Method and device for generating a user-specific charging strategy for a device battery of a technical device

Abstract

The invention relates to a method, in particular an at least partially computer-implemented method, for providing a lower and / or upper charge limit for carrying out charging processes of a device battery (12), wherein the lower and / or upper charge limit indicate a limit of the actual charge level of the device battery (12) at which the discharging of the device battery (12) is stopped or at which the charging is stopped; comprising the following steps: - recording (S1) operating parameter curves of a device battery (12); - Determining (S4) a current ageing state or determining a predicted course of the ageing state for a given prediction horizon depending on the company size trends for a past period; - adjusting (S5) the lower and / or upper state of charge limit depending on a deviation of the current state of ageing from a predetermined target state of ageing or depending on a deviation of the predicted course of the state of ageing for the predetermined prediction horizon from a predetermined course of the target state of ageing in order to reduce the deviation in the future operation of the device battery (12); - Providing (S6) the lower and / or upper charge level limit for operating the device battery (12).

Description

Technical area

[0001] The invention relates to device batteries for operating technical devices, and in particular to the use of charging strategies for charging such device batteries. Technical background

[0002] The use of battery-operated technical devices depends significantly on the application and behavior of the device's user. Accordingly, the sequence of charging phases, discharging phases, and rest phases of the device battery varies from device to device. Furthermore, the number of charging processes is significantly determined by the load during the discharging phases. The charging processes, in particular their duration, charging cycles, initial charge states, and final charge states, are therefore significantly dependent on the energy consumption during the discharging phases, which are determined by the type of use.

[0003] Typically, the upper and lower charge limits, i.e. the maximum and minimum real charge levels, are defined for the use of a device battery, and the available real charge level range in between is mapped or scaled to a range between 0 and 100% as the displayed charge level. This means that the user is shown a fully discharged device battery with a charge level of 0% and a fully charged battery with a charge level of 100%, with the real charge level of the discharged device battery at a higher charge level (lower charge level limit), e.g., approximately 20% SOC, and the real charge level of the fully charged device battery at a lower charge level (upper charge level limit), e.g., approximately 80% SOC. This enables battery-friendly charging ora more battery-friendly operation of the device battery can be achieved, and the additional capacity of the device battery between 0% actual charge level and the lower charge level limit and between the upper charge level limit and 100% actual charge level can be released if necessary, at the expense of increased battery aging. Disclosure of the invention

[0004] According to the invention, a method for generating a user-specific charging strategy for device batteries of a battery-operated technical device in the form of a lower and / or upper charge level limit for carrying out charging processes according to claim 1 and a corresponding device according to the independent claim are provided.

[0005] Further embodiments are specified in the dependent claims.

[0006] According to a first aspect, a method, in particular an at least partially computer-implemented method, is provided for providing a lower and / or upper charge limit for carrying out charging processes of a device battery, wherein the lower and / or upper charge limit indicate a limit of the actual charge level of the device battery at which the discharging of the device battery is stopped or at which the charging is stopped; comprising the following steps: - Recording operating parameter curves of a device battery; - Determination of a current ageing state or determination of a predicted course of the ageing state for a given prediction horizon depending on the company size trends for a past period; - Adjusting the lower and / or upper state of charge limit depending on a deviation of the current state of ageing from a specified target state of ageing or depending on a deviation of the predicted course of the state of ageing for the specified prediction horizon from a specified course of the target state of ageing in order to reduce the deviation in the future operation of the device battery; - Providing the lower and / or upper charge level limit for operating the device battery.

[0007] Portable batteries degrade over their service life and depending on their load and use. This so-called aging leads to a continuously decreasing maximum power or storage capacity. The state of aging corresponds to a measure of the aging of energy storage devices. According to convention, a new portable battery can have an aging state (in terms of its capacity, SOH-C) of 100%, which decreases noticeably over the course of its service life. The measure of the aging of a portable battery (change in the aging state over time) depends on the individual load on the portable battery, i.e., in the case of vehicle batteries, the driver's usage behavior, external ambient conditions, and the vehicle battery type.

[0008] Operating a device battery, i.e. charging and discharging it, at real charge levels below the lower charge level limit and above the upper charge level limit, leads to increased degradation of the device battery. However, normal operation of a technical device usually does not require the device battery to be used to its full capacity. Therefore, by adjusting the lower and upper charge levels, which correspond to a real minimum permissible charge level and a real maximum permissible charge level, respectively, aging can be reduced and the service life of the device battery extended. The real charge level of a device battery indicates the ratio of the stored usable charge to the maximum storable usable charge.

[0009] It may be provided that the lower and / or upper charge level limit is displayed or signaled to a user as a displayed charge level of 0% or a displayed charge level of 100%.

[0010] A user often has a specific charging behavior, whereby a charging process is started when the average charge level falls below a certain displayed state of charge and is terminated when a certain displayed state of charge, e.g., 100%, is reached. Thus, by specifying the lower and upper state of charge limits, the actual state of charge limits between which the charging process is carried out can be influenced.

[0011] Adapting a charging strategy by setting a lower and / or upper state of charge limit is conventionally performed to provide additional battery capacity under special conditions.

[0012] Due to the individual use of the device battery, the charging behavior differs, in particular because when a lower limit of a displayed charge level is reached, the search for a charging option is triggered.

[0013] Knowing the charging behavior—that is, the level of charge at which a user attempts to initiate a charging process and the level of charge at which the user aborts or terminates the charging process—significantly determines the degradation of the device's battery. As long as the number of charging processes does not change significantly, i.e., there is no noticeable loss of convenience for the user, e.g., more than one or two additional charging processes per week, the load on the device's battery during a charging process can be influenced by specifying lower and / or upper charge limits.

[0014] The available charge range can be displayed to the user as a state of charge between 0 and 100% SOC, while the lower and upper SOC limits can correspond to real-world states of charge, for example, between 5 and 30%, e.g., 20%, or between 70 and 95%, e.g., 80% SOC. Adjusting this lower and / or upper SOC limit thus determines the amount of charge flow during a charging process, particularly in degradation-intensive areas of very low and very high SOC, and thus the degradation of the device battery over a longer period of time.

[0015] The current aging state can be determined using conventional and known models for determining the aging state. In particular, an electrochemical aging state model can be used, which is fundamentally based on an electrochemical battery model. Such an electrochemical battery model can comprise a system of differential equations that, based on differential equations parameterized via model parameters, models internal battery states, in particular equilibrium states and, if applicable, kinetic states, using a time integration method and provides a relationship between operating parameter profiles of the device battery, namely a battery current, a battery voltage, a battery temperature, and a state of charge of the device battery, and the internal battery state. Such electrochemical battery models are known, for example, from the publications US 2016 / 023,566, US 2016 / 023,567, and US 2020 / 150,185.An aging state can be derived from the internal battery states.

[0016] According to the above method, it may be possible to predict the aging status of the device battery if the usage behavior is appropriately predicted or specified.

[0017] The basis for predicting the aging state is a usage pattern that reflects past usage behavior. The usage pattern specifies the type of use that leads to a certain load on the device battery and can be specified in a variety of ways. The usage pattern can make it possible to artificially specify or simulate a continuous course of load variables, such as battery current and temperature, and possibly battery voltage and state of charge, so that these represent a load on the device battery in a future period that corresponds to the load in the past, which is to be specified by the usage pattern, in particular during a specified past period of, for example, 6 months.

[0018] Furthermore, the usage pattern can define charging cycles, discharging cycles, and rest cycles, each representing a time period of a typical operating parameter profile. The usage pattern can, for example, be determined from historical usage-dependent operating parameter profiles of the device battery and comprise a sequence of charging cycles, discharging cycles, and rest cycles. The cycles are determined by their average durations, power throughputs, and one or more other usage characteristics. The charging cycles can be defined by charging profiles, and the discharging cycles by discharging profiles. The corresponding time periods are sequenced to obtain a predicted operating parameter profile.

[0019] To predict the aging state progression, the predicted operating variable progression is then evaluated using the aging state model.

[0020] The procedure can be carried out cyclically with a cycle duration of between one day and one month.

[0021] The lower and / or upper state of charge limit is adjusted depending on a deviation of the current state of age from a predefined target state of age or depending on a deviation of the predicted course of the state of age for the predefined prediction horizon from a predefined course of the target state of age in order to reduce the deviation in the future operation of the device battery. The deviation of the current state of age from a predefined target state of age can be determined as a simple difference between the age states. The deviation of the predicted course of the state of age for the predefined prediction horizon from a predefined course of the target state of age can be specified as the sum or integral of the deviations within the predefined prediction horizon.

[0022] In the case of a positive deviation, an incremental increase in the upper state of charge limit and / or an incremental decrease in the lower state of charge limit can be made. Similarly, in the case of a negative deviation, an incremental increase in the lower state of charge limit and / or an incremental decrease in the upper state of charge limit can be made. The change in the state of charge limit can, for example, be between + / -0.5 and + / -1.5%.

[0023] Alternatively, the increase in the upper / lower state of charge limit and / or the decrease in the lower / upper state of charge limit can be made proportional to the positive / negative deviation. Furthermore, a positive / negative change in the deviation and a positive / negative integral of the deviation over the prediction horizon can be used to increase the upper / lower state of charge limit and / or decrease the lower / upper state of charge limit.

[0024] Based on the usage pattern, which is specified in such a way that a course of the aging state can be predicted using a suitable aging state model that indicates a comparable load on the device battery, the influence of the predicted charging cycles on the degradation of the device battery can now be modeled by iteratively varying the upper and / or lower state of charge limit.

[0025] Methods for predicting artificial operating variables for portable batteries are known, for example, from DE 10 2022 202 882 A1 and DE 10 2021 212 689 A1.

[0026] Due to the required computing capacity, the method can be executed in a central unit remote from the device. For this purpose, the operating parameters of the technical device, in particular the device battery, such as battery current, battery voltage, battery temperature, and charge level, are transmitted to the remote central unit with high temporal resolution, and a usage pattern is created from this that reflects the resulting load on the device battery over a previous period of, for example, 6 months.

[0027] The usage pattern can then be used to appropriately predict charging cycles, discharging cycles, and rest cycles, e.g., in the form of operating parameter curves. In particular, the operating parameter curves are predicted by a sequence of characteristic charging cycles, discharging cycles, and rest cycles resulting from the previously determined usage pattern.

[0028] In general, the usage pattern can define one or more charging cycles, one or more discharging cycles and one or more rest cycles, each of which represents a time period of a given operating variable.

[0029] For example, charging cycles, discharging cycles and rest cycles can be arranged according to a hidden Markov model determined by the usage pattern.Thus, in order to determine an artificial operating variable profile, a sequence of time segments of the operating variable profiles of the one or more charging cycles, the one or more discharging cycles and the one or more rest cycles can be carried out, wherein the sequence is carried out according to a sequence which corresponds to a sequence of cycles in the predetermined previous period or is determined therefrom in particular on the basis of frequency considerations, wherein the time segments of the operating variable profiles for the one or more charging cycles and the one or more discharging cycles are compressed, truncated or stretched in time in such a way that a specific state of charge value results for the end times of discharging cycles and the start times of the subsequent charging cycles.

[0030] Furthermore, the upper and lower state of charge limits are used to signal the available state of charge range to the driver as a range between 0 and 100% of the state of charge. This means that the state of charge range between the lower and upper state of charge limits is mapped or scaled to a state of charge range between 0 and 100%. Brief description of the drawings

[0031] Embodiments are explained in more detail below with reference to the attached drawings. They show: Fig. 1 is a schematic representation of a vehicle with a vehicle battery in communication with a central unit; Fig. 2 a flowchart illustrating a method for adapting the charging strategy of a vehicle depending on the historical use of the vehicle; and Fig. 3 a diagram illustrating the generation of artificial operating variables depending on a probability distribution of a starting state of charge. Description of embodiments

[0032] Fig. Figure 1 schematically shows a vehicle 1 as an example of a technical device. The vehicle 1 is powered by an electric motor 11, which is supplied with energy via a vehicle battery 12 as a device battery. The vehicle has a control unit 13. A battery management system 14 is provided for monitoring the vehicle battery 12 and for measuring operating variables.

[0033] The control unit 13 or the battery management system 14 uses suitable sensors to record operating variables of the vehicle battery 12, in particular the terminal voltage, the battery current, and the battery temperature, and determines the state of charge by integrating charge inflows and outflows. Using a communication unit 15, these operating variables can be transmitted as operating variable profiles to a central unit 2 remote from the vehicle.

[0034] The central unit 2 comprises a data processing unit 21 in which part of the method described below can be carried out, and a database 22 for storing data points, model parameters, states and the like.

[0035] In Fig. Figure 2 shows a flowchart illustrating an exemplary procedure for determining an upper and / or lower state of charge limit. The method can be performed in conjunction with control unit 13 and central unit 2.

[0036] In step S1, operating variables, i.e. the battery voltage, the battery current, the battery temperature and the state of charge at cell level and / or at module level, are recorded in the vehicle battery 12 and transmitted to the central unit as time series.

[0037] Based on the operating parameter profiles, an aging state model can be parameterized and / or created in the central unit 2, which makes it possible to provide precise information about the aging state. Such a model can be further improved by using a large number of operating parameter profiles from multiple vehicles with similar vehicle batteries.

[0038] The current aging state can be determined from the operating variables using conventional and known models for determining the aging state. In particular, an electrochemical aging state model can be used, which is fundamentally based on an electrochemical battery model. Such an electrochemical battery model can comprise a system of differential equations that, based on differential equations parameterized via model parameters, models internal battery states, in particular equilibrium states and, if applicable, kinetic states, using a time integration method and provides a relationship between the operating variables of the device battery, namely a battery current, a battery voltage, a battery temperature, and a state of charge of the device battery, and the internal battery state.Such electrochemical battery models are known, for example, from the publications US 2016 / 023,566, US 2016 / 023,567, and US 2020 / 150,185. An aging state can be derived from the internal battery states.

[0039] In step S2, a usage pattern regarding the type of usage within a predetermined, in particular immediately past, period of, for example, 6 months can be determined in the central unit 2 from the historical business size trends.

[0040] The usage pattern can indicate the type of use in a variety of ways. For example, for discharge cycles, the energy throughput, such as the ampere-hour throughput, the duration and variation of the power drawn at respective battery temperatures and states of charge, and other characteristics can be used to describe usage. A rest cycle can be described by its average duration, average battery temperature, and average state of charge. A charging cycle can be specified by a charging curve (the course of the average charging current depending on the state of charge), a lower limit of the displayed state of charge, and an upper limit of the displayed state of charge.

[0041] For example, a hidden Markov model can be created from the sequence of discharge cycles, charge cycles and rest cycles, which allows an artificial generation of a future use, so that synthetic or artificial, ie not real, operating variable profiles can be generated, which lead to a comparable load on the vehicle battery 12.

[0042] In step S3, the usage pattern enables the generation of artificial operating parameter profiles. The usage pattern can, for example, select a time period, such as a week, a day, a month, or similar, within the predetermined, particularly immediately past, period within which the vehicle battery 12 was used on average, i.e., the time period in which the change in aging state is closest to the average of all aging state changes in the time periods. A sequence of cycles, including their durations and loads, can now be determined, e.g., in the form of an ampere-hour throughput.

[0043] Each charging cycle can be assigned an operating variable profile resulting from a charging curve (profile of the maximum charging current versus the state of charge), and each discharging cycle can be assigned a varying operating variable profile corresponding to a load on the vehicle battery 12, which indicates the average load of the discharge cycles from the predetermined period. To generate the predicted artificial operating variable profiles, the operating variable profiles can be arranged one or more times in the sequence of the predetermined period. Several different discharge cycles can also be defined and assigned operating variable profiles that have different durations and ampere-hour throughputs, so that city trips, motorway trips, and cross-country trips with significantly different durations within the predetermined period can also be taken into account in the artificial operating variable profile.

[0044] Alternatively, using a hidden Markov model, sequences of characteristic charging, discharging, and resting cycles (preferably multiple charging, multiple discharging, and multiple resting cycles) can be determined for random selection according to the transition probabilities between charging, discharging, and resting cycles. Operating variable profiles with a load on the vehicle battery 12 determined by the usage pattern are assigned to each of these cycles. Each cycle is then assigned a temporal segment of a specific operating variable profile, which are then arranged in sequence. As described above, the actual state of charge at which a charging cycle ends or a discharging cycle begins can be specified by temporally compressing, stretching, or shortening the temporal segments of the operating variable profiles.

[0045] Thus, the usage pattern can be used to predict operating size trends within the prediction horizon based on the usage behavior during the predetermined past period, which leads to a comparable load or degradation per unit of time.

[0046] In Fig.Figure 3 shows, as an example, a schematic representation of the transition of the operating variable profiles of the battery current I and the actual state of charge SOC from a discharge cycle BZ1 to a charging cycle LZ and from the charging cycle LZ to a further discharge cycle BZ2. One can see the starting state of charge SOC* at the beginning of the charging cycle, which results from a random selection of the probability distribution of the starting states of charge when compiling the artificial operating variable profile and can therefore vary for further such transitions within the predicted operating variable profile. One can also see the final state of charge SOC** at the beginning of the discharge cycle, which results from a random selection of the probability distribution of the final states of charge when compiling the artificial operating variable profile and can therefore vary for further such transitions within the predicted operating variable profile.

[0047] When generating the predicted operating variable curves, operating variable curves of discharge cycles following a charge cycle can be provided in such a way that the displayed state of charge at the time of the change from the discharge cycle to the charge cycle corresponds to the specified frequency distribution.

[0048] The predicted operating parameter profiles can now be used in step S4 to determine an aging state trajectory according to the provided aging state model. In step S4, a profile of the predicted aging state is obtained based on the calendar age of the vehicle battery 12, which is determined using the artificial operating parameter profiles and the aging state model.

[0049] In step S5, the lower and / or upper state of charge limit is adjusted depending on a deviation of the predicted aging state profile for the specified prediction horizon from a specified target aging state profile in order to reduce the deviation in the future operation of the device battery. The deviation of the predicted aging state profile for the specified prediction horizon from a specified target aging state profile can be specified as the sum or integral of the deviations within the specified prediction horizon.

[0050] In the case of a positive deviation, an incremental increase in the upper state of charge limit and / or an incremental decrease in the lower state of charge limit can be made. Similarly, in the case of a negative deviation, an incremental increase in the lower state of charge limit and / or an incremental decrease in the upper state of charge limit can be made. The change in the state of charge limit can, for example, be between + / -0.5 and + / -1.5%.

[0051] Alternatively, the increase in the upper / lower state of charge limit and / or the decrease in the lower / upper state of charge limit can be made proportional to the positive / negative deviation. Furthermore, a positive / negative change in the deviation and a positive / negative integral of the deviation over the prediction horizon can be used to increase the upper / lower state of charge limit and / or decrease the lower / upper state of charge limit.

[0052] The upper and lower state of charge limits determined by the above method can now be transmitted back to the vehicle in a subsequent step S6 and implemented there. In particular, the upper and lower state of charge limits (as real state of charge limits) determine the displayed state of charge of 100% and 0%, respectively, since this corresponds to the usable capacity range of the vehicle battery 12.

[0053] The vehicle may further provide for the driver to selectively deactivate the automated charging strategy in order to increase the available battery capacity and obtain a longer range of the vehicle. 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] US 2016 / 023,566 [0015, 0038] US 2016 / 023,567 [0015, 0038] US 2020 / 150,185 [0015, 0038] DE 10 2022 202 882 A1

[0025] DE 10 2021 212 689 A1

[0025]

Claims

[1] Method, in particular an at least partially computer-implemented method, for providing a lower and / or upper charge limit for carrying out charging processes of a device battery (12), wherein the lower and / or upper charge limit indicate a limit of the actual charge level of the device battery (12) at which the discharging of the device battery (12) is stopped or at which the charging is stopped; comprising the following steps: - recording (S1) operating parameter curves of a device battery (12); - Determining (S4) a current ageing state or determining a predicted course of the ageing state for a given prediction horizon depending on the company size trends for a past period; - adjusting (S5) the lower and / or upper state of charge limit depending on a deviation of the current state of ageing from a predetermined target state of ageing or depending on a deviation of the predicted course of the state of ageing for the predetermined prediction horizon from a predetermined course of the target state of ageing in order to reduce the deviation in the future operation of the device battery (12); - Providing (S6) the lower and / or upper charge level limit for operating the device battery (12). [2] Method according to claim 1, wherein the target aging state is predetermined according to the calendar age of an average device battery (12) or the course of the target aging state is predetermined according to the calendar age of the average device battery (12). [3] Method according to claim 1 or 2, wherein a usage pattern is determined from the operating variable curves of a predetermined, in particular immediately past, period, wherein the usage pattern indicates operating characteristics which represent a load on the device battery (12), so that an artificially predicted curve of operating variables can be determined depending on the usage pattern. [4] Method according to claim 3, wherein the usage pattern defines one or more charging cycles, one or more discharging cycles and one or more rest cycles, each of which is assigned a time segment of a predetermined operating variable profile. [5] Method according to claim 4, wherein, in order to determine an artificial operating variable profile, a sequence of the time segments of the operating variable profiles of the one or more charging cycles, the one or more discharging cycles and the one or more rest cycles is carried out, wherein the sequence is carried out according to a sequence which corresponds to a sequence of cycles in the predetermined previous period or is determined therefrom, in particular on the basis of frequency considerations, wherein the time segments of the operating variable profiles for the one or more charging cycles and the one or more discharging cycles are compressed, truncated or stretched in time, so that the charge states at the end of a charging cycle / discharging cycle each correspond to a charge state at the beginning of a discharging cycle / charging cycle. [6] Method according to one of claims 1 to 5, wherein the lower and / or upper state of charge limit is adapted depending on a deviation of the current state of ageing from a predetermined target state of ageing or depending on a deviation of the predicted course of the state of ageing for the predetermined prediction horizon from a predetermined course of the target state of ageing, by an incremental increase of the upper state of charge limit and / or an incremental reduction of the lower state of charge limit being carried out in the case of a positive deviation and / or an incremental increase of the lower state of charge limit and / or an incremental reduction of the upper state of charge limit being carried out in the case of a negative deviation. [7] Method according to one of claims 1 to 5, wherein the lower and / or upper state of charge limit is adapted as a function of a deviation of the current state of ageing from a predetermined target state of ageing or as a function of a deviation of the predicted course of the state of ageing for the predetermined prediction horizon from a predetermined course of the target state of ageing, by increasing the upper / lower state of charge limit and / or reducing the lower / upper state of charge limit in proportion to the positive / negative deviation, wherein in particular a positive / negative change in the deviation and / or a positive / negative integral of the deviation over the prediction horizon is used to increase the upper / lower state of charge limit and / or reduce the lower / upper state of charge limit. [8] Method according to one of claims 1 to 7, wherein the lower and / or the upper charge level limit is signalled to a user as a displayed charge level of 0% or a displayed charge level of 100%. [9] Method according to one of claims 1 to 8, wherein the aging state model comprises an electrochemical battery model comprising a time-variant differential equation system. [10] A method according to any one of claims 1 to 9, wherein a selection is provided by which the user selectively selects or deactivates the use of the adjusted lower and / or upper state of charge limit. [11] Apparatus for carrying out one of the methods according to one of claims 1 to 10. [12] A computer program product comprising instructions which, when the program is executed by at least one data processing device, cause the device to carry out the steps of the method according to any one of claims 1 to 10. [13] Machine-readable storage medium comprising instructions which, when executed by at least one data processing device, cause the device to carry out the steps of the method according to one of claims 1 to 10.

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