdivided into 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 charging period TL. Each of the charging strokes LH defines a partial charge in 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 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.

[0043] Each of the partial charging periods PTL comprises a partial charging time LZ and a relaxation time RZ. Charging, i.e., the supply of voltage 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. This creates overvoltages. After the partial charging time LZ of one of the partial charging periods PTL, a relaxation time RZ follows within the partial charging period PTL, i.e., before the next partial charging period PTL or between the partial charging times LZ of the adjacent partial charging periods PTL. The relaxation time RZ enables the cells 56 to relax, i.e., the overvoltages to decay and thus an approximation of an open-circuit voltage value. Each of the relaxation times RZ or each of the partial charging periods 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 measurement point. The sum of the majority of the partial charging periods PTL is equal to the charging period TL. The charging strokes LH, the partial charging periods PTL, 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, the last partial charging period PTL, and the last relaxation time RZ.

[0044] 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 as a secondary condition. For example, a user connects his motor vehicle 50 to the in-house AC wallbox as charging station 91 and indicates in the charging request 75 that he will not need the vehicle again for 18 hours. 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 should be reached upon departure. The charging period TL is therefore 18 hours. The charging 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 prior art would, for example,(depending on storage size and charging power) may require, for example, 6 hours. According to the method 100 shown in Figure 3, however, after each charging stroke LH of 20%, the voltage U is relaxed for, for example, at least 3 hours as a relaxation time RZ, in order to be able to later use the voltage U measurable at the end E of the relaxation time RZ in the DeltaQ method. This results in a total charging time of 6h + 4 * 3h = 18h, where 6h are allocated to the charging times LZ and four times 3h are defined as relaxation times RZ. The charging strokes LH and the times are purely exemplary and may differ from the example shown.

[0045] Figure 3 schematically shows a flowchart of a method 100 according to one aspect of the disclosure. The method 100 according to Figure 3 is a method 100 for scheduled charging 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.

[0046] The method 100 according to Figure 3 comprises: detecting 110 a charging request 75 for the scheduled charging of the battery cell 56 from an initial state of charge SOC_S to a final state of charge SOC_E within a charging period TL. The method 100 comprises: outputting 115 charging information 77 relating to the execution of the scheduled charging and perceivable by a user of the motor vehicle 50.

[0047] 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 partial charging periods PTL corresponding to the charging period TL, wherein each of the partial charging periods PTL comprises a partial charging time LZ and a relaxation time RZ.

[0048] The sum of the majority of the partial charging periods PTL is less than or equal to the charging period TL and / or the sum of the majority of the charging strokes LH is equal to the difference between the final state of charge SOC_E and the initial state of charge SOC_S.

[0049] The charging strokes LH, the partial charging periods PTL and / or the relaxation times RZ of the partial charging periods PTL are equal to each other.

[0050] The determination 120 of the plurality of charging strokes LH and the plurality of partial charging periods PTL comprises an optimization with a predetermined minimum number of partial charging periods PTL and / or the associated relaxation times RZ as a constraint.

[0051] The method 100 comprises: outputting 130 a control signal 76 for the scheduled charging of the battery cell 56 based on the plurality of charging strokes LH and the plurality of partial charging periods PTL.

[0052] 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.

[0053] The method 100 comprises: determining 150 a voltage curve 65 based on the cell voltage U and a charge quantity Q corresponding to the cell voltage U.

[0054] A 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 interchanged, shifted, and / or carried out simultaneously. Figure 4 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 device 51 to carry out the method 100 and / or the steps of the method 100 according to Figure 3.

[0055] 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 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 drive, 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.

[0056] Reference symbol (part of the description)

[0057] 50 motor vehicles

[0058] 51 Data processing device

[0059] 52 drive

[0060] 53 Communication interface

[0061] 55 Energy storage device

[0062] 56 battery cells

[0063] 65 Voltage curve

[0064] 66 Charging curve

[0065] 75 loading request

[0066] 76 Control signal

[0067] 77 Charging information

[0068] 90 vehicle-external network

[0069] 91 charging stations

[0070] 100 procedures

[0071] 110 Recording a loading request

[0072] 115 Output of charging information

[0073] 120 Determine

[0074] 130 Outputting a control signal

[0075] 140 Detecting a cell voltage

[0076] 150 Determining a voltage curve

[0077] 200 Computer program and / or computer-readable medium

[0078] E End of a relaxation time

[0079] I Current

[0080] LH loading hub

[0081] LZ partial charging time

[0082] PTL partial charging period

[0083] Q Load size

[0084] RZ Relaxation time SOH Health status

[0085] SOC state of charge

[0086] SOC_E discharge state

[0087] SOC_S Initial state of charge SOC Z Intermediate charge state t Time

[0088] TL charging period

[0089] U cell voltage, voltage

[0090] U_S initial voltage U_E final voltage

Claims

Claims 1. A method (100) for scheduled charging for diagnosing a battery cell (56) for an energy storage device (55) for a motor vehicle (50), the method (100) comprising: - detecting (110) a charging request (75) for the scheduled charging of the battery cell (56) from an initial state of charge (SOC_S) to a final state of charge (SOC_E) within a charging 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 charging period (TL), each of the partial charging periods (PTL) comprising a partial charging time (LZ) and a relaxation time (RZ); and - Outputting (130) a control signal (76) for the scheduled charging of the battery cell (56) based on the plurality of charging strokes (LH) and the plurality of partial charging periods (PTL).

2. The method (100) according to claim 1, wherein the sum of the plurality of partial charging periods (PTL) is less than or equal to the charging period (TL) and / or the sum of the plurality of charging strokes (LH) is equal to the difference between the final state of charge (SOC_E) and the initial state of charge (SOC_S).

3. Method (100) according to claim 1 or 2, wherein the charging strokes (LH), the partial charging periods (PTL) and / or the relaxation times (RZ) of the partial charging periods (PTL) are equal to one another.

4. Method (100) according to one of the preceding claims, wherein the method (100) comprises: - Outputting (115) charging information (77) relating to the execution of the scheduled charging and perceivable by a user of the motor vehicle (50).

5. The method (100) according to any one of the preceding claims, wherein determining (120) the plurality of charging strokes (LH) and the plurality of partial charging periods (PTL) comprises an optimization with a predetermined minimum number of partial charging periods (PTL) and / or the associated relaxation times (RZ) as a constraint.

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

7. The method (100) of claim 6, wherein the method (100) comprises: - Determining (150) a voltage curve (65) based on the cell voltage (II) and a charge quantity (Q) corresponding to the cell voltage (II).

8. A 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. A 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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