CN114252779A - Method and device for determining the state of charge of a battery in a battery-operated machine - Google Patents

Method and device for determining the state of charge of a battery in a battery-operated machine Download PDF

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CN114252779A
CN114252779A CN202111122856.2A CN202111122856A CN114252779A CN 114252779 A CN114252779 A CN 114252779A CN 202111122856 A CN202111122856 A CN 202111122856A CN 114252779 A CN114252779 A CN 114252779A
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charge
state
soc
battery
calc
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C·西莫尼斯
C·沃尔
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Robert Bosch GmbH
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Robert Bosch GmbH
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/367—Software therefor, e.g. for battery testing using modelling or look-up tables
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G01R31/3842—Arrangements for monitoring battery or accumulator variables, e.g. SoC combining voltage and current measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/382—Arrangements for monitoring battery or accumulator variables, e.g. SoC
    • G01R31/3835—Arrangements for monitoring battery or accumulator variables, e.g. SoC involving only voltage measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/385—Arrangements for measuring battery or accumulator variables
    • G01R31/387—Determining ampere-hour charge capacity or SoC
    • G01R31/388—Determining ampere-hour charge capacity or SoC involving voltage measurements
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/392—Determining battery ageing or deterioration, e.g. state of health
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01R—MEASURING ELECTRIC VARIABLES; MEASURING MAGNETIC VARIABLES
    • G01R31/00—Arrangements for testing electric properties; Arrangements for locating electric faults; Arrangements for electrical testing characterised by what is being tested not provided for elsewhere
    • G01R31/36—Arrangements for testing, measuring or monitoring the electrical condition of accumulators or electric batteries, e.g. capacity or state of charge [SoC]
    • G01R31/396—Acquisition or processing of data for testing or for monitoring individual cells or groups of cells within a battery
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/48—Accumulators combined with arrangements for measuring, testing or indicating the condition of cells, e.g. the level or density of the electrolyte
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M10/00—Secondary cells; Manufacture thereof
    • H01M10/42—Methods or arrangements for servicing or maintenance of secondary cells or secondary half-cells
    • H01M10/425—Structural combination with electronic components, e.g. electronic circuits integrated to the outside of the casing
    • H01M2010/4278—Systems for data transfer from batteries, e.g. transfer of battery parameters to a controller, data transferred between battery controller and main controller
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01M—PROCESSES OR MEANS, e.g. BATTERIES, FOR THE DIRECT CONVERSION OF CHEMICAL ENERGY INTO ELECTRICAL ENERGY
    • H01M2220/00—Batteries for particular applications
    • H01M2220/20—Batteries in motive systems, e.g. vehicle, ship, plane
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02E—REDUCTION OF GREENHOUSE GAS [GHG] EMISSIONS, RELATED TO ENERGY GENERATION, TRANSMISSION OR DISTRIBUTION
    • Y02E60/00—Enabling technologies; Technologies with a potential or indirect contribution to GHG emissions mitigation
    • Y02E60/10—Energy storage using batteries

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  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • Engineering & Computer Science (AREA)
  • Manufacturing & Machinery (AREA)
  • Chemical & Material Sciences (AREA)
  • Chemical Kinetics & Catalysis (AREA)
  • Electrochemistry (AREA)
  • General Chemical & Material Sciences (AREA)
  • Microelectronics & Electronic Packaging (AREA)
  • Secondary Cells (AREA)

Abstract

The invention relates to a method for ascertaining a calculated state of charge of a battery-powered machine; the method comprises the following steps: -providing an operating parameter of the battery; -providing a calculated state of charge in the machine by means of a distribution model, which accounts for the calculated state of charge from the modeled no-load voltage of the battery; -ascertaining a reference state of charge from the operating variable by means of a reference state of charge model, wherein the reference state of charge model is trained in order to specify the reference state of charge from the operating variable and in particular from a predefined state of aging; -applying a correction to the modeled open circuit voltage as a function of the difference between the reference state of charge and the calculated state of charge, in order to ascertain the calculated state of charge from the corrected open circuit voltage by means of the distribution model.

Description

Method and device for determining the state of charge of a battery in a battery-operated machine
Technical Field
The present invention relates to battery-powered machines, in particular motor vehicles, such as electric or hybrid vehicles, and also to measures for determining the state of charge of a battery.
Background
The energy supply of an electrically operated, battery-operated machine, such as an electrically drivable motor vehicle, takes place by means of a battery as an electrical energy accumulator. When operating an electrically drivable motor vehicle, a statement about the current state of charge of the battery is important. On the one hand, the driver or the navigation system requires a statement about the current state of charge for planning a possible stop in order to carry out the charging process if necessary. On the other hand, state of charge is required for energy management, in particular for implementing hybrid strategies in hybrid drive systems.
In modern battery controllers, in addition to the function for operating the battery, a battery model is also stored which allows the current state of charge to be determined from the change curves of the battery current, the battery voltage, the battery temperature and similar parameters. Furthermore, the cell model is parameterized with a number of parameters which can also take into account the past load of the cell. The battery model has, as important parameters, a no-load voltage, two resistance values, i.e., an internal resistance and a parallel resistance of the RC element, and a capacitor capacity of the RC element, which depend on the aging state of the battery. In the case of corresponding battery models, this is currently only achieved inadequately in the battery controller, taking into account the aging of the battery, since the aging state can now be specified only with inadequate accuracy.
Disclosure of Invention
According to the present invention, a method for ascertaining the state of charge of a battery-operated machine according to claim 1 and a method for operating a central unit for providing a reference state of charge, a method for operating a battery-operated machine and corresponding devices according to the independent claims are provided.
Further embodiments are given in the dependent claims.
According to a first aspect, a method for ascertaining a state of charge of a battery of a machine is provided, having the following steps:
-providing an operating parameter of the battery;
-providing a state of charge calculated in the machine by means of a distribution model, which accounts for the calculated state of charge from the modeled no-load voltage of the battery;
-ascertaining a reference state of charge from the operating variable by means of a reference state of charge model, wherein the reference state of charge model is trained in order to specify the reference state of charge from the operating variable and in particular from a predefined state of aging;
-applying a correction to the modeled open circuit voltage as a function of the difference between the reference state of charge and the calculated state of charge, in order to ascertain the calculated state of charge from the corrected open circuit voltage by means of the assignment model.
In order to operate a machine having a battery, knowledge of the current state of charge of the battery is necessary. The state of charge changes continuously during active operation as a result of charge consumption, the type of operating mode and the current battery state being determined in a non-linear manner: how the state of charge of the battery decreases at a specific charge consumption or increases at a charge increase in a charging process or a regeneration process (braking energy recovery).
The current state of charge is usually ascertained by means of a state of charge model, which specifies the current state of charge of the battery as a function of operating variables of the battery, such as, for example, the battery current, the battery temperature and the battery voltage. The state of charge is usually specified here as the percentage of the maximum charge capacity when the battery is fully charged. The state of charge is determined by means of the battery model parameters, which include, in particular, the no-load voltage of the individual cells of the battery, the internal resistance values and the parallel resistance values of the RC elements and the capacitor capacity. The battery model parameters in turn depend on the state of aging of the battery.
The state of charge model includes a battery model and an assignment model. The battery model is used to ascertain the voltage of the battery or the cell voltage, which corresponds to the terminal voltage of the individual battery cells, by means of the battery model parameters. The distribution model is used for outputting the state of charge according to the aging state, the temperature and the single battery voltage of the battery.
The assignment model is established on the basis of the measurement and is implemented, for example, as a characteristic field in order to assign the no-load voltage modeled by the battery model to the measured state of charge. The state of aging of the battery can be estimated from the operating variables of the battery on the basis of a predefined state of aging model.
The data configuration of the state of charge model as a function of the battery model parameters which depend on the state of aging and the current operating variables which describe the current operating state is very complicated, in particular because the state of aging model is required for ascertaining the state of aging, and the state of aging model is also required to be configured with data. Therefore, implementation in a battery controller in a battery-powered machine is resource intensive.
Furthermore, the determination of the modeled open-circuit voltage on the basis of the operating variables is usually carried out only imprecisely. The no-load voltage is typically modeled based on a characteristic field. However, configuring the battery model with data on the basis of all operating variables that influence the open circuit voltage, such as temperature, state of aging and state of charge, is very complicated. In particular, such battery models can only be implemented with great effort in battery controllers, since the temperature and aging state dependency is difficult to map in a comprehensive manner due to highly dynamic load transfer and recovery processes and relaxation behavior (relax).
The state of charge model generally provides a battery model in order to model the no-load voltage as the cell voltage or battery voltage in the unpowered operation and to assign it to the current state of charge according to a distribution function. The distribution function maps the no-load voltage, typically the battery temperature, and the state of aging to the corresponding state of charge of the battery.
In order to calculate the no-load voltage using the battery model, the operating variables of the battery, namely the battery current, the battery voltage, the battery temperature and the current state of charge and, if necessary, the state of aging of the battery, are required.
The above-described method provides for correcting the state of charge model in the battery-operated machine by means of an additionally provided reference model. For this purpose, the state of charge calculated in this way is compared with the state of charge ascertained by means of a reference model in order to correct the state of charge model.
The reference model maps the state of aging, the battery temperature and the battery voltage in the unpowered operating point to a reference state of charge, in particular in the form of a multidimensional characteristic field. For this purpose, the reference model can be built with the aid of a larger database, in particular on the basis of fleet data.
If a deviation occurs between the modeled state of charge and the reference-state of charge, then the state of charge model needs to be corrected.
Preferably, the reference model is implemented in the central unit outside the machine, so that it can be trained and refined based on fleet data for many machines. The correction can be carried out on the basis of the difference between the measured open-load voltage and the modeled open-load voltage of the cell or battery in the case of stabilization, i.e. when the battery current is zero or close to zero.
Since the state of charge model in the machine first determines the modeled residual voltage from the measured current operating variables, in particular on the basis of the characteristic field, and subsequently assigns the modeled residual voltage to the state of charge by means of the assignment model, the modeled residual voltage ascertained by the battery model can be corrected. The correction is made based on the difference between the measured open circuit voltage in the case of stabilization and the open circuit voltage modeled by the battery model.
It can be provided that the correction is carried out in such a way that, in addition, a continuous and temporally differentiable profile of the corrected cell voltage is generated for applying the modeled no-load voltage or the distribution model, so that the ascertained state of charge is likewise continuous and temporally differentiable.
Furthermore, it can be provided that the correction is carried out by means of a correction characteristic curve. The correction variable has a continuous and temporally differentiable profile which, with a 100% state of charge, leads to a correction variable which does not change the modeled open-circuit voltage. This prevents, on the one hand, a corrected modeled residual voltage which is greater than the maximum possible value, in particular when the battery is fully charged, and, on the other hand, the change in the residual voltage can be adapted by the correction as a function of the current state of charge.
It can be provided that the reference state of charge model is implemented outside the machine in a central unit, the operating variables of the battery being transmitted to the central unit by the relevant machine.
The advantage of the above-described method is that, in the presence of an accurate or continuously improved reference model, for example in a central unit, a very inaccurate parameterization of the state of charge model takes place outside the machine during commissioning, thus enabling the result of ascertaining the current state of charge more accurately, without continuous reparameterization of the battery model being required.
In particular, provision can be made for the reference state of charge to be transmitted to the machine or for a trigger signal to be ascertained as a result of a comparison between the reference state of charge and the calculated state of charge to be transmitted to the machine.
According to one specific embodiment, the reference state of charge model can be formed on the basis of data and ascertained using training data from a plurality of battery-specific measurements.
Furthermore, the aging state can be ascertained in the central unit by means of an aging state model, in particular based on data, and the aging state considered in the reference state of charge model for ascertaining the reference state of charge is provided.
Provision can be made for the correction to be carried out according to a correction characteristic curve which provides a correction variable as a function of the calculated state of charge, the correction variable being applied to the modeled residual voltage in an additive or multiplicative manner.
In particular, the correction characteristic curve can be updated as a function of a determination of a difference between the reference state of charge and the calculated state of charge by: the predefined functional relationship of the correction characteristic curve is parameterized by an evaluation point, which depends on the current state of charge and the difference between the reference state of charge and the calculated state of charge.
According to a further aspect, a method for operating a central unit for providing a reference state of charge for a battery of a battery-operated machine, in particular for the above method, is provided, having the following steps:
-receiving an operating parameter of the battery;
-ascertaining a reference-state-of-charge of the battery with a reference-state-of-charge model based on the operating parameter of the battery;
-transmitting the reference-state of charge to the machine or transmitting a trigger signal to the machine, the trigger signal being ascertained as a result of a comparison between the reference-state of charge and a state of charge calculated by the machine.
According to another aspect, a method for operating a battery-operated machine is provided for ascertaining a calculated state of charge of a battery in the machine, having the following steps:
-ascertaining the modeled no-load voltage by means of a battery model;
-correcting the modeled open-load voltage as a function of the calculated state of charge by means of a correction characteristic curve, wherein the correction characteristic curve provides a correction variable as a function of the calculated state of charge;
-loading the modeled no-load voltage with the correction amount;
-ascertaining the calculated state of charge by means of a distribution model from the corrected open-load voltage.
Furthermore, the correction characteristic curve can be updated as a function of a reference state of charge or a trigger signal by: the predefined functional relationship of the correction characteristic curve is parameterized by means of an evaluation point, which depends on the current state of charge and the difference between the reference state of charge and the calculated state of charge.
According to another aspect, a system for ascertaining a state of charge of a battery of a machine is provided, wherein the system has a plurality of machines and a central unit, wherein the system is designed to:
-providing an operating parameter of the battery;
-providing a calculated state of charge in the machine by means of a distribution model, which accounts for the calculated state of charge from the modeled no-load voltage of the battery;
-ascertaining a reference state of charge from the operating variable by means of a reference state of charge model, wherein the reference state of charge model is trained in order to specify the reference state of charge from the operating variable and in particular from a predefined state of aging;
-applying a correction to the modeled open circuit voltage as a function of a difference between a reference-state of charge and the calculated state of charge, in order to ascertain the calculated state of charge from the corrected open circuit voltage by means of the assignment model.
According to a further aspect, an apparatus, in particular a data processing unit in a central unit, for providing a reference state of charge for a battery of a battery-operated machine is provided, wherein the apparatus is designed to:
-receiving an operating parameter of the battery;
-ascertaining a reference-state-of-charge of the battery with a reference-state-of-charge model based on the operating parameter of the battery;
-transmitting the reference-state of charge to the machine or transmitting a trigger signal to the machine, the trigger signal being ascertained from the result of the comparison between the reference-state of charge and the calculated state of charge received from the machine.
According to a further aspect, a control unit in a device, in particular in a battery-operated machine, for ascertaining a calculated state of charge of a battery in the machine is provided, wherein the device is configured for:
-ascertaining the modeled no-load voltage by means of a battery model;
-correcting the modeled idling voltage as a function of the calculated state of charge by means of a correction characteristic curve, wherein the correction characteristic curve provides a correction variable as a function of the calculated state of charge;
-loading said modeled no-load voltage with said operating parameter;
-ascertaining the calculated state of charge by means of a distribution model from the corrected open-load voltage.
Drawings
The embodiments are explained in detail below with the aid of the figures.
Wherein:
fig. 1 shows a schematic diagram of a system for providing a reference-state of charge to motor vehicles of a fleet of vehicles by a central unit based on fleet data;
fig. 2 shows a schematic functional block diagram of a process for ascertaining the state of charge of a battery by means of a state of charge model and a correction function;
FIG. 3 shows a flow chart illustrating a method for identifying correction requirements for a state of charge model used to ascertain the state of charge of a battery;
FIG. 4 shows a flow chart illustrating a method for applying a correction to a state of charge model for a battery in a motor vehicle using a correction-characteristic curve;
fig. 5 shows a time profile of the battery current for illustrating the time periods in which the no-load voltage of the battery can be detected; and is
Fig. 6a and 6b show characteristic curves for correcting the modeled idle voltage of a battery model in a motor vehicle.
Detailed Description
The method according to the invention is described below with the aid of a vehicle battery, which is used as a battery in a number of motor vehicles as battery-operated machines. In a motor vehicle, a state of charge model for the respective battery can be implemented in the control unit. The state of charge model can be continuously updated or corrected by means of the central unit on the basis of operating parameters of the vehicle batteries from the fleet.
The above examples represent a number of stationary or mobile machines with a grid-independent energy supply, such as for example vehicles (electric cars, electric bicycles, etc.), appliances, machine tools, household appliances, IOT devices, etc., which are in connection with a central unit (cloud) via a corresponding communication connection (e.g. LAN, internet).
Fig. 1 shows a system 1 with a central unit 2 which is in combined connection with a plurality of motor vehicles 4 of a fleet 3. One of the motor vehicles 4 is shown in more detail in fig. 1 as representative of the other motor vehicles.
The motor vehicle 4 has a battery 41 (traction battery), an electric drive motor 42 and a control unit 43, respectively, as a rechargeable electrical energy accumulator, which together form a drive system, as is known from the prior art.
The control unit 43 is connected to a communication module 44 which is suitable for transmitting data between the respective motor vehicle 4 and the central unit 2 (the so-called cloud). The operating parameters of the battery are detected by means of a sensor device 45 in a manner known per se.
The central unit 2 has a data processing unit 21 and a database 22, wherein the method described below can be executed in the data processing unit 21 and the database 22 is used for storing the aging state change curves of the batteries 41 of the vehicles 4 of the fleet 3.
The operating variable describes at least one variable, the state of aging of the battery being dependent on said variable. The operating variables F can describe the course of the battery current, the course of the battery voltage (terminal voltage), the course of the battery temperature and the course of the state of charge. The operating variable F is detected in a fast time raster of 2 to 100 Hz and can be transmitted to the central unit 2 periodically in uncompressed and/or compressed form. For example, the time series can be transmitted to the central unit 2 in blocks at intervals of 10 minutes to several hours.
In the central unit 2, two operating characteristics can be generated from the operating variables F or in other embodiments, operating characteristics can already be generated in the respective motor vehicle 4, which operating characteristics relate to the evaluation time period. The operational characteristics are used to determine an aging state. These operating characteristics are ascertained over successive evaluation periods of several hours (e.g. six hours) to several weeks (e.g. one month), respectively. A common value for the evaluation period is one week.
The operating characteristics can include, for example, characteristics relating to the evaluation period and/or cumulative characteristics and/or statistical variables ascertained over the service life range up to now. In particular, the operating characteristics can include, for example: temperature, battery voltage, histogram data of the battery current with respect to a state of charge variation curve, in particular with respect to a battery temperature distribution over the state of charge, a charging current distribution over the temperature and/or a discharging current distribution over the temperature, cumulative total charge (Ah), an increase in average capacity during charging (in particular for charging processes in which the charge increment is above a threshold fraction (for example 20%) of the total battery capacity), a maximum value of differential capacity (dQ/dU: change in charge divided by change in battery voltage), etc.
An aging state model can be provided in the central unit 2, which aging state model is established on the basis of characteristic curves, on the basis of physics or on the basis of data. The aging status model can evaluate the operational feature points and the operational feature points can ascertain the aging status of the respective batteries of a particular vehicle of the fleet.
In fig. 2, a block diagram is shown in detail for illustrating the functions performed in the system 1 with the central unit 2 and the respective vehicles 4 of the platoon 3. Fig. 3 accordingly shows a flow chart for describing a method performed at the central unit 2 of the system 1. Fig. 4 shows a part of a method which is carried out in a motor vehicle, in particular in the control unit 43. The method for ascertaining the state of charge is described in detail below for motor vehicles 4, which are exemplary of a vehicle fleet 3.
In step S1, the operating variable F of the battery 41 is transmitted to the central unit 2 as described above. Furthermore, the current state of charge SOC calculated in the relevant motor vehicle 4 is transmittedcalc。
In step S2, the operating variable F is summarized as an operating characteristic. The operating variables F and the operating characteristics are subsequently processed in a physical-based or data-based aging state model 51 in order to obtain the current aging state SOH.
The State of aging (SOH: State of Health) is a key parameter for specifying the maximum remaining battery capacity or the maximum remaining battery charge. The aging state can be expressed as a Capacity Retention Rate (SOH-C) or an increase in internal resistance (SOH-R). The capacity retention rate SOH-C is expressed as a ratio of the measured instantaneous capacity to the initial capacity of the fully charged battery. The relative change in the internal resistance SOH-R increases as the degree of aging of the battery increases. The state of aging can be provided as SOH-C or SOH-R, respectively.
In step S3, the state of aging SOH thus modeled of the battery 41 and the operating variables received by the particular motor vehicle 4 are fed to a reference state of charge model 52, which outputs a reference state of charge SOCref. The reference state of charge model 52 is implemented in the central unit 2, in particular outside the vehicle, and can be established on the basis of fleet data. The reference state of charge model 52 implements the battery current, the battery temperature, the state of charge SOC currently calculated in the motor vehicle 4calcAnd state of aging SOH to reference-state of charge SOCrefAnd has been established by means of fleet data.
The reference state of charge model 52 can be provided, in particular, as a data-based model, which is trained on fleet data or from measurement data of a test stand for measuring batteries.
The aging state model 51 and the reference state of charge model 52 are preferably implemented in the central unit 2. This has the advantage that they can be updated regularly or continuously, in particular on the basis of fleet data.
In step S4, it is checked whether the reference state of charge SOC has occurredrefAssociated with said calculated state of charge SOC delivered by the associated motor vehicle 4calcIn particular a deviation above a predetermined threshold value. If the reference-state-of-charge SOC is determinedrefAnd the calculated state of charge SOCcalcIf there is a deviation between (alternative: yes), a correction in the motor vehicle is triggered in step S5, otherwise (alternative: no) a jump is made back to step S1.
The method for correcting the ascertainment of the state of charge in a motor vehicle is described below.
For this purpose, in step S11, the state of charge model in the motor vehicle is continuously operated in order to provide the current calculated state of charge SOC for the subsequent vehicle function in the motor vehicle 4calc. The current operating variable F and the current calculated state of charge SOC are likewise determinedcalcTo said central unit 2.
The state of charge model includes a battery model 53 and an assignment model 54.
In step S12, the battery model 53 uses modeling, in particular based on the characteristic field, to derive the operating variable F, i.e. the current battery current, the current battery temperature, and the current calculated state of charge SOCcalcAnd the current state of aging SOH to find out the modeled no-load voltage UocvWherein said current isThe aging state can be ascertained inside or outside the vehicle, in particular can be received by the central unit 2, and the modeled no-load voltage UocvCan correspond to the no-load voltage U of the single batteryocvOr if necessary, the idle voltage of the entire battery 41.
Such a modeled free-wheeling voltage U can be corrected by means of a correction block 55ocv. In step S13, it is checked in the correction block 55 whether a correction should be carried out. This can be signaled by the central unit 2 as a function of the trigger signal TR, in particular if the reference state of charge SOCrefAnd the calculated state of charge SOC ascertained by the state of charge modelcalcThe deviation between these is identified before or within a predetermined past time period and is signaled by the central unit 2. If a correction is to be carried out (alternative: yes), the method continues with step S14. Otherwise (alternative: no), the process goes back to step S11.
In step S14, it is checked whether a steady state of the battery exists. This can be identified by monitoring the battery current. If the battery current is 0A (alternative: YES), an idle voltage U is applied to the battery 41 in step S15messThe measurement of (2). Otherwise (alternative: no), the method continues with step S17.
As shown in connection with fig. 5 (diagram of the time-dependent course of the battery current), in step S15, the idling voltage U is carried out at a time when the motor vehicle 4 is not movingmessThe measurement of (2). For this purpose, during the standby time, the controller can be woken up after an applicable time (time t 1) (relaxation has ended), for example 1 hour, and the idling voltage U can be applied by means of the sensor device 45messThe measurement of (2). In a further advantageous embodiment of the invention, the measurement can also be carried out at a time greater than the above-mentioned applicable time, i.e. immediately before the start of motor vehicle 4 (time t 2). Here, the measurement can preferably already be carried out when the door of the vehicle is unlocked, and not only when the motor vehicle 4 is started, for ensuring the sameThe battery is not loaded by the power electronics nor by additional loads via the onboard electrical system.
In step S16, the correction model 55 is based on the measured no-load voltage UmessAnd the modeled no-load voltage UocvTo determine a correction-characteristic curve. The correction characteristic curve represents the current calculated state of charge SOCcalcIs mapped onto the correction value K.
In step S17, the calculated state of charge SOC is added tocalcA correction variable K is applied, which has already been determined from the last correction characteristic curve according to the current state of charge SOCcalcAnd (6) obtaining. In the embodiment shown, the correction variable K is used to model the open-circuit voltage U in the addition block 56ocvAn additive load is performed. Likewise, the modeled open-circuit voltage U can also be considered by means of a correction variable, such as, for example, by multiplicationocvAlternative possibilities for loading.
In step S18, the corrected no-load voltage U is correctedkorrAccording to the corrected open-load voltage U by means of a provided distribution model 54korrCalculating a current calculated state of charge SOC from the state of aging SOH and the battery temperature Tcalc. Such a calculated state of charge SOCcalcFor subsequent vehicle functions.
The correction model in the correction block 55 is based in particular on the calculated state of charge SOCcalcTo output a correction variable K, wherein K has a continuous and differentiable profile with respect to the calculated state of charge and, in particular, has a value which does not change and, in particular, does not increase the modeled no-load voltage U from the battery model 53, in particular, when the modeled state of charge is 100%ocvSo as not to provide said no-load voltage UocvIs larger than the physically largest possible value of the open circuit voltage.
Fig. 6a and 6b show, for example, the dependence on the calculated state of charge SOCcalcFor the variation curve of the correction value K. In fig. 6a may beA linear profile of the correction variable K is seen and a non-linear profile of the correction variable K is seen in fig. 6 b. The correction variable K corresponds to a residual voltage difference, which is determined from the correction characteristic curve and is added to the modeled residual voltage U in accordance therewithocvThe above.
The correction characteristic curve corresponds to a parameterisable function which tends towards zero towards 100% of the modeled state of charge, in order thus not to increase the maximum open circuit voltage beyond the physically maximum possible value. In the case of the correction characteristic curve of fig. 6a, when the calculated state of charge is below 100%, the correction characteristic curve is determined as a linear curve which outputs an open-load voltage difference of 0 when the calculated state of charge is 100%, and for the current value of the calculated state of charge outputs a value of the open-load voltage difference which corresponds to the measured open-load voltage UmessWith modelled no-load voltage UocvThe difference of (a). The correction characteristic curve thus ascertained is now used to correct the modeled open-load voltage until a further deviation occurs between the reference state of charge and the state of charge SOC calculated in motor vehicle 4.
As shown in fig. 6b, the method is similarly performed with a known functional relationship in the case of non-linearity. In principle, the characteristic curve can be freely selected, as long as it is continuous and differentiable and has a value at a state of charge value of 100%, which does not change the modeled open-circuit voltage Uocv。
The characteristic curve shown at the present time shows the offset correction value. For the correction variable to be applied in a multiplied manner, this corresponds to a factor of 1 when the calculated state of charge is 100%.

Claims (17)

1. For ascertaining a calculated state of charge (SOC) of a battery (41) of a battery-driven machine (4)calc) The method of (1); the method comprises the following steps:
-providing (S1) an operating variable (F) of the battery (41);
-providing the state of charge (SOC) calculated in the machine (4) by means of a distribution model (54)calc) The distribution model (54) being dependent on the modeled no-load voltage (U) of the battery (41)ocv) To explain the calculated state of charge (SOC)calc）；
-ascertaining (S3) a reference state of charge (SOC) from the operating variable (F) by means of a reference state of charge model (52)ref) Wherein the reference state-of-charge model (52) is trained in order to specify the reference state-of-charge (SOC) as a function of the operating variable (F) and in particular as a function of a predefined state of aging (SOH)ref）；
According to a reference state of charge (SOC)ref) And the calculated state of charge (SOC)calc) Difference of (c) versus modeled no-load voltage (U)ocv) Performing (S4, S5) a correction to the corrected no-load voltage (U)korr) Ascertaining the calculated state of charge (SOC) by means of the distribution model (54)calc）。
2. Method according to claim 2, wherein the modeled no-load voltage (U) is ascertained from the operating variable (F) by means of a characteristic field-based or data-based battery model (53)ocv）。
3. Method according to any of claims 1 to 2, wherein the reference-state-of-charge model (52) is implemented outside the machine in a central unit (2), wherein the operating parameters (F) of the battery (41) are transmitted by the relevant machine (4) to the central unit (2).
4. The method of claim 3, wherein the reference-state-of-charge (SOC) is determinedref) To the machine (4), or to transmit a trigger signal (TR) to the machine (4), said trigger signal being dependent on the reference state of charge (S)OCref) And the calculated state of charge (SOC)calc) And the comparison therebetween.
5. The method according to one of claims 1 to 4, wherein the reference state of charge model (52) is formed on the basis of data and ascertained from targeted measurements for a plurality of batteries (41) using training data.
6. Method according to claim 5, wherein the state of aging (SOH) is ascertained in the central unit (2) by means of an aging-state model (51) and the state of aging (SOH) is provided, in the reference-state-of-charge model (52), in order to ascertain the reference-state-of-charge (SOC)ref) Taking into account the aging state.
7. Method according to any one of claims 1 to 6, wherein said correction is carried out according to a correction-characteristic curve that depends on the calculated state of charge (SOC)calc) Providing a correction variable (K), wherein the modeled residual voltage (U) is added or multipliedocv) Loading the correction variable (K).
8. The method of claim 7, wherein said reference-state of charge (SOC) is based onref) And said calculated state of charge (SOC)calc) To update the correction-characteristic curve by determining the difference by: parameterizing a predefined functional relationship of the correction characteristic curve by means of an evaluation point which is dependent on the current state of charge (SOC)calc) And the reference-state-of-charge (SOC)ref) And the calculated state of charge (SOC)calc) The difference between them.
9. Method for operating a central unit (2), the central unit (2) being used to provide a reference for a battery (41) of a battery-operated machine (4)State of charge (SOC)ref) In particular for use in a method according to any one of claims 1 to 7, having the steps of:
-receiving an operating parameter (F) of the battery (41);
-ascertaining a reference state of charge (SOC) of the battery (41) with a reference-state of charge model (52) based on the operating variable (F) of the battery (41)ref）；
-comparing said reference-state of charge (SOC)ref) To the machine (4) or to transmit a trigger signal (TR) to the machine (4), said trigger signal being dependent on the reference state of charge (SOC)ref) With the calculated state of charge (SOC) received from the machine (4)calc) To ascertain the result of the comparison therebetween.
10. Method for operating a battery-driven machine (4) in order to ascertain a calculated state of charge (SOC) of a battery (41) in the machine (4)calc) The method has the following steps:
-ascertaining (S11) the modeled no-load voltage (U) by means of a battery model (53)ocv）；
The state of charge (SOC) calculated from the calibration characteristic curvecalc) To correct (S16) said modeled no-load voltage (U)ocv) Wherein the correction characteristic curve is based on the calculated state of charge (SOC)calc) To provide a correction variable (K);
-feeding said modeled no-load voltage (U)ocv) Loading (S17) the correction variable (K);
-according to said corrected no-load voltage (U)korr) Ascertaining (S18) the calculated state of charge (SOC) by means of a predefined allocation model (54)calc）。
11. The method of claim 10, wherein the method is based on a reference state of charge (SOC)ref) Or trigger signal (TR)) To update the correction-characteristic curve by: parameterizing a predefined functional relationship of the correction characteristic curve by means of an evaluation point, which depends on the current state of charge (SOC)calc) And the reference-state-of-charge (SOC)ref) And the calculated state of charge (SOC)calc) The difference between them.
12. For ascertaining the state of charge (SOC) of a battery (41) of a battery-driven machine (4)calc) Wherein the system has a plurality of machines (4) and a central unit (2), wherein the system is configured for:
-providing an operating parameter (F) of the battery (41);
-providing a state of charge (SOC) calculated in the machine (4) by means of a distribution model (54), the distribution model (54) depending on the modeled no-load voltage (U) of the battery (41)ocv) Illustrating the calculated state of charge (SOC)calc）；
-ascertaining a reference state of charge (SOC) from the operating variable (F) by means of a reference state of charge model (52)ref) Wherein the reference state-of-charge model (52) is trained in order to specify the reference state-of-charge (SOC) as a function of the operating variable (F) and in particular as a function of a predefined state of aging (SOH)ref）；
According to a reference state of charge (SOC)ref) And the calculated state of charge (SOC)calc) Difference of (c) to the modeled no-load voltage (U)ocv) Correction is carried out in order to obtain a corrected open-circuit voltage (U)korr) Ascertaining the calculated state of charge (SOC) by means of the distribution model (54)calc）。
13. Device, in particular data processing unit (21) in a central unit (2), for providing a reference state of charge (SOC) for a battery (41) of a battery-driven machine (4)ref) Wherein the clothes areIs configured for:
-receiving an operating parameter (F) of the battery (41);
-ascertaining a reference state of charge (SOC) of the battery (41) with a reference-state of charge model (52) based on the operating variable (F) of the battery (41)ref）；
-converting said reference-state of charge (SO)Cref) To the machine (4) or to transmit a trigger signal (TR) to the machine (4), said trigger signal being dependent on the reference state of charge (SOC)ref) And the calculated state of charge (SOC) received from the motor vehicle (4)calc) To ascertain the result of the comparison therebetween.
14. Control unit (43) in a device, in particular a battery-driven machine (4), for ascertaining a calculated state of charge (SOC) of a battery (41) in the machine (4)calc) Wherein the apparatus is configured to:
-ascertaining the modeled no-load voltage (U) by means of a battery model (53)ocv）；
The state of charge (SOC) calculated from the calibration characteristic curvecalc) To correct said modelled no-load voltage (U)ocv) Wherein the correction characteristic curve is based on the calculated state of charge (SOC)calc) To provide a correction variable (K);
-feeding said modeled no-load voltage (U)ocv) Loading the correction variables (K);
-ascertaining the calculated state of charge (SOC) from the corrected no-load voltage by means of a distribution model (54)calc）。
15. Use of the device according to claim 14 in motor vehicles, electric bicycles, aircraft, in particular unmanned planes, machine tools and/or household appliances.
16. Computer program product comprising instructions which, when the program is executed by at least one data processing means, cause the data processing means to carry out the steps of the method according to any one of claims 1 to 11.
17. A machine-readable storage medium comprising instructions which, when executed by at least one data processing mechanism, cause the data processing mechanism to perform the steps of the method according to any one of claims 1 to 11.
CN202111122856.2A 2020-09-24 2021-09-24 Method and device for determining the state of charge of a battery in a battery-operated machine Pending CN114252779A (en)

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