Method for determining the state of a battery cell of 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 determining the state of charge of a battery cell of an energy storage device for a motor vehicle, comprising: first excitation of the battery cell by a first current pulse separated in time from a first charge; detection of a first cell voltage as a response of the battery cell to the first current pulse; second charge of the battery cell by a charge input; second excitation of the battery cell by a second current pulse separated in time from the second charge; detection of a second cell voltage as a response of the battery cell to the second current pulse; determination of a first internal resistance based on the first cell voltage and the first current pulse and of a second internal resistance based on the second cell voltage and the second current pulse; and determination of a state of charge reference based on the charge input and a change in internal resistance between the first internal resistance and the second internal resistance.

Description

[0001] The present disclosure relates to a method for determining the state of a battery cell of an energy storage device for a motor vehicle.

[0002] 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 contain, such as 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 state (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] However, the cells may have a cell chemistry and / or structure that increases the complexity of modeling. For example, lithium iron phosphate cells used as battery cells (so-called LFP cells) exhibit a relatively flat open-circuit voltage characteristic curve in some sections, as well as a hysteresis of the open-circuit voltage characteristic curve. In addition, various aging effects generally alter the course of the open-circuit voltage characteristic curve. In particular, the relatively flat open-circuit voltage characteristic curve in some sections and the hysteresis of LFP cells have a negative impact on the currently used state determination methods and can, for example, lead to inaccuracies in determining the state of charge. This can have a direct impact on the vehicle's range prediction.In addition, the incorrect determination of the state of charge can have a negative impact on the determination of the age or state of health and can lead to premature activation of protective functions and / or to restrictions in the charging performance.

[0007] 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).

[0008] However, due to measurement noise and model errors, recalibration of parameters is necessary for the use of such methods. Without recalibration, for example, the determination of the battery cell's state of charge can be compromised by battery cell aging.

[0009] For recalibration, it is known to fully charge the energy storage device and thus sample the 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 of the SOC estimator is possible. However, recalibration should be possible for every user and every charging behavior.

[0010] Models and methods for determining the state of health use, for example, empirical functions based on the history of cell parameters, data-driven algorithms, AI, and / or equivalent circuits. Typically, knowledge of the state of charge and an open-circuit voltage characteristic are used to infer the current capacity value using a look-up table, for example, and thus determine information about the state of health.

[0011] A fundamental problem, however, is the close connection between determining the state of charge and the state of health. Thus, an accurate determination of the state of charge is difficult if the current state of health is unknown.

[0012] DE 10 2023 118 719.8, which was not yet published on the filing date of the present disclosure, describes a method for determining the internal resistance of a battery cell of an energy storage device for an electrically driven motor vehicle. The method comprises: charging the battery cell with a charging current; repeatedly temporarily lowering the charging current to a measuring charging current; measuring a cell voltage dependent on the charging current; and determining the internal resistance based on the cell voltage and the charging current. Based on the internal resistance, for example, a performance forecast for charging and / or providing electrical energy and / or a capacity and / or aging estimate can be made.

[0013] Patent application DE 10 2022 129 208.8, which was not yet published on the filing date of the present disclosure, describes an alternative method. According to this method, it is possible to use relaxed voltage points together with a summed charge throughput to reconstruct the voltage curve. This is a comparatively low-complexity 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.

[0014] 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 provide a determination of the state of a battery cell without necessarily requiring a value for a state of charge and / or state of health.

[0015] The problem is solved by the features of the independent claims. The subclaims contain further developments of the disclosure.

[0016] According to one aspect of the disclosure, the object is achieved by a method for determining the state of a battery cell of an energy storage device for a motor vehicle, the method comprising: first excitation of the battery cell by a first current pulse spaced apart in time from a first charging step; detecting a first cell voltage as a reaction of the battery cell to the first current pulse; second charging of the battery cell by a charge input; second excitation of the battery cell by a second current pulse spaced apart in time from the second charging step; detecting a second cell voltage as a reaction of the battery cell to the second current pulse; determining a first internal resistance based on the first cell voltage and the first current pulse and a second internal resistance based on the second cell voltage and the second current pulse;and determining a state of charge reference based on the charge input and an internal resistance change between the first internal resistance and the second internal resistance;

[0017] It was discovered that the internal resistance of a cell, especially an LFP cell, is particularly dependent on the state of charge. This relationship between the internal resistance and the state of charge is typically non-linear and can also vary across certain temperature ranges, allowing this relationship to be used for state estimation. Repeated excitation as part of a controlled, intelligent diagnostic or charging process to determine the two internal resistances and the introduced charge throughput makes it possible to detect a change in the cell's internal resistance in relation to the charge input. The information about the change in internal resistance and the introduced charge quantity can be correlated with the state of charge reference. This is made possible by the non-linear resistance curve versus the state of charge.

[0018] It was also discovered that after stimulating the battery cell with a current pulse, the internal resistance can be determined from the subsequent voltage response. Charging can precede each excitation to ensure that a battery cell exhibiting hysteresis delivers a consistent voltage response according to a charging-voltage characteristic. Spacing the charging and excitation phases allows for relaxation of the battery cell, allowing an approximation of the battery cell's open-circuit voltage and thus reliably determining the internal resistance through the excitation.

[0019] The second charging allows the excitations to be spaced apart such that different internal resistances are established, allowing the state of charge reference to be determined. The state of charge reference can reliably and accurately characterize the state of charge and / or define one or more parameters for a state of charge estimator.

[0020] The disclosure thus enables cell diagnosis independent of assumptions about the state of charge, a direct comparison between an open-circuit voltage characteristic and a state of charge, and without the need for prior recalibration of the state of charge estimator. Assuming a qualitatively equivalent resistance curve over the state of charge, the problem of the connection between a definition of the state of charge and the state of health can thus be circumvented.

[0021] The disclosure thus provides the possibility of inferring the state variables of the state of charge and thus also the state of health through an intelligent charging mode and knowledge of the internal resistance change over a specific charge input. The state of health is not estimated by correlating the increase in resistance and the decrease in capacity, but rather by extrapolating the amount of charge applied within the state of charge limits, which can be determined by the method.

[0022] Optionally, the battery cell is characterized by a charging-voltage characteristic curve with hysteresis, and the respective charging is carried out in such a way that the corresponding cell voltage corresponds to a charging cell voltage on the charging-voltage characteristic curve. It was recognized that LFP cells in particular exhibit hysteresis. Hysteresis describes the difference between the open-circuit voltages of the discharge voltage curve or discharge voltage characteristic and the charging voltage curve or charging voltage characteristic. There is therefore a closed-circuit voltage curve for each charging and discharging case, i.e. a so-called charging branch that describes the open-circuit voltage curve during charging, and a discharging branch that describes the open-circuit voltage curve during discharging. The difference between and the transition from the "discharging branch" to the "charging branch" can vary depending on the history and boundary conditions.To ensure that the first internal resistance and the second internal resistance are comparable, charging is performed. Thus, the cell voltage of the battery cell corresponds to the charging branch and is independent of any further history on the charging branch.

[0023] Optionally, the respective charging and the corresponding current pulse can be spaced apart in time such that the corresponding cell voltage corresponds to a resting voltage. By switching off the current after the current pulse and the temporal spacing, the voltage relaxes and moves toward the resting voltage characteristic. This enables particularly reliable detection of the internal resistance through the cell voltage in response to a current pulse.

[0024] Optionally, charging is performed with a constant charging current. This allows a predefined charge input to be achieved particularly effectively. In another embodiment, a variable charging current is also possible, in which case the charge input can then be calculated, for example, via an integral of the current over time.

[0025] Optionally, the state of charge reference includes a starting state of charge related to the first current positive and a final state of charge related to the second current pulse. It was discovered that the change in internal resistance correlates with the charge input to a specific pair of starting state of charge and final state of charge. Thus, the starting state of charge and final state of charge can be accurately and reliably determined based on the change in internal resistance with the charge input. It should be noted that no charge input occurs immediately before and after each current pulse, and the state of charge is therefore constant immediately before and after each current pulse.

[0026] Optionally, the method comprises: determining a state of health. It was recognized that the internal resistance and thus the change in internal resistance can change with the state of health, see also D. -I. Stroe, M. Swierczynski, SK Kær and R. Teodorescu, “Degradation Behavior of Lithium-Ion Batteries During Calendar Ageing-The Case of the Internal Resistance Increase,” in IEEE Transactions on Industry Applications, vol. 54, no. 1, pp. 517-525, Jan.-Feb. 2018, doi: 10.1109 / TIA.2017.2756026. This can also be used to determine an increase in internal resistance due to aging using previous series of measurements. Alternatively or additionally, the method comprises: recalibrating a state of charge estimator to determine the state of charge of the battery cell. It was recognized that the state of charge estimator can have parameters for determining the state of charge.The state of charge reference can be used to adjust the parameters according to aging and thus recalibrate the state of charge estimator.

[0027] Optionally, the method comprises checking a diagnostic period, a charging request, and / or an initial state, wherein the initial state is defined by a cell temperature and / or a cell voltage. It has been recognized that the method may take a comparatively long time, for example, to reach the charging threshold, to relax the cell voltage to a resting voltage, to relax the cell voltage in response to one of the current pulses, and / or, during the second charging, to introduce the charge. The internal resistance and thus the method depend on the cell temperature, which can be taken into account. The cell voltage can provide information about the state of the cell with regard to hysteresis, for example, whether the cell is already behaving according to the charging threshold. In this case, the first charging step could be dispensable and / or shortened.

[0028] In other words, the above description can be summarized as follows, with reference to a specific embodiment that is described as non-limiting for the present disclosure: The disclosure relates to a Delta-R method for determining the state of LFP storage devices. The core idea, however, can be outlined as follows: a controlled, intelligent charging process is carried out to determine two internal resistance values ​​and the entered charge throughput, e.g., by applying the method according to DE 10 2023 118 719.8 for determining internal resistance during AC charging or a diagnostic mode during a rapid charging process. Relaxed, defined voltage values ​​can also be generated using the Delta-Q charging method (DE 10 2022 129 208.8). The information about the increase in internal resistance and the entered charge quantity can be correlated with the SOC_start value. This is made possible by the non-linear resistance curve across the SOC.Knowledge of the SOC allows for recalibration of the SOC estimator and, through extrapolation, an SOH estimate. For example, a user wants their vehicle to run the “Delta-R diagnostic mode” overnight. For this to happen, the vehicle must remain plugged into the wallbox at home for a certain period of time (e.g., at least 12 hours). The algorithm first checks whether all boundary conditions (outside temperature, available time, etc.) are met. If the conditions are met, the Delta-R method starts and generates a value pair consisting of Delta_R = R_2 - R_1 and Delta_Q. A look-up table in the vehicle can be used to determine the starting and ending SOC for this specific Delta-R value. By combining the SOC information with the entered charge quantity Delta-Q, the current SOH can also be determined. SOH and SOC information are used to update or recalibrate dependent functions in the vehicle.

[0029] 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.

[0030] 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.

[0031] 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.

[0032] 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. Figure 2 shows a schematic diagram of a voltage characteristic of a battery cell with hysteresis; Fig. 3 schematically shows a current profile for performing a method according to an aspect of the disclosure and an associated cell voltage; Fig. 4 shows a detail of the cell voltage according to Fig. 3; Fig. 5 shows a dependence between a state of charge and a change in internal resistance over a charge input; Fig. 6 schematically shows a flow diagram of a method according to one aspect of the disclosure; and Fig. 7 shows a schematic representation of a computer program and / or computer-readable medium according to one aspect of the disclosure.

[0033] Fig. 1 schematically shows a motor vehicle 50 according to one aspect of the disclosure. The motor vehicle 50 is a land vehicle. The motor vehicle 50 is a passenger car.

[0034] 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.

[0035] 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.

[0036] Each of the battery cells 56 has an anode, a cathode, and an electrolyte (not shown). For example, the battery cell 56 is a lithium iron phosphate cell. The cathode comprises lithium iron phosphate, the anode comprises graphite with embedded lithium, and the electrolyte is suitable for transporting charge carriers, in particular lithium ions. The battery cells 56 of the energy storage device 55 have a hysteresis H (see, for example, Fig. 2).

[0037] The motor vehicle 50 according to Fig. 1 comprises 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 generate a current profile (see Fig. 3) with a current I and to measure the cell voltage U of one of the battery cells 56 (see Fig. 3 to 5).

[0038] Fig. 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. Thus, the energy storage device 55 for charging the battery cells 56 can be supplied with electrical energy from the vehicle-external network 90 via the charging station 91. The charging station 91 can be, for example, a wall box or wall charging station and / or a public and / or private charging point.

[0039] 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. The charging can be a partial charge, wherein the partial charge is selected such that the hysteresis H can be classified as insignificant, i.e., the partial charge is carried out such that the voltage U of the battery cell 56 corresponds to a characteristic charging load (see Fig. 2). Charging can then be carried out using a comparatively slow charging rate of, for example, C / 3, i.e., at a charging rate at which the energy storage device 55 would be fully charged in 3 hours.

[0040] The data processing device 51 is configured to execute a state of charge estimator 80. The state of charge estimator 80 is configured to determine the state of charge (SOC). For this purpose, measurement data and / or information relating to the battery cells 56 can be transmitted to the state of charge estimator 80.

[0041] The motor vehicle 50 or the data processing device 51 is designed to process the data relating to Fig. 6. 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 a change in internal resistance DRi and a charge entry DQ can be stored in the data memory 54, for example as a look-up table.

[0042] Alternatively or additionally, the data processing device 51 can be connected to the communication interface 53 for communication purposes. Via the communication interface 53, the data processing device 51 can transmit information for evaluation to a vehicle-external server (not shown) or a backend, wherein the server is configured to carry out steps of the method 100 according to Fig. 6 to be carried out.

[0043] Fig. Figure 2 shows a schematic diagram of a voltage characteristic of a battery cell 56 with hysteresis H, i.e. a relationship between a voltage U and a state of charge SOC. Such a battery cell 56 is shown in relation to Fig. 1 described. Fig. 2 is made with reference to Fig. 1 described.

[0044] Fig. 2 illustrates the hysteresis behavior of the voltage U of a battery cell 56 as a function of the state of charge SOC, for example for battery cells 56 designed as LFP cells. For better illustration, overvoltages are neglected in the description.

[0045] The voltage U shown generally increases with increasing SOC and decreases with decreasing SOC. The voltage U exhibits a hysteresis H, i.e., it is protocol-dependent, or rather, dependent on the history of the SOC.

[0046] The voltage characteristic curve has a charging voltage characteristic curve UKL and a discharging voltage characteristic curve UKE. The charging voltage characteristic curve UKL approximates and / or corresponds to an open-circuit voltage characteristic curve of the battery cell 56 that can be achieved during charging. The discharging voltage characteristic curve UKE approximates and / or corresponds to an open-circuit voltage characteristic curve of the battery cell 56 that can be achieved during discharging. There is a difference referred to as hysteresis H between the charging voltage characteristic curve UKL and the discharging voltage characteristic curve UKE. The arrows illustrate the protocol dependence of the voltage characteristic curve: during charging, the charging voltage characteristic curve UKL is sampled, and during subsequent discharging, the discharging 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 charging voltage characteristic curve (UKL) and the discharging voltage characteristic curve (UKE) coincide at certain points. The difference between the charging voltage characteristic curve (UKL) and the discharging voltage characteristic curve (UKE) influences the performance of battery cell 56.

[0047] 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.

[0048] Fig. Fig. 3 schematically shows a current profile, i.e. a current I for charging a battery cell 56 as a function of a time t, for carrying out a method 100 according to an aspect of the disclosure and an associated cell voltage U. Such a battery cell 56 and its features are described with reference to Fig. 1 and Fig. 2 described. Fig. 3 is made with reference to Fig. 1 and Fig. 2 described.

[0049] The current profile and the cell voltage U comprise a plurality of sections: First, a first charging 105 of the battery cell 56 takes place.

[0050] A first loading 105 takes place according to the exemplary Fig. 3 with a constant current I in order to achieve a sufficient charge input into the cell 56 and thus ensure that a charging-voltage characteristic curve UKL is achieved. The charge input for the first charging 105 can depend on the history of the battery cell 56, the current and / or the temperature T. The cell voltage U increases. The state of charge SOC increases from an initial state of charge SOC_S and the cell voltage U becomes independent of the history of the battery cell 56 before the first charging 105. The cell voltage U therefore corresponds to the charging-voltage characteristic curve UKL.

[0051] After the first charge 105, a first charging pause 106 occurs. During the first charging pause 106, the current I is zero and the cell voltage U relaxes to an open-circuit voltage OCV corresponding to the state of charge SOC. The charging pause 106, or relaxation time, can be, for example, one hour.

[0052] After the first charging pause 106, a first excitation 110a of the battery cell 56 occurs by a first current pulse IP1. The first charging 105 and the first current pulse IP1 are separated in time by the first charging pause 106. The first current pulse IP1 has, for example, a duration of a few seconds and / or less than one second.

[0053] After the first excitation 110a, a first cell voltage U1 is detected 110b as a reaction of the battery cell 56 to the first current pulse IP1. In this case, the cell voltage U initially rises in response to the first current pulse IP1 and then falls again. The drop in the cell voltage U is detected as the first cell voltage U1 (see also Fig. 4). During the detection 110b, the current I is zero and the cell voltage U relaxes to an open-circuit voltage OCV corresponding to the state of charge SOC. Due to the first charging 105, the first cell voltage U1 corresponds to a charging cell voltage UL1 according to the charging voltage characteristic UKL. The information of the voltage response allows a resistance value for a first internal resistance Ri1 to be deduced (see description of Fig. 4)

[0054] After detecting 110b the first cell voltage U1, a second charging 115 of the battery cell 56 takes place by a charge input DQ. The charging 115 takes place with a constant charging current I. This increases the state of charge SOC of the battery cell 56. The cell voltage U corresponds to the charging-voltage characteristic curve UKL.

[0055] After the second charge 115, a second charging pause 116 occurs. During the second charging pause 116, the current I is zero and the cell voltage U relaxes to an open-circuit voltage OCV corresponding to the state of charge SOC, which is higher than after the first charge 105. The duration of the second charging pause 116 should be equal to the duration of the first charging pause 106 in order to establish as similar a reference as possible.

[0056] After the second charging pause 116, a second excitation 120a of the battery cell 56 occurs by a second current pulse IP2. The second charging 115 and the second current pulse IP2 are separated in time by the second charging pause 116. The second current pulse IP2 has, for example, a duration of a few seconds and / or less than one second. The respective currents I of the first current pulse IP1 and the second current pulse IP2 can be equal to or different from one another. The respective currents I should be equal to improve comparability of the internal resistances Ri1, Ri2.

[0057] After the second excitation 120a, a detection 120b of a second cell voltage U2 takes place as a reaction of the battery cell 56 to the second current pulse IP2. In this case, the cell voltage U initially rises in response to the second current pulse IP2 and then falls again. The drop in the cell voltage U is detected as the second cell voltage U2 (see also Fig. 4). During the detection 120b, the current I is zero and the cell voltage U relaxes to an open-circuit voltage OCV corresponding to the state of charge SOC. Due to the second charging 115, the second cell voltage U2 corresponds to a charging cell voltage UL2 according to the charging voltage characteristic UKL. The information of the voltage response allows a resistance value for a second internal resistance Ri2 to be deduced (see description of Fig. 4). After the second charging 115 or the second excitation 120a, the state of charge SOC of the battery cell is equal to a final state of charge SOC_E.

[0058] The current profile and the cell voltage U according to Fig. 3 are part of a diagnosis of battery cell 56. The aforementioned sections or steps require a diagnostic time TD. The diagnostic time TD thus comprises the duration of the first charging 105, the first pause 106, the first excitation 110a, the detection 110b, the second charging 115, the second pause 116, the second excitation 120a, and the second detection 120b.

[0059] Fig. 4 shows a detail of the cell voltage U according to Fig. 3. Fig. 4 is made with reference to Fig. 3. This shows Fig. 4 the decay of the cell voltage U as a function of time t after one of the current pulses IP1, IP2.

[0060] Fig. 4 illustrates a determination of the internal resistance of the battery cell 56 or the energy storage device 55 by excitation 110a, 120a with a defined pulse current pulse IP1, IP2. The internal resistance Ri1, Ri2 is obtained by Ohm's law. The following applies to the first internal resistance Ri1 = dU / dl = ABS(U1(t0+dt) - U1(t0)) / IP1, where ABS() is the absolute value function, dU is a voltage difference of the first cell voltage U1 during decay starting from a reference time t0 at a maximum first cell voltage U1 over a time difference dt, and where the current difference dl is defined by the first current pulse IP1. The current I of the first current pulse IP1 is also denoted by IP1. The first internal resistance Ri1 is therefore the voltage response to the first current pulse IP1.

[0061] Analogously, the second internal resistance Ri2 = dU / dl = ABS(U2(t0+dt) - U2(t0)) / IP2 applies, where dU is a voltage difference of the second cell voltage U2 during decay, starting from a reference time t0 at a maximum first cell voltage U1 over a time difference dt, and where the current difference dl is defined by the second current pulse IP2. The current I of the second current pulse IP2 is also denoted by IP2. The second internal resistance Ri2 is therefore the voltage response to the second current pulse IP2.

[0062] Fig. Figure 5 shows a dependency between a state of charge SOC, in particular an initial state of charge SOC_S, and an internal resistance change DRi over a charge input DQ. The dependency according to Fig. 5 refers to a battery cell 56 as described with reference to Fig. 1 to 4 described. Fig. 5 is made with reference to Fig. 1 to 4 described.

[0063] Such a dependency can, for example, be stored as a look-up table in the data memory 54 (see Fig. 1) and / or be retrievable for the data processing device 51. The dependency shows that the initial state of charge SOC_S can be determined based on an internal resistance change DRi, which is equal to the difference between the first internal resistance Ri1 and the second internal resistance Ri2, and the charge input DQ. The quotient of the internal resistance change DRi and the charge input DQ is proportional to the initial state of charge SOC_S. The method 100 according to Fig. 3 and Fig. 6 thus enables the determination of the internal resistance change DRi and the charge input DQ, and thus the initial state of charge SOC_S. The same applies to the final state of charge SOC_E (not shown). The initial state of charge SOC_S and the final state of charge SOC_E, or their difference, are a state of charge reference SOC_R.

[0064] Fig. Figure 5 illustrates that the nonlinear internal resistance curve over the state of charge (SOC) can be used to determine the initial state of charge (SOC_S) using the internal resistance information. Furthermore, the nonlinear internal resistance curve over the state of charge (SOC) can be used to determine the final state of charge (SOC_E) using the internal resistance information (not shown).

[0065] Fig. 6 schematically shows a flow diagram of a method 100 according to one aspect of the disclosure. The method 100 according to Fig. 6 is a method 100 for determining the state of a battery cell 56 of an energy storage device 55 for a motor vehicle 50. Such a battery cell 56, such an energy storage device 55 and such a motor vehicle 50 and their features are described with reference to Fig. 1 to 5 described. Fig. 6 is made with reference to Fig. 1 to 5 described.

[0066] The procedure 100 according to Fig. 6 comprises: checking 101 a charging period TL, a charging request 75, and / or an initial state Z, wherein the initial state Z is defined by a cell temperature T and / or a cell voltage U. The initial state Z can also include an outside temperature. The outside temperature and the cell temperature T can be interdependent.

[0067] The method 100 comprises: first charging 105 the battery cell 56.

[0068] The method 100 comprises: first excitation 110a of the battery cell 56 by a first current pulse IP1 spaced apart in time from the first charging 105.

[0069] The method 100 comprises: detecting 110b a first cell voltage U1 as a response of the battery cell 56 to the first current pulse IP1.

[0070] The method 100 includes: a second charging 115 of the battery cell 56 by a charge input DQ. The charging 115 is performed with a constant charging current I.

[0071] The battery cell 56 is characterized by a hysteresis H having a charging voltage characteristic UKL, and the respective charging 105, 115 is carried out in such a way that the corresponding cell voltage U1, U2 corresponds to a charging cell voltage UL1, UL2 on the charging voltage characteristic UKL.

[0072] The method 100 comprises: second excitation 120a of the battery cell 56 by a second current pulse IP2 spaced apart in time from the second charging 115. The respective charging 105, 115 and the corresponding current pulse IP1, IP2 are spaced apart in time such that the corresponding cell voltage U1, U2 corresponds to an open-circuit voltage OCV.

[0073] The method 100 comprises: detecting 120b a second cell voltage U2 as a response of the battery cell 56 to the second current pulse IP2.

[0074] The method 100 comprises: determining 130 a first internal resistance Ri1 based on the first cell voltage U1 and the first current pulse IP1 and a second internal resistance Ri2 based on the second cell voltage U2 and the second current pulse IP2.

[0075] Steps 105 to 120b constitute a charging or diagnostic method and enable the determination 130 of the internal resistances Ri1, Ri2 as a function of the charge input DQ, optionally using the method for determining internal resistance during AC charging according to DE 10 2023 118 719.8 and / or a diagnostic mode during a rapid charging process. Relaxed, defined voltage values ​​can also be generated using the Delta-Q charging method according to DE 10 2023 118 719.8.

[0076] The method 100 comprises: determining 140 a state of charge reference SOC_R based on the charge input DQ and an internal resistance change DRi between the first internal resistance Ri1 and the second internal resistance Ri2. The internal resistance change DRi can be calculated based on a difference between the first internal resistance Ri1 and the second internal resistance Ri2: DRi = Ri2 - Ri1. When determining the state of charge reference SOC_R, the method 100 can access a look-up table. The state of charge reference SOC_R can optionally be output to be processed or taken into account for operating the battery cell 56 and / or the energy storage device 55.

[0077] The state of charge reference SOC_R comprises a starting state of charge SOC_S related to the first current pulse IP1 and a final state of charge SOC_E related to the second current pulse IP2. Alternatively or additionally, the state of charge reference SOC_R can comprise only the starting state of charge SOC_S or the final state of charge SOC_E. The state of charge reference SOC_R can comprise a difference between the final state of charge SOC_E and the starting state of charge SOC_S.

[0078] The method 100 includes: determining 150a a state of health SOH. Additionally or alternatively, the method 100 includes: recalibrating 150b a state of charge estimator 80 to determine the state of charge SOC of the battery cell 56.

[0079] The person skilled in the art will recognize that the method 100 according to Fig. 6 can also be performed in a different order than that shown. In particular, it is possible for steps of method 100 to be interchanged, shifted, and / or performed simultaneously.

[0080] The method 100 can be carried out in practice, for example, as follows: If a user wishes the motor vehicle 50 to run the "Delta-R diagnostic mode" overnight, the user can trigger the charging request 75 and connect the motor vehicle 50 to a charging station 91 for a specific time (e.g., at least 12 hours as the diagnostic duration TD). First, it is checked whether all boundary conditions (outside temperature, available time, etc.) are met. If the conditions are met, the Delta-R method starts and generates a value pair from an internal resistance difference DRi and a charge entry DQ. Using a look-up table in the motor vehicle 50, the value of the starting state of charge SOC_S and the final state of charge SOC_E can be determined for this specific internal resistance difference DRi. By combining the SOC information with the entered charge quantity DQ, the current state of health SOH can also be determined.The state of health SOH and the state of charge SOC are used to update or recalibrate corresponding dependent functions in the vehicle.

[0081] Fig. Figure 7 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 includes instructions (not shown) which, when the program or instructions are executed by a data processing device 51, cause the data processing device 51 to execute the method 100 and / or the steps of the method 100 according to Fig. 6 to be carried out.

[0082] The instructions can be present as program code in any code or in any language, in particular in code suitable for controlling and / or monitoring motor vehicles 50 and / or their energy storage device 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. Reference symbol (part of the description) 50 motor vehicles 51 Data processing device 52 drive 53 Communication interface 54 data storage 55 Energy storage device 56 battery cells 75 loading request 80 state of charge estimator 90 vehicle-external network 91 charging stations 100 procedures 101 Check 105 first store 106 first charging break 110a first stimulation 110b Detecting a first cell voltage 115 second loading 116 second charging break 120a second excitation 120b Detecting a second cell voltage 130 Determining a first internal resistance and a second internal resistance 140 Determining a state of charge reference 150a Determination of a health condition 150b Recalibration 200 Computer program and / or computer-readable medium DQ load entry DRi internal resistance change dt time difference dU voltage difference H Hysteresis I current, charging current IP1 first current pulse IP2 second current pulse OCV resting voltage Ri1 first internal resistance Ri2 second internal resistance t time t0 reference time T cell temperature TD diagnostic period U voltage U1 first cell voltage U2 second cell voltage U voltage, cell voltage UE discharge cell voltage UKE discharge voltage characteristic curve UKL charging voltage characteristic curve UL charging cell voltage UL1 first charging cell voltage UL2 second charging cell voltage SOC state of charge SOH health status SOC_E final state of charge SOC_R state of charge reference SOC_S Starting state of charge Z Initial state QUOTES CONTAINED IN THE DESCRIPTION

[0000] This list of documents submitted by the applicant was generated automatically and is included solely for the convenience of the reader. This list is not part of the German patent or utility model application. The DPMA assumes no liability for any errors or omissions. Cited patent literature

[0000] DE 10 2023 118 719.8 [0012, 0028, 0075] DE 10 2022 129 208.8 [0013, 0028] Cited non-patent literature

[0000] 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

[0007] D. -I. Stroe, M. Swierczynski, S. K. Kær and R. Teodorescu, „Degradation Behavior of Lithium-Ion Batteries During Calendar Ageing-The Case of the Internal Resistance Increase,“ in IEEE Transactions on Industry Applications, vol. 54, no. 1, pp. 517-525, Jan.-Feb. 2018, doi: 10.1109 / TIA.2017.2756026

[0026]

Claims

[1] Method (100) for determining the state of a battery cell (56) of an energy storage device (55) for a motor vehicle (50), the method (100) comprising: - first excitation (110a) of the battery cell (56) by a first current pulse (IP1) spaced apart in time from a first charging (105); - detecting (110b) a first cell voltage (U1) as a reaction of the battery cell (56) to the first current pulse (IP1); - second charging (115) of the battery cell (56) by a charge input (DQ); - second excitation (120a) of the battery cell (56) by a second current pulse (IP2) spaced apart in time from the second charging (115); - detecting (120b) a second cell voltage (U2) as a reaction of the battery cell (56) to the second current pulse (IP2); - determining (130) a first internal resistance (Ri1) based on the first cell voltage (U1) and the first current pulse (IP1) and a second internal resistance (Ri2) based on the second cell voltage (U2) and the second current pulse (IP2); and - determining (140) a state of charge reference (SOC_R) based on the charge input (DQ) and an internal resistance change (DRi) between the first internal resistance (Ri1) and the second internal resistance (Ri2). [2] Method (100) according to claim 1, wherein - the battery cell (56) is characterized by a charging voltage characteristic (UKL) exhibiting hysteresis, and - the respective charging (105, 115) is carried out in such a way that the corresponding cell voltage (U1, U2) corresponds to a charging cell voltage (UL1, UL2) on the charging voltage characteristic curve (UKL). [3] Method (100) according to claim 1 or 2, wherein the respective charging (105, 115) and the corresponding current pulse (IP1, IP2) are spaced apart in time such that the corresponding cell voltage (U1, U2) corresponds to an open-circuit voltage (OCV). [4] Method (100) according to one of the preceding claims, wherein the charging (115) is carried out with a constant charging current (I). [5] Method (100) according to one of the preceding claims, wherein the state of charge reference (SOC_R) comprises a starting state of charge (SOC_S) related to the first current plus (IP1) and a final state of charge (SOC_E) related to the second current pulse (IP2). [6] Method (100) according to one of the preceding claims, wherein the method (100) comprises: - Determining (150a) a state of health (SOH) and / or recalibrating (150b) a state of charge estimator (80) for determining the state of charge (SOC) of the battery cell (56). [7] Method (100) according to one of the preceding claims, wherein the method (100) comprises: - Checking (101) a diagnostic period (TD), a charging request (75) and / or an initial state (Z), wherein the initial state (Z) is defined by a cell temperature (T) and / or a cell voltage (U). [8] Computer program and / or computer-readable medium (200) 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 any 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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