Method for sorting batteries, battery, battery recycling system and motor vehicle

Abstract

According to the invention, during operation of a battery (1), a plurality of safety-related and service life-related operating parameters are detected for at least one battery cell (4) of the battery (1). A classification parameter (SoR) is then determined by means of a two-stage evaluation of at least one of the operating parameters and / or a calculation parameter derived therefrom. In this case, a safety parameter is derived for at least one safety-related operating parameter in a first stage and compared with a corresponding threshold value, and in the case of a fall below the threshold value or, if necessary, one of a plurality of threshold values, a fault prognosis is generated in a second stage using the plurality of service life-related operating parameters. The classification parameter (SoR) is then determined based on the fault prognosis.

Description

Technical Field

[0001] The invention relates to a method for sorting batteries with respect to their suitability for further processing. The invention further relates to a battery, in particular a battery for a motor vehicle. The invention further relates to a motor vehicle having such a battery. The invention further relates to a battery recycling system (or battery reuse system). Background Art

[0002] The advancement of the electrification of motor vehicles requires the use of large batteries, especially in terms of their (storage) capacity, especially because customers expect relatively long driving ranges. These batteries are usually composed of a plurality of battery cells (usually called secondary battery cells) combined into battery modules. Most of these are lithium-ion cells, which are currently advantageous due to their energy density.

[0003] Batteries, also called "traction batteries", are designed on the one hand with regard to the achievable range and on the other hand for a service life that is considered to be suitable (usually measured in the number of possible charging cycles). After reaching the end of their service life, the battery can optionally be supplied for a second use, for example as an intermediate storage in a charging station or the like, or can be further utilized by means of material recycling. In particular, in order to avoid damage to the battery, for example to individual cells, or to determine whether the battery should be used again or recycled, it is expedient to monitor and evaluate the battery in this way.

[0004] For example, a recycling mode is known from document CN 106324516 A, in which a battery management system of a battery recognizes whether the battery should be recycled. In this case, the determined battery state and information about the battery are automatically transmitted to a recycling station.

[0005] Document DE 10 2015 110 961 A1 discloses a battery inspection assistance system, which includes a tag having a temperature-sensitive section indicating a temperature change and a load-sensitive section indicating a position change. When inspecting the battery, changes in the temperature of the battery can be identified based on the temperature-sensitive section of the tag, and changes in the load of the battery can be identified based on the load-sensitive section of the tag. Summary of the invention

[0006] The object of the present invention is to improve the sorting of batteries with regard to their suitability for further processing.

[0007] The method according to the invention is used to classify batteries, in particular traction batteries of motor vehicles, with respect to suitability for further (or subsequent, continued) processing. Preferably, the battery has at least one battery cell (in particular a secondary cell, ie a rechargeable cell), preferably a plurality of such battery cells.

[0008] According to the method, during operation of the battery, a plurality of safety-related and service life-related operating parameters are detected for at least one battery cell of the battery. A classification parameter (German: (or classification variable). For this purpose, a safety parameter is derived for at least one safety-related operating parameter in a first phase and compared with a corresponding threshold value. If (the safety parameter) falls below the threshold value or at least one of a plurality of threshold values, a fault prediction is generated in a second phase with the aid of a plurality of service life-related operating parameters. A classification parameter is then determined based on the fault prediction.

[0009] Preferably, if a threshold value or, in particular, one of a plurality of threshold values ​​is exceeded, a recycling category is assigned to the battery, ie, in particular, a recycling recommendation, ie, a recommendation for material recycling of the battery, is issued.

[0010] Failure predictions generated based on service life-related operating parameters are also referred to as “performance” parameters or “durability” parameters, i.e., “performance parameters” or “durability parameters”.

[0011] A two-stage process is used for the classification, in which the safety aspect is taken into account on the one hand and the service life aspect on the other hand, so that a higher or more favorable "solution" can be achieved in a simple manner when considering further processing options. Because if a safety criterion is not met, it is recognized that it has priority over the service life aspect. Therefore, there is no joint consideration or mixing of safety-related and service life-related aspects, which could lead to inaccuracies in the evaluation. Therefore, a higher persuasiveness or effectiveness of the classification is achieved.

[0012] The term "below a threshold value or limit value" is understood here and hereinafter to mean that the difference between the safety parameter (or even the classification parameter) and the threshold value or limit value (or also called limit value) does not change its sign. In contrast, "exceeding" is always understood in this context independently of direction, i.e. the difference changes its sign.

[0013] Preferably, the methods described here and hereinafter are carried out by a battery management system of the battery, by a database provided by the manufacturer of the battery or a system having the battery, preferably a motor vehicle, and / or at a service location downstream of production (eg workshop, recycling company, etc.).

[0014] The conjunction “and / or” is to be understood here and hereinafter to mean in particular that the features connected by means of this conjunction can be designed both together and alternatively to one another.

[0015] In a preferred method variant, in a first phase, a so-called history parameter (as a safety parameter) is determined for at least one battery cell of the battery as a function of at least one safety-relevant operating parameter determined for the battery cell, in particular as a function of temperature, voltage (or an electrical parameter associated therewith), pressure and / or gas concentration of decomposition gases. The history parameter preferably reflects a previous (i.e. existing in the past) operating load of the or the respective battery cell. For example, in particular, changes in the respective operating parameter within the time period between the previous and current classification are included in the history parameter.

[0016] In a preferred method variant, a (so-called) Shannon entropy is determined as a safety parameter, in particular as the above-mentioned history parameter, from at least one safety-relevant operating parameter determined for the battery cell, in particular from the temperature (in particular the “cell temperature”), the voltage, the pressure (in particular the cell internal pressure) and / or the gas concentration of the decomposition gases. For this purpose, preferably a data set is formed for each battery cell and each safety-relevant operating parameter, which preferably reflects the change in the corresponding operating parameter over a period of time between the previous and current classification. Furthermore, a plurality of value ranges are assigned to each operating parameter used and the individual values ​​of the corresponding operating parameter are sorted into the value ranges. For example, four ranges are specified for the temperature, in particular “range A” from a minimum value (e.g. the minimum detected value or a value specified specifically by the manufacturer) to 10 degrees Celsius, “range B” from 10 to 20 degrees Celsius, “range C” from 20 to 30 degrees Celsius and “range D” from 30 degrees Celsius to a maximum value. The number of value ranges is preferably specified by the manufacturer. A probability of occurrence is then preferably assigned to each value range, in particular by dividing the number of individual values ​​in the corresponding value range by the total number of all individual values ​​of the corresponding data set. The Shannon entropy of the corresponding operating parameters (especially the physical parameters considered) is expressed by the following formula:

[0017]

[0018] Here,

[0019] -i: The number of the dataset to consider

[0020] -j: The number of the value range to consider

[0021] -n: The number of defined value ranges

[0022] -pj: the probability of occurrence of the jth value range of the i-th data set

[0023] -a: The base of the logarithm (especially base 10, base 2, or base e).

[0024] Optionally, in addition or alternatively to the above Shannon entropy, at least one of the calculated parameters "health state" or "power state" can also be added to the above safety considerations as a safety parameter, in particular as a history parameter. In this case, the calculated parameter health state is preferably formed according to a weighted combination of one of the following operating parameters or at least two of the following operating parameters, namely internal resistance, internal impedance, internal conductivity, capacitance, voltage, self-discharge rate, number of cycles, operating time of the battery, temperature of the battery cells, charge acceptance, total charge flux, total power flux and total energy flux.

[0025] The determination of the health state is described below by way of example for the total charge flux. However, the method can be used for the other operating parameters mentioned above. In addition, multiple operating parameters can be taken into account in the calculation of the health state by means of a weighting function. For a constant current I within a time t, for the charge flux (or charge quantity) Q:

[0026] Q=I*t(2)

[0027] Since the current is not constant over time, the time-varying current i(t) must be integrated over time (especially over the period between the previous and current classification). In addition, in order to determine the total charge flux, both the charging current and the discharging current must be taken into account, so the magnitude of the time-varying current is used:

[0028]

[0029] By discretizing into m parts, we get:

[0030]

[0031] Since large currents have a stronger effect on the state of health than small currents, the discrete total charge flux is current-weighted by an exponent n. This exponent is determined empirically for each battery cell. Furthermore, it is divided by the average current magnitude to obtain units for the charge flux:

[0032]

[0033] Here we calculate the average current:

[0034]

[0035] The state of health ("SOH") is now given by the following formula:

[0036] SoH=(Q char -Q gew )*100 / Q char (7)

[0037] Where Qchar represents the characteristic total charge flux of the battery.

[0038] Furthermore, high temperatures have a stronger influence on the state of health than low temperatures. Therefore, it is derived from the Arrhenius equation in a simplified manner that the reaction rate doubles with a temperature increase of 10 K, and therefore the aging rate also doubles ("reaction rate-temperature rule"). Therefore, the weighted charge flux is weighted in the formula for the state of health by the influence of the temperature according to the reaction rate-temperature rule and a certain reference temperature Tnenn. In this case, Tnenn is the reference temperature at which aging occurs with a factor of 1:

[0039] SoH=(Q char -(2*(T / 10-T nenn / 10)+1)*Q gew )*100 / Q char (8)

[0040] In an exemplary method variant, the total energy flux is determined from a combination of the energy density of the battery cell and the number of cycles:

[0041] E ges =w zelle *m zelle *n (9)

[0042] E ges =w zelle *V zelle *n (10)

[0043] Among them, Eges represents the total energy flux, wzelle represents the weight or volume energy density of a single cell, mzelle represents the weight of a single cell, Vzelle represents the volume of a single cell, and n represents the number of cycles (n can also take a real value).

[0044] In particular, it is determined based on the history parameters whether, due to impermissible operating states occurring during previous operation of the respective battery cell, there are circumstances which are detrimental to safe further use of the respective battery cell, in particular for use in a motor vehicle.

[0045] In a preferred method variant, the fault prognosis is determined in a second phase for at least one battery cell of the battery using service life-related operating parameters according to a statistical model. The model includes in particular the operating parameters of the battery cell, the number of cycles of the battery cell, the capacity of the battery cell, the total power of the fast charge and / or the mileage of the motor vehicle including the battery.

[0046] In a preferred variant, the failure prognosis is determined in a second phase for at least one battery cell of the battery using service life-related operating parameters, specifically according to a Weibull distribution. The Weibull distribution includes in particular the following operating parameters (specifically preferably their currently determined values), namely the operating duration of the battery cell, the number of cycles of the battery cell, the capacity of the battery cell, the total power of the fast charge and / or the mileage of the motor vehicle including the battery (and in particular in relation to the corresponding characteristic values ​​or typical values ​​for the parameters). The adjusted Weibull distribution specifies the probability of a battery cell failure as a percentage.

[0047] Preferably, the Weibull distribution (especially of two parameters) is determined according to the following formula:

[0048]

[0049] Here:

[0050] t: measured (ie in particular currently accumulated (German: aufgelaufen)) operating time of the battery cell, preferably since the last classification,

[0051] t0: initial operating duration of the battery cell at the start of the observation, ie in particular at the time of the last classification

[0052] - T: characteristic operating time of the battery cell (specified by the manufacturer in the context of the design, e.g. T=5000 h for electric vehicles),

[0053] -n: the measured (especially cumulative) number of cycles of the battery cell,

[0054] -n0: The initial number of cycles of the battery cell at the beginning of the observation,

[0055] - N: characteristic number of cycles of the battery cell (specified by the manufacturer in the context of the design, e.g. N=1000 for a typical lithium-ion battery),

[0056] -c: measured capacity of the battery cell,

[0057] -c0: the initial capacity of the battery cell at the beginning of the observation,

[0058] - C: characteristic capacity of the battery cell (specified by the manufacturer in the context of the design, e.g. C = 1000 mAh for a typical lithium-ion battery),

[0059] -p: the total power of fast charging during the observed operation duration,

[0060] -p0: The total power of the initial fast charge at the beginning of the observation.

[0061] -P: total power of the characteristic fast charge (specified by the manufacturer in the design scope),

[0062] -r: the measured (especially accumulated) mileage of the motor vehicle,

[0063] -r0: mileage of the electric vehicle when the battery cell is installed,

[0064] -R: characteristic mileage of the electric vehicle (specified by the manufacturer in the design scope),

[0065] -a, β, γ, κ, ν: weight coefficients determined for different design parameters,

[0066] b: shape factor of the Weibull distribution (for considerations of early failures, the shape parameter b<1 is selected. For considerations of random failures, the shape parameter b=1 is selected, which in particular represents a constant assumed failure rate. For wear and fatigue failures, the shape parameter b>1 is selected).

[0067] In the above variant, the total power quantity p is preferably determined according to the following formula

[0068]

[0069] In particular, it is similar to the total charge determination, where u(t) represents the voltage that varies with time.

[0070] In the first and especially in the second stage, statistical methods are used for the classification, so that the statements that can be made therefrom are advantageously relatively reliable.

[0071] In an expedient development, the fault prognosis of the respective battery cell determined, in particular according to the above-mentioned Weibull distribution, is linked to a value range of the classification parameter according to its value.

[0072] Here, at least the following value ranges are preferably associated with the classification parameter, namely "like new" (e.g. 0 to 5 percent for a prediction of failure; can be used directly in a motor vehicle), "vehicle use" (e.g. 5 to 35 percent for a prediction of failure; indicating that the battery has been used but can still be used in a motor vehicle), "secondary use" (or also "industrial grade"; e.g. 35 to 60 percent for a prediction of failure; indicating that use below the primary purpose of use is recommended) and "recycling" (also called "recycling grade"; e.g. 60 to 100 percent for a prediction of failure; indicating that it is recommended that the battery should be sent for material recycling). These value ranges or "categories" thus indicate the suitability of the battery for disposal. Preferably, corresponding suggestions or instructions are also given to the user of the battery, such as "the battery can be used in the vehicle without restriction", "it is recommended to replace the battery and the battery can be used later" or "it is recommended to replace the battery and send it for recycling".

[0073] In an alternative embodiment to the above-described use of the Weibull distribution, a failure prediction is generated by firstly determining error density functions for the battery cells of a production unit (also called a "batch", "lot" or "batch") statistically based on tests. These error density functions are at least partially "interpreted" with the aid of the Weibull distribution, ie, in particular mapped, so that (in particular in part) a failure rate for the battery cells can be derived, which changes over time depending on the type of failure (early failure, random failure, aging failure) or does not change over time, in particular in the case of random failures. Optionally, the failure rates determined in this way are then either combined (in particular after weighting) or individually added as parameters to a description model for the battery cells (optionally for the battery modules formed therefrom and / or for the traction battery comprising the battery modules). As description models, reliability diagrams, Markov chains, etc. can be used, for example. Subsequently, at least one characteristic value for the reliability and / or failure probability of the respective battery cell (or battery module or traction battery) is derived from the description model parameterized in this way. In this case, one or more characteristic values ​​represent in particular the above-described failure prediction. In particular, the above-mentioned service life-related operating parameters (preferably their currently detected values), preferably the operating duration of the battery cell, the number of cycles of the battery cell, the capacity of the battery cell, the total power of the fast charge and / or the mileage of the motor vehicle including the battery, are also introduced as input parameters into the description model. As described above, the determined fault prognosis of the corresponding battery cell is also assigned a corresponding value range of the classification parameter depending on its value.

[0074] Optionally, for example after authorization by a user or maintenance personnel, the battery is prepared for subsequent use or recycling, in particular by means of corresponding measures stored in the battery management system and / or in a database. Such preparation includes, for example, discharging the battery to a respectively predetermined "residual value", adjusting the temperature to a predetermined temperature value and / or others. In particular, the battery management system is also configured to open the battery and electrical consumers, in particular the "onboard power supply" in a motor vehicle, for example a (high-voltage) circuit breaker between a downstream control device and at least one electric motor, before starting these steps.

[0075] In an expedient, additional method variant, at least one battery cell is assigned a special classification, namely "special waste", on the basis of special events detected during battery operation, which make recycling impossible. This is the case, for example, if complete thermal damage, mechanical damage exceeding a limit value (thus "severe" damage), etc., is detected for the respective battery cell.

[0076] The classification of the batteries (or the respective battery cells) described here and below preferably takes place at predetermined time intervals and / or at individually selectable times. In the case of individually selectable times, the classification can be triggered by maintenance personnel, for example, within the scope of vehicle maintenance.

[0077] In a further preferred method variant, in particular for the case where the battery comprises, as described above, a plurality of battery cells which form at least one battery module, preferably even a plurality of battery modules, a classification parameter is determined for at least a plurality, preferably for all battery cells. Based on the classification parameter for each of the battery cells, a module classification parameter and a battery classification parameter are then preferably determined.

[0078] Preferably, as described above, the “individual or individual” Shannon entropy is determined for each or at least some of the battery cells according to formula (1). The arithmetic mean is then derived from this:

[0079]

[0080] Here:

[0081] -i: The number of the observed Shannon entropy

[0082] -Ei: Shannon entropy of the i-th data set of the observed physical parameter

[0083] -m: The number of all datasets.

[0084] In particular, the standard deviation of all Shannon entropies of the data set (in particular for the data detected during the observation time) is determined from this:

[0085]

[0086] From this, a so-called outlier coefficient Ai is then preferably derived for each individual data set.

[0087] A i =|E i -E|σ E (15)

[0088] The outlier factor is in particular a measure of how many standard deviations a Shannon entropy deviates from the mean value of all Shannon entropies. This outlier factor and optionally additionally or alternatively the standard deviation are advantageously used to determine statistical outliers in the measured data of the observed physical parameter with less effort and even preferably exclude them from the above considerations.

[0089] Preferably, a percentage distribution is formed from the individual classification parameters of the battery cells for the individual classifications of the respective battery modules and / or batteries. The distribution thus indicates in particular the percentage of the respective battery modules or batteries which are still suitable for vehicle use, the percentage which are to be used a second time, and the percentage which are to be recycled. Optionally, this distribution is again compared with a boundary distribution and classified based on this comparison. For example, a smaller percentage of the battery cells for secondary use may be accepted for further vehicle use.

[0090] It is further optional to additionally take into account the number of warning messages that occurred during operation when classifying a battery module or a whole battery, in particular to take them into account in a weighted manner. For example, the weighting can increase as the number of classes that differ from vehicle use, in particular "worse" classes, increases in the battery modules or batteries, so that as the distribution of the individual "cell classes" tends more and more towards secondary use, fewer and fewer warning messages are sufficient to set the "overall class" of the battery (or battery module) to a "worse" class, i.e., for example from vehicle use to secondary use.

[0091] In a further advantageous method variant, the battery is specifically provided with information about the manufacture and / or design of at least one contained battery cell, about the limits of safety-related and / or service life-related operating parameters and / or about measures for initiating downstream use and / or recycling. Preferably, this information is stored in the above-mentioned database and / or battery management system after manufacture, in particular by the manufacturer. In particular, in order to be able to retrieve this information in a simple manner during assembly of the battery, optionally even during manufacture of the battery from one or more battery cells, a barcode is provided for the respective battery cell, a battery module consisting of a plurality of battery cells and / or even the battery itself, which barcode contains this information and / or a link to a database for retrieving this information.

[0092] For example, the information includes information on the cell identification number and, if applicable, the module number, the battery number and, optionally, the vehicle identification number, the cell chemistry used for the battery cell, the manufacturer's identification number, the manufacturer-specified permissible (or characteristic) number of cycles for the first use, second use and end of service life ("end of use") of the respective battery cell, the manufacturer-specified permissible range (mileage) for the first use as a motor vehicle battery, the manufacturer-specified permissible operating duration for the first use, second use and end of service life (either as a total operating duration or as separate data for storage, rest and use times), the manufacturer-specified the permitted charge flux for first use, second use and at the end of service life, the recycling method to be used (e.g. recycling steps or recycling methods), an indication of hazardous substances, the total energy flux permitted by the manufacturer for first use, second use and at the end of service life, the total power flux permitted by the manufacturer for first use, second use and at the end of service life, the operating duration permitted by the manufacturer outside the permitted operating voltage window and / or the permitted operating temperature window of the battery cell for first use, second use and at the end of service life, the discharge method to be used before starting recycling, the nominal weight and / or the production date or molding date of the battery cell.

[0093] The battery according to the invention is particularly designed and equipped for use in a motor vehicle (optionally an electric bicycle, a scooter, a water vehicle, etc.). In this case, as described above, the battery has at least one battery cell (preferably a plurality of battery cells combined to form a battery module) and a battery management system. The battery management system is configured to detect a plurality of safety-related and service life-related operating parameters for at least one battery cell of the battery during operation of the battery and to provide them to a controller of the battery management system and / or to the aforementioned database external to the battery or the motor vehicle in order to carry out the above method.

[0094] In an expedient embodiment, the battery management system, in particular its controller, is configured to exclude individual battery cells or battery modules which are no longer suitable for further vehicle use according to the above classification from a cell string of a plurality of battery cells or a module string of a plurality of battery modules in a battery module. For this purpose, the battery is advantageously equipped with a corresponding switching device in order to be able to disconnect the individual battery cells or battery modules from the corresponding circuit. In this case, the battery is thus "reconfigured".

[0095] In another suitable design, the battery management system is configured to transmit the current operating parameters and the parameters derived therefrom to the database for updating, especially for the case where the information is transmitted to an external database. In this case, the current classification parameters are transmitted, especially their distribution, identification features, such as vehicle identification number or module identification number, current number of cycles, current mileage, current charge flux and / or current capacity, current operation duration, current time outside the specified operation window (such as voltage window, temperature window, discharge current window), the type and number of warnings that have appeared and / or vehicle status reports with safety reference significance for the battery (such as accident data, collision data, propagation warning, overheating warning, deep discharge warning, overcharge warning, current overcurrent warning, EMC warning, etc.), the time point of the next classification, the current total energy flux, the current total power flux and / or the current number of fast charging processes. These parameters are also required for classification in the database. Optionally, the battery management system is also configured to call characteristic operating parameters (i.e., their characteristic values) from the database for the corresponding classification, i.e., the characteristic operating parameters specified by the manufacturer for the corresponding battery in particular.

[0096] The battery recycling system according to the invention comprises a database as described above, which contains battery-specific information about the manufacture and / or design of at least one battery cell contained in the battery, about the limits of safety-related and / or service life-related operating parameters and / or about measures for starting the downstream use and / or recycling of the battery cell (especially the main or first use in a motor vehicle). This information is supplied to the database, in particular as described above. The database is also provided for obtaining a plurality of safety-related and service life-related operating parameters for at least one battery cell of the battery from a battery management system of the battery and for carrying out the method as described above, in particular automatically.

[0097] In an expedient embodiment, the database is provided for evaluating measures for initiating downstream use and / or recycling of a plurality of batteries in terms of effort and costs based on the input information and for generating a plan for the full utilization of the facilities for use and / or recycling based on this evaluation. Thus, for example, it is determined how many different batteries with similar classification distribution, chemical composition, etc. are stored in the database and available for further processing. In this case, the database is advantageously provided for grouping the sorted batteries, in particular with regard to their properties and further processing, and for transmitting the corresponding grouping information, for example, to the recycling plant that is geographically closest to the group or at least responsible, the next responsible workshop, etc., in particular for better utilization planning at recycling plants and / or workshops that transform batteries for secondary use.

[0098] Additionally, the database is optionally configured to preferably determine the amount of recycling and / or special waste generated, the recycling or disposal costs, etc. based on the above grouping.

[0099] Furthermore, it is expedient if the database is also provided for, for example, when a motor vehicle with a battery to be recycled arrives at a recycling plant, to optionally automatically transmit information about the recycling steps required for a specific battery to a recycling machine.

[0100] A motor vehicle according to the present invention includes the above-mentioned battery. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] The embodiments of the present invention are further described below with reference to the accompanying drawings. In the accompanying drawings:

[0102] Figure 1 shows a schematic diagram of a battery having a plurality of battery modules consisting of a plurality of battery cells,

[0103] Figure 2 A schematic diagram showing an information flow diagram of data between a plurality of batteries and a database,

[0104] Figure 3 a schematic diagram showing a diagram of the flow of information between a database and a recycling location for batteries,

[0105] Figure 4 A schematic diagram of a motor vehicle with a battery is shown.

[0106] Corresponding parts (and parameters) are always provided with the same reference symbols in all the figures. DETAILED DESCRIPTION

[0107] Figure 1 The motor vehicle 2 is shown in Figure 4 ) is a traction battery, also called a battery pack, referred to as a "battery 1" for short. The battery 1 comprises a plurality of individual battery cells, which are designed as secondary battery cells (i.e. rechargeable battery cells) and are referred to as "cells 4" for short. A plurality of cells 4 are arranged in a common module housing 6, whereby they are combined to form a battery module 8. The interconnection of the individual cells 4 is not shown in detail. The battery 1 comprises a battery housing 10, in which a plurality of battery modules 8 are arranged and are also connected to one another, which is likewise not shown in detail.

[0108] In order to determine the current operating parameters of each cell 4, a sensor unit 12 is assigned to each cell 4. The sensor unit is provided for detecting the current temperature T of the respective cell 4, the current pressure in the cell 4, and optionally the gas concentration of the decomposition gases of the medium contained in the respective cell 4. A sampling rate of approximately one-thirtieth of a Hertz is sufficient. The resolution of the individual sensor signals should be in the range of 1 Kelvin, 10 kPa or 1 ppm of dissolved gas.

[0109] The battery 1 also includes a battery management system 14, which constitutes a controller, which is also configured to determine the electrical operating parameters of the individual cells 4, namely the current voltage (preferably with a resolution of 1 volt), the charging and discharging current, the total charge flux QG, the current (storage) capacity c, and other operating parameters, such as the cumulative operating duration of the corresponding cell, the number of charging cycles performed n, the total power of the fast charge, the current mileage r of the motor vehicle 1, etc.

[0110] Furthermore, the battery management system 14 is configured to automatically carry out a method for classifying the battery 1 with respect to its suitability for further processing. To this end, the battery management system 14 determines the Shannon entropy for each operating parameter and for each cell 4 in a first evaluation phase based on the data of the corresponding sensor unit 12 and the current voltage within a predetermined period of time.

[0111] If the Shannon entropy exceeds a predefined threshold value, the battery management system 14 outputs the classification “recovery level” for this cell 4 and terminates the further evaluation of this cell 4 .

[0112] If all Shannon entropies are below the corresponding threshold value, the battery management system 14 transitions to the second evaluation phase. In this second evaluation phase, the battery management system 14 determines the Weibull distribution for each cell using the accumulated operating time, the accumulated number of charging cycles, the current and original capacity, the accumulated total power of fast charging and the accumulated mileage. In this case, the corresponding parameters are associated with their (manufacturer-specific) characteristic quantities, i.e., quantities that occur when used in accordance with regulations.

[0113] The Weibull distribution for each cell 4 indicates the failure prognosis, i.e. the probability of failure (in percentage). Classifications are then assigned according to a predetermined pattern, which are based on the value ranges of the Weibull distribution. These classes indicate whether the respective cell 4 is (almost) new, suitable for further use in a motor vehicle 2 (automotive grade), recommended for secondary use (e.g. as a temporary storage in industry) (industrial grade), or whether it is sent for material recycling (recycling grade).

[0114] According to the classification of the single battery 4, the battery management system 14 generates a classification distribution of the battery modules 8 and the battery 1, and then judges based on this, specifically judging whether to replace only one battery module 8 or the entire battery 1 according to the threshold comparison.

[0115] For redundancy or decommissioning of the detected operating parameters and optionally even a classification, the battery management system 14 is configured to transmit the above-mentioned sensor data and operating parameters and, if necessary, even a classification of the cells 4 to a database 20 (see Figure 2 ). The database 20 is arranged on a server 22, which is accessible to a plurality of battery management systems 14 and can therefore aggregate information on a plurality of batteries 1. A "client 24" (described in more detail below) is in communication connection with the server 22.

[0116] In order to be able to associate the information of a particular battery 1 for the first time with the records stored on the manufacturer's side in the database 20 or to transfer the information in a simple manner to the database 20 for storage, the corresponding cell 4, battery module 8 and battery 1 are each provided with a barcode 30, which contains a link to the corresponding database record. The database record contains information on the characteristic values ​​of the operating parameters required for the above-mentioned classification, the cell chemistry used, the date of manufacture and the manufacturing plant, etc. In addition, the database record contains the above-mentioned classification, which is determined by the database 20 or determined by the battery management system 14 and then transferred to the database 20.

[0117] Furthermore, the database 20 is provided for estimating the volume of batteries 4 that are no longer recyclable for secondary use, material recovery and, if necessary, landfill or another end use, based on the sorting of the plurality of batteries 1 , as well as the estimated costs for this purpose.

[0118] In particular, the server 22 and the database 20 form a battery recycling system, by means of which the disposal suitability of the batteries 1 (which results from the corresponding classification) is detected.

[0119] If it is now determined for a battery 1 of a specific motor vehicle 1 that this battery 1 is sent for recycling, a corresponding message is output to the user of the motor vehicle 1 (triggered by the database 20 or the battery management system 14). For example, the user can drive to a repair shop to remove the battery 1 and replace it if necessary. If the battery 1 is sent to a recycling plant 32 representing one of the customers 24 (see Figure 3 ), then in the recycling plant, information about the battery 1 and the required recycling process for the specific battery 1 can be retrieved from the database 20 by means of a scanner 34 via the corresponding barcode 30 of the battery 1 or cell 4 or battery module 8. The database 20 transmits this information, for example, to a recycling machine 36 in the recycling plant 32 or at least to a server there. The recycling process here usually depends on the specific cell chemistry and structure of the corresponding cell 4.

[0120] Since information about multiple batteries 1 is concentrated in the database 20, it is also possible and advantageous to provide for the full utilization planning of the recycling plant 32 with the help of the database 20, for example by supplying the same type of batteries 1 to different recycling plants 32 for recycling, so that the same recycling process can be performed on multiple batteries 1 without having to repeatedly switch recycling machines 36 for different types of batteries.

[0121] The content of the present invention is not limited to the above-mentioned embodiments. On the contrary, other embodiments of the present invention can be derived from the above description by those skilled in the art. In particular, the individual features and their design variations described according to different embodiments of the present invention can also be combined with each other in other ways.

[0122] List of reference numerals:

[0123] 1 Battery

[0124] 2 Motor Vehicles

[0125] 4 single pool

[0126] 6 Module housing

[0127] 8 Battery Module

[0128] 10 Housing

[0129] 12 Sensor unit

[0130] 14 Battery Management System

[0131] 20 Database

[0132] 22 Servers

[0133] 24 customers

[0134] 30 Barcode

[0135] 32 Recycling Plant

[0136] 34 Scanner

[0137] 36 Recycling Machine

Claims

1. A method for classifying batteries (1) with respect to their suitability for further processing, wherein: According to this method: - during operation of the battery (1), detecting a plurality of safety-related and service life-related operating parameters for at least one battery cell (4) of the battery (1), - determining a classification parameter (SoR) by means of a two-stage evaluation of at least one of the operating parameters and / or a calculation parameter derived therefrom, in, - in a first phase, a safety parameter is derived for at least one safety-related operating parameter and compared with a corresponding threshold value, - for cases where the threshold value is undershot, in a second phase a fault prediction is generated using a plurality of service life-related operating parameters, and -Determine the classification parameters based on the failure prediction (SoR) In a first stage, a safety parameter is determined for at least one battery cell (4) of the battery (1) based on at least one safety-related operating parameter determined for the battery cell (4), namely based on temperature, voltage, pressure and / or gas concentration of decomposition gases, wherein the safety parameter characterizes the previous operating load, and in a second stage, the failure prognosis is determined for at least one battery cell (4) of the battery (1) with the aid of service life-related operating parameters based on a statistical model, wherein the model includes the following operating parameters, namely the operating duration of the battery cell (4), the number of cycles of the battery cell (4), the capacity of the battery cell (4), the total power of fast charging and / or the mileage of the motor vehicle (2) including the battery (1), and wherein the failure prognosis of the battery cell (4) or each battery cell (4) is assigned to a value range of a classification parameter (SoR) based on its value.

2. The method according to claim 1, in, The classification parameter (SoR) is assigned at least the following value ranges: "as new", "vehicle use", "secondary use" and "recycled".

3. The method according to claim 1, in, At least one battery cell (4) is assigned a special classification, namely "special waste", based on a special event detected during operation of the battery (1), which makes recycling impossible.

4. The method according to claim 1, in, The battery (1) comprises a plurality of battery cells (4) which form at least one battery module (8), wherein a sorting parameter (SoR) is determined for at least a plurality of the battery cells (4), and wherein a module sorting parameter and a battery sorting parameter are determined as a function of the respective sorting parameter (SoR).

5. The method according to claim 1, in, The battery (1) is specifically provided with information about the manufacture and / or design of at least one contained battery cell (4), about limits of safety-related and / or service life-related operating parameters and / or about measures for initiating downstream use and / or recycling.

6. The method according to claim 1, wherein: For the case where one of a plurality of threshold values ​​is undershot, a fault prognosis is generated in a second phase using a plurality of service life-related operating parameters.

7. A battery (1), comprising: At least one battery cell (4) and a battery management system (14), which is configured to detect a plurality of safety-related and service life-related operating parameters for at least one battery cell (4) of the battery (1) during operation of the battery (1) and to provide them to a controller of the battery management system (14) and / or to an external database (20) in order to execute a method according to one of claims 1 to 6.

8. The battery (1) according to claim 7, wherein: The battery (1) is a battery for a motor vehicle.

9. A battery recycling system (20, 22), comprising a database (20) containing battery-specific information about the manufacture and / or construction of at least one battery cell (4) contained in the battery (1), about the limits of safety-related and / or service life-related operating parameters and / or about measures for initiating downstream use and / or recycling of the battery cell (4), wherein: The database (20) is configured to obtain a plurality of safety-related and service life-related operating parameters for at least one battery cell (4) of the battery (1) from a battery management system (14) of the battery (1) and to carry out a method according to one of claims 1 to 6.

10. The battery recycling system (20, 22) according to claim 9, in, The database (20) is configured to evaluate measures for initiating downstream use and / or recycling of a plurality of batteries (1) in terms of effort and costs based on the input information and to generate a utilization plan for the system for use and / or recycling based on the evaluation.

11. A motor vehicle (2) comprising a battery (1) according to claim 7.

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