Method, computer program product and prognosis system for determining the working life of a traction battery of a vehicle

Abstract

The present disclosure relates to a method for determining the working life of a traction battery of a boat, including the steps of determining a system configuration and/or operating conditions of the boat, providing a traction battery model, which states an ageing condition of the traction battery as time progresses depending on the system configuration and/or operating conditions determining at least one condition that confirms the end-of-life condition of the traction battery has been reached and calculating the time-period until the end-of-life condition is reached on the basis of the traction battery model.

Claims

1. A method for determining a working life of a traction battery of a boat, comprising: determining, by at least one processor and based on a received envisaged region of use of the boat, climate conditions of the received envisaged region of use to determine operating conditions of the boat; calculating, by the at least one processor and based on a traction battery model comprising a mathematical model, an ageing condition of the traction battery as time progresses depending on the operating conditions; determining, by the at least one processor, at least one condition that confirms an end-of-life condition of the traction battery has been reached; and calculating, by the at least one processor and on a basis of the ageing condition determined by the traction battery model comprising the mathematical model, a time period until the at least one condition is reached.

2. The method according to claim 1, wherein determining of the operating conditions comprises a determination of one or more a temperature prevailing in the traction battery, a temperature limit, or of operating cycles.

3. The method according to claim 1, wherein determining of the at least one condition comprises a determination of a threshold value for the ageing condition upon reaching of which the end-of-life condition of the traction battery exists, wherein calculating of the time period until the end-of-life condition is reached determines at what point in time the threshold value is reached.

4. The method according to claim 1, wherein the operating conditions are recorded during one or more of the working life of the traction battery and the traction battery model or the operating conditions are adjusted on the basis of recorded operating conditions.

5. The method according to claim 1, wherein a parameter of the operating conditions is divided into different value ranges and total operating time of the traction battery is recorded in each operating condition determined by value ranges over the working life of the traction battery.

6. The method according to claim 1, wherein calculating the ageing condition comprises: determining, by the at least one processor, a system configuration by determining one or more of a number of traction batteries, a battery type, an interconnection of traction batteries, a number of interconnections of battery cells within the traction battery, a type and number of consumers, or a charger for the traction battery; and calculating, by the at least one processor and based on the traction battery model comprising the mathematical model, the ageing condition of the traction battery as time progresses depending on one or more of the system configuration or the operating conditions.

7. The method according to claim 6, where the battery type and the number of consumers comprises one or more of a propulsion engine or further consumers.

8. The method according to claim 1, wherein the traction battery model includes at least one parameter relating to the ageing condition of the traction battery as a function of time on the basis of the operating conditions.

9. The method according to claim 8, wherein the at least one parameter is one or more of a specific value for the ageing condition, an internal resistance, a useable capacity, a clamping voltage, a self-discharge feature, or a number of charging/discharging cycles of the traction battery.

10. The method according to claim 9, wherein the specific value for the ageing condition states the useable capacity relative to a starting capacity of the traction battery.

11. The method according to claim 10, wherein the specific value for the ageing condition states the useable capacity relative to the starting capacity of the traction battery under stipulation of a constant continuous discharge performance.

12. The method according to claim 1, wherein the traction battery model states a value range for the ageing condition.

13. The method according to claim 12, wherein the traction battery model states the value range for the ageing condition for at least one parameter depending on time.

14. The method according to claim 12, wherein a width of the value range increases as time progresses.

15. The method according to claim 8, wherein the ageing condition or the at least one parameter is measured at the traction battery during the working life of the boat at specific points in time, and is compared with values determined by the traction battery model—at these points in time, and the traction battery model—is adjusted on the basis of this comparison.

16. The method according to claim 15, wherein the ageing condition stated by the traction battery model or the at least one parameter is measured at one or more of the traction battery during a charging process, maintenance of the traction battery or following expiry of the working life.

17. A computer program product with a program code stored on a non-transitory machine-readable data carrier for carrying out the program code, the computer program product executed by a data processing system to: determine, based on a received envisaged region of use of a boat, climate conditions of the received envisaged region of use to determine operating conditions of the boat; calculate, based on a traction battery model comprising a mathematical model, an ageing condition of a traction battery as time progresses depending on the operating conditions; determine at least one condition that confirms an end-of-life condition of the traction battery has been reached; and calculate, on a basis of the ageing condition determined by the traction battery model comprising the mathematical model, a time period until the at least one condition is reached.

18. A prognosis system for determining a working life of a traction battery of a boat comprising: at least one processor; and at least one storage medium having encoded thereon executable instructions that, when executed by the at least one processor, cause the at least one processor to carry out a method, the method comprising: determining, based on a received envisaged region of use of the boat, climate conditions of the received envisaged region of use to determine operating conditions of the boat; calculating, based on a traction battery model comprising a mathematical model, an ageing condition of the traction battery as time progresses depending on the operating conditions; determining at least one condition that confirms an end-of-life condition of the traction battery has been reached; and calculating, on a basis of the ageing condition determined by the traction battery model comprising the mathematical model, a time period until the at least one condition is reached.

19. The prognosis system according to claim 18, wherein: the at least one storage medium is encompassed on a web server; and the at least one processor is designed for accessing the web server to operate in a decentralized way to implement the executable instructions stored on the at least one storage medium and access the web server.

Description

BRIEF DESCRIPTION OF THE FIGURES

(1) Specific non-limiting embodiments of the present disclosure are explained in more detail with reference to the description of the following Figures. These show schematically:

(2) FIG. 1 is a schematic of an electric drive system of an electrically driven boat and a prognosis system for determining the working life of a traction battery of the drive system;

(3) FIG. 2 is a flow chart of a method to be carried out with the prognosis system for determining the working life of the traction battery;

(4) FIGS. 3, 4, and 5 are diagrams illustrating parameters and specific values calculated with the method for the ageing condition of the traction battery as time progresses;

(5) FIG. 6 presents an embodiment of the traction battery model; and

(6) FIG. 7 is a diagram of a high-level architecture for implementing processes in accordance with aspects of the present disclosure.

(7) While the above-identified drawings set forth presently disclosed embodiments, other embodiments are also contemplated, as noted in the discussion. This disclosure presents illustrative embodiments by way of representation and not limitation. Numerous other modifications and embodiments can be devised by those skilled in the art which fall within the scope and spirit of the principles of the presently disclosed embodiments.

DETAILED DESCRIPTION

(8) Non-limiting examples of the present methods and systems will be described as follows with reference to the Figures.

(9) FIG. 1 schematically shows an electric drive system 10 in the form of an outboard engine of a boat. The electric drive system 10 comprises a traction battery 12, which is connected with a propulsion engine 16 driving a ship's propeller 14 and further electric consumers of the electric drive system 10 not shown here and supplies these with electric energy. The traction battery 12 is disconnectably fitted in a housing 18 of the electric drive system 10. The drive system 10 further comprises a battery management system 20 connected with a display mounted on the electric drive system 10 to be visible for a user and designed for calculating specific values of the traction battery 12, such as for example a current ageing condition, i.e. a serviceability (abbreviated: SOH value) of the traction battery 12, a provisional or remaining working life of the traction battery 12, a charging condition of the traction battery 12 (abbreviated: SOC value) etc., and to display these on the display.

(10) The drive system has an interface 22, via which the traction battery 12 can be connected with a charger 24 for electrical charging. The charger 24 is designed for measuring at least one parameter of the traction battery 12 relating to the ageing condition 12 and for transmitting the measured values for the parameter together with a point in time for the respective measurement to the battery management system 20 via the interface 22. The charger 24 is especially designed for measuring an internal resistance of the traction battery 12, which increases with an advancing ageing condition of the traction battery 12.

(11) The interface 22 is further equipped for connecting the drive system 10 with a measuring unit 26, which is equipped for calculating at least one parameter or specific value displaying the current ageing condition, and for transmitting the values calculated in this way to the battery management system 20. More precisely the measuring unit 26 is equipped for measuring a useable capacity and an internal resistance of the traction battery 12 and for transmitting the same together with a point in time of the measurement to the battery management system 20 via the interface 22. This can for example take place in that the measuring unit 26 first completely charges the traction battery 12 and then completely discharges the same with a stipulated constant continuous discharge performance. In other words, by measuring a useable capacity the measuring unit 26 can determine an actual state of ageing condition of the traction battery. Alternatively, the measuring unit 26 can be equipped for carrying out another suitable measuring method.

(12) The exchange of information via the interface 22 between the electric drive system 10, in particular the battery management system 20, and the respective charger 24 and the measuring unit 26 is indicated by means of the broken lines 28 in FIG. 1.

(13) A prognosis system 30 is also shown in FIG. 1, which is designed for determining the working life of the traction battery 12. The prognosis system 30 comprises a prognosis unit 32 in the form of a data processing system, which can be connected with the drive system 10 via the interface 22 or a further interface not shown here for exchanging information as indicated in FIG. 1 by means of a broken line 34. The prognosis unit 32 can also be connected with the charger 24 as well as with the measuring unit 26 for exchanging information, as is indicated in FIG. 1 by means of a further broken line 36. More precisely the prognosis unit 32 is equipped for receiving the values measured by the charger 24 and the measuring unit 26 for the parameters relating to the ageing condition of the traction battery 12.

(14) The prognosis system 30 further comprises a web server 38 with a machine-readable data carrier 40, on which a computer program product is stored. The prognosis unit 32 is connected with the web server 38 as indicated by means of a further broken line 42 in FIG. 1, and is equipped for accessing and implementing the computer program product provided on the data carrier 40. The computer program product constitutes a web-based software, which can be accessed by the prognosis unit 32 for carrying out a method for determining the working life of the traction battery 12. In other words, the computer program product comprises a program code stored on the data carrier for carrying out the method for determining the working life of the traction battery when the computer program product is implemented by the prognosis unit 32.

(15) The prognosis unit 32 is in particular a decentralized data processing system, for example in the form of a personal computer, which accesses the web server for carrying out the computer program product. In other words, the prognosis unit 32 is designed for accessing the web server 38 in a decentralized way in order to carry out the computer program product stored on the data carrier 40. This has the advantage that the computer program product, and therefore the method for determining the ageing condition underlying the same, can be centrally administered and adjusted.

(16) With reference to FIG. 2 the method to be carried out by the prognosis unit 32 for determining the working life of the traction battery 12 is explained in more detail as follows. The prognosis unit 32 can here be activated by a user prior to putting into service or during the operation of the traction battery 12 to carry out the method for determining the working life of the traction battery 12. In other words, by executing the method by the prognosis unit 32, the prognosis unit 32 calculates the estimated operating time after which an end-of-life condition of the traction battery 12 is reached.

(17) Due to the high acquisition costs of the traction battery 12 it is known to rent or lease the traction battery 12 when purchasing an electric drive system 10. This can provide a basis for calculating customer- and application-specific financing models in that the prognosis unit 32 calculates an estimated working life of the traction battery 12. The prognosis unit 32 further offers the possibility of an interpretation of the electric drive system, in particular the traction battery, that is fit for use and cost-optimized.

(18) In the method shown in FIG. 2 an application- and customer-specific calculation of the time period until the end-of-life condition is reached is carried out. This is ensured in that the calculation of the method is carried out with reference to a system configuration and operating conditions of the boat or the electric drive system 10. The method consequently comprises a first step S1 of determining a system configuration and operating conditions of the boat.

(19) In the present embodiment example this is realized by entering data concerning the system configuration and the operating conditions into the prognosis unit 32. The prognosis unit 32 comprises a graphic user interface and an input means for this, via which the user enters the data concerning the system configuration and the operating conditions into the prognosis unit 32.

(20) An entry of data by the user takes place with regard to the system configuration to be determined in step S1: The number of traction batteries 12; the battery type of the respective traction battery 12; the type of interconnection of the drive batteries, for example whether these are interconnected in parallel or in series; the number of interconnection of battery cells within the respective traction battery 12; the features, in particular capacity, and/or the type of the propulsion engine 16; further consumers within the drive system 10, in particular a totaled capacity of the further consumers during the operation of the drive system 10; the charger 24 used for charging the traction battery 24; a maximum current strength induced during charging the traction battery 12 by the charger; and/or a cooling system for cooling the traction battery 12, which ensures a maximum operating temperature of the traction battery 12.

(21) The entry of data by the user also takes place with regards to the operating conditions to be determined in step S1 with regard to: an envisaged region of use or an envisaged place of use of the boat, on the basis of which the prognosis unit determines a temperature profile, i.e. a progression of the temperature over the year; a maximum or minimum temperature to be maintained inside the traction battery 12 through cooling or by means of a heater; an envisaged number of operating cycles; and/or storage conditions of the traction battery 12.

(22) The entry of the envisaged number of operating cycles can be realized in such a way that a respective number of operating cycles is entered by the user for the respective seasons of the year, i.e. spring, summer, autumn and winter. In this way the entry of operating conditions can be simplified for the user, whilst the operating conditions can however be illustrated sufficiently precisely at the same time. The user can for example estimate and enter an average number of operating cycles per week for every season of the year.

(23) In a subsequent step S2 of the method a provision of a traction battery model takes place, which states an ageing condition of the traction battery 12 as time progresses, i.e. depending on time, and depending on the system configuration and/or operating conditions. More precisely the traction battery model is a mathematical model that quantifies an ageing condition of the traction battery 12 depending on the system configuration, operating conditions and operating period. The traction battery model is included in the computer program project. The provision of the traction battery model is consequently realized in that the prognosis unit 32 accesses the web server 38 and the computer program product stored on the same.

(24) In a third method step S3 a calculation of at least one parameter relating to the ageing condition of the traction battery 12 or a specific value as a function of time takes place by means of the traction battery model. This especially takes place on the basis of the system configuration and operating conditions determined in step S1. In the embodiment example shown here the traction battery model calculates a relative capacity as a parameter, as shown in FIG. 3, and an internal resistance of the traction battery 12, as shown in FIG. 4, as time progresses. The relative capacity describes a relationship between a currently available or usable capacity relative to a starting capacity of the traction battery 12, i.e. a capacity prior to its commissioning, whilst stipulating a constant continuous discharge performance. The relative capacity thus forms a specific value for the ageing condition of the traction battery 12.

(25) FIG. 3 especially shows a diagram, in which the relative capacity calculated by the traction battery model is shown as time progresses. The ordinate of the diagram shows the relative capacity in percent and the abscissa of the diagram the operating time in years. As the efficiency of the traction battery 12 decreases with increasing age, the usable and thus the relative capacity of the traction battery 12 falls accordingly, as illustrated in FIG. 3. Intensive use of the traction battery 12 therefore results in a faster decrease in the relative efficiency compared to moderate use.

(26) FIG. 4 shows a corresponding diagram in which the internal resistance of the traction battery 12 calculated by the traction battery model is shown as time progresses. The ordinate of the diagram shows the internal resistance in mΩ and the abscissa of the diagram the operating time in years. An increasing value for the internal resistance here shows an increasing ageing of the traction battery 12. A more intensive use consequently results in a faster increase of the internal resistance compared to a moderate use of the traction battery 12.

(27) As is clear from the diagrams in FIGS. 3 and 4 the traction battery model is equipped for determining a minimum and maximum value for the parameters that can be expected for the respective points in time, which accordingly illustrate a moderate or intensive use of the traction battery 12. In this way the change of the respective parameter for moderate as well as intensive use of the traction battery 12 is illustrated for the user. A value corridor that widens as time progresses or a value range for the parameters is therefore stated. Prognosis-immanent uncertainties during the calculation of the parameters and specific values can also be taken account in this way.

(28) The method further comprises a fourth step S4 of determining at least one condition that confirms the reaching of an end-of-life condition of the traction battery 12. This take place in that the user sets a threshold value for at least one parameter calculated by the traction battery model and transmits this to the prognosis unit 32 via the graphic interface and the input means. The set threshold value is therefore a value that indicates that the traction battery 12 is in an end-of-life condition when the parameter calculated by the traction battery model reaches the threshold value.

(29) In the embodiment example shown here the user sets a threshold value for the relative capacity, i.e. the usable capacity relative to the starting capacity of the traction battery 12 as a condition indicating that the end-of-life condition has been reached. The threshold value set by the user can for example substantially be 87% as indicated by means of a dotted line 44 in FIG. 3. In other words, an end-of-life condition of the traction battery 12 is reached as soon as the actual useable capacity of the traction battery 12 shows a value of 87% of the starting capacity of the traction battery 12 at a stipulated constant discharge current. Alternatively, or additionally the user can set a threshold value for the internal resistance of the traction battery 12 as a condition to indicate that the end-of-life condition has been reached.

(30) In a further step S5 of the method a calculation of the time-period until the end-of-life condition is reached then follows on the basis of the ascertained conditions and the calculated parameters as a function of time. For both moderate and intensive use of the traction battery 12, a time-period until the end-of-life condition is reached, i.e. the specified limit value, is calculated, as shown in FIG. 5.

(31) The prognosis unit 32, is further equipped for calculating a further specific value for the ageing condition, the SOH value, as time progresses on the basis of the previously calculated parameters, in particular the relative capacity and/or the internal resistance and the end-of-life condition status. The calculated SOH value as time progresses is illustrated in the diagram according to FIG. 5. The ordinate of the diagram shows the SOH value in percent, wherein a value of 100% states the starting condition of the traction battery 12, i.e. at the start of its operation or prior to commissioning of the traction battery 12, and a value of 0% the end-of-life condition of the traction battery 12. The abscissa of the diagram shows the operating period in years. Alternatively, different or several SOH values can be calculated on the basis of the respective previously calculated parameters, i.e. the relative capacity and the internal resistance. A first SOH value can for example be determined on the basis of the relative capacity, and a second SOH value on the basis of the internal resistance. For this, special conditions are set for the respective calculated parameters, which indicate that the end-of-lie condition of the traction battery 12 has been reached.

(32) According to the calculated parameters an SOH value each is calculated for the respective points in time of the operating period for moderate as well as for intensive use. In this way a value corridor or value range that widens as time progresses is stated for the SOH value. The time-period until the end-of-life condition is reached varies correspondingly along with the differentiation between moderate and intensive use. As ageing of the traction battery 12 will progress faster with intensive use the working life of the traction battery 12 is correspondingly shorter. As is clear from FIG. 5 the present embodiment example of the method lists an operating period of approximately 8 years for moderate use of the traction battery 12 and an operating period of approximately 6 years as a time-period for reaching the end-of-life condition of the traction battery 12 with intensive use.

(33) The previously described method steps S1 to S5 can be carried out prior to commissioning as well as during the operation of the traction battery 12 for determining the working life, in particular the remaining working life of the traction battery 12.

(34) It is further envisaged in the method for validating and adjusting the working life calculated by the prognosis unit 32 to measure the parameters calculated by the prognosis unit 32 during operation of the traction battery 12, to compare the measured values with the predicted values, and to adjust the method for determination or the traction battery model to the working life on the basis of this comparison.

(35) For this a measuring of the parameters relating to the ageing condition takes place on the traction battery 12 in a method step S6, in particular, of the internal resistance and the useable or relative capacity. The drive system 10 is connected with the charger 24 or the measuring unit 26, which are equipped for measuring the internal resistance of the traction battery 12, for measuring the internal resistance of said traction battery 12. This can for example take place during a charging process. The drive system 10 is correspondingly connected with the measuring unit 26, which is designed for measuring the useable or relative capacity, for measuring the useable capacity of the traction battery 12. Measuring the useable or relative capacity can for example take place during maintenance of the traction battery 12 and/or after the calculated working life has expired. The values measured by the charger 24 and the measuring unit 26 are subsequently transmitted to the battery management system 20 via the interface 22 and stored there with reference to the operating period at the point in time of the measurement. The values measured in this way can also be transmitted to the prognosis unit 32. In a next step the parameters measured by the charger 24 and the measuring unit 26 for the values of the ageing condition are compared with the values calculated by the prognosis unit. This takes place by means of the prognosis unit 32.

(36) The battery management system 20 is further designed for measuring and recording operating conditions during the operating period, i.e. the working life of the traction battery 12. The data measured in this way is also described as so-called “logging data”. For this, parameters identifying operating conditions such as for example a current value, a temperature and the SOC value of the traction battery 12, are first divided into different value ranges as shown in Table 1. The different value ranges here identify different operating conditions of the traction battery 12. Based on this the battery management system 20 is designed for recording a total operating period of the traction battery 12 in each operating condition set by each of the value ranges over the working life of the traction battery 12.

(37) TABLE-US-00001 TABLE 1 Current Temperature SOC <−220 A <−10° C.    <5% −220 . . . −181 A −10 . . . 0° C.  5 . . . 20% −180 . . . −101 A 0 . . . 10° C. 20 . . . 50% −100 . . . 20 A 11 . . . 20° C. 50 . . . 60% −20 . . . 0 A 21 . . . 30° C. 60 . . . 70% 0 . . . 10 A 31 . . . 40° C. 70 . . . 95% 11 . . . 60 A 41 . . . 50° C. 95 . . . 100%  61 . . . 100 A 51 . . . 60° C. >100 A >60° C.

(38) In addition, the battery management system 20 is designed for recording further parameters identifying the operating conditions, in particular, the number of operating cycles, cell temperature, a storage voltage, a discharge degree, a pack voltage and a maximum cell difference, at periodic points in time, for example every 8 hours, also in a switched-off condition of the traction battery 12. The parameters recorded by the battery management system 20 are then made available to the prognosis unit 32.

(39) The prognosis unit 32 is designed for comparing the values recorded by means of the battery management system 20 with the values determined for the operating condition in method step S1.

(40) Based on the above comparisons between the initially determined or calculated parameters and those measured or recorded during operation an adjustment of the traction battery model and/or the determined operating parameters then takes place in a method step S7. This is realized by means of the prognosis system 30. The reliability of the method, and therefore the accuracy of the calculated working life until the end-of-life condition is reached, can be improved in this way.

(41) Following the adjustment of the traction battery model and/or the determined operating parameters in method step S7, method step S5 of calculating the time-period, in particular the remaining time period until the end-of-life condition is reached, can then be carried out once more.

(42) The prognosis unit 32 is further designed for calculating the data and values relating to the parameters identifying the operating conditions provisionally to be recorded by the battery management model on the basis of the traction battery model, and for transmitting these to the battery management system 20. The predicted values relating to the ageing condition and the parameters identifying the operating conditions are thus transmitted to the battery management system 20.

(43) The battery management system 20 further receives the values measured by the charger 24 and the measuring unit 26 for the parameters of the ageing condition relating to the point in time of the measurement. As described before, the battery management system 20 also records the parameters that are characteristic for the operating conditions during operation.

(44) In other words, the respective predicted values as well as the measured or recorded values for the respective parameters during operation of the drive system 10 are therefore available to the battery management system 20. The battery management system 20 is here designed for comparing the values recorded or measured during operation with the calculated values, and to assess on the basis of this comparison whether the time period calculated by the prognosis unit 32 until the end-of-life condition is reached will provisionally be complied with or not. If the number of recorded operating cycles for example exceeds a number of operating cycles predicted by the prognosis unit 32 at a specific point in time during operation, the battery management system 20 will show that an actual use of the drive system 10 is higher compared to an originally planned working life, so that the provisional time period until the end-of-life condition of the traction battery 12 is reached will be shorter than the one calculated by the prognosis unit 32. The battery management system 20 is designed for adjusting the value transmitted by the prognosis unit 32 for the time-period until the end-of-life condition is reached on the basis of this comparison, and for displaying the value adjusted in this way to the user via the display.

(45) The battery management system 20 can further be designed for determining a serviceability of the traction battery 12. The serviceability can, for example, be a range or an operating period for different operating conditions of the boat, such as for example moderate or intensive use. The determination of the serviceability can be carried out on the basis of the calculated or predicted SOH value or the calculated or predicted parameters as time progresses, which are transmitted by means of the prognosis unit 32 and/or on the basis of the parameter measured by means of the charger 24 or the measuring unit 26, in particular the relative capacity and the internal resistance and/or on the basis of the parameters measured or recorded by the drive system 10. The specific serviceability can be displayed to the user of the boat via the display. In other words, the values predicted by the prognosis unit 32 and/or the values measured by the measuring unit 26 and/or the charger 24 can be used by the battery management system 20 for determining a specific value for the serviceability, in particular, a range or an operating period, depending on different operating modes of the boat.

(46) FIG. 6 shows an embodiment of the traction battery model 46 in the form of a block diagram, which comprises an ageing model for the traction battery 12. The traction battery model 46, in particular, comprises a mathematical model 48 in the form of a function or an algorithm, which calculates a first SOH value, SOH.sub.C, relating to a relative capacity of the traction battery 12, and a second SOH value, SOH.sub.R, relating to an internal resistance of the traction battery 12, as time progresses depending on a plurality of input parameters.

(47) The input parameters for the mathematical model 48 are described in more detail as follows with reference to FIG. 6. The mathematical model 48 is provided with the system configuration relating to the boat and the operating conditions relating to use of the boat as indicated by means of the arrow 50 in FIG. 6. This can be realized by means of the prognosis unit 32. Values measured for the relative capacity rC.sub.m and the internal resistance R. of the traction battery 12 are also transmitted to the mathematical model 48 as indicated by means of the arrow 52 in FIG. 6, which are calculated by the charger 24 and/or the measuring unit 26 and transmitted to the traction battery model 46. The values measured during operation of the traction battery 12 for the parameters relating to the ageing condition are read out of the drive system 10 and transmitted to the traction battery model 46 as indicated by arrow 54 in FIG. 6. Values relating to a storage period, a storage voltage, a load current, in particular, a discharge current and a charge throughput, a cell temperature and/or a discharge degree can be measured by the battery management system 20 in this regard and transmitted to the traction battery model 46.

(48) On the basis of these input parameters, the mathematical model 48 calculates the relative capacity rC of the traction battery 12 as time progresses, i.e. rC(t), and transmits this value to a first processing unit 56, which calculates a first SOH value, SOH.sub.c, as time progresses, from the same and issues it for further processing as indicated by arrow 58 in FIG. 6. The values for the relative capacity rC(t) of the traction battery 12 calculated by the mathematical model 48 are then transmitted to a second processing unit 60. The second processing unit 60 further receives a value for the starting capacity C.sub.initial of the traction battery 12, which equals a value for the capacity of the traction battery 12 in a new condition, in particular prior to commissioning, and multiplies the same with the value determined by the mathematical model 48 for the relative capacity rC(t). The values calculated in this way are then transferred to a third and a fourth processing unit 62, 64. The third processing unit 62 calculates a rest capacity of the traction battery 12 as time progresses, i.e. C(t) and, as indicated by arrow 66 in FIG. 6, issues this for further processing. The fourth processing unit 64 however determines a prevailing rest capacity C.sub.actual of the traction battery 12 and issues this as indicated by arrow 68 in FIG. 6.

(49) The mathematical model 48 is further designed for determining an internal resistance increase depending on time, dR(t), on the basis of the input parameters mentioned above, and to transfer the calculated values to a fifth processing unit 70. The fifth processing unit 70 is designed for calculating the second SOH value, SOH.sub.R, as time progresses and for issuing the same for further processing as indicted by arrow 72 in FIG. 6. The values calculated by the mathematical model 48 for the internal resistance increase dR(t) are further transmitted to a sixth processing unit 72. The sixth processing unit 72 then receives an initial internal resistance value R.sub.initial for the traction battery 12, which equals a value for the internal resistance of the traction battery in a new condition, in particular prior to its commissioning, and multiplies this with the values for the internal resistance increase dR(t). The value calculated in this way is transferred to a seventh processing unit 74, which determines the internal resistance of the traction battery 12 as time progresses, R(t), and issues the same for further processing as indicated by arrow 76 in FIG. 6. The values calculated by the sixth processing unit 72 are then transferred to an eighth processing unit 78, which calculates a prevailing internal resistance value R.sub.actual of the traction battery 12 and issues the same for further processing as indicated by arrow 80.

(50) Any suitable computing device can be used to implement the computing devices of the present disclosure (for example, 26, 32, 38) and methods/functionality described herein and be converted to a specific system for performing the operations and features described herein through modification of hardware, software, and firmware, in a manner significantly more than mere execution of software on a generic computing device, as would be appreciated by those of skill in the art. One illustrative example of such a computing device 700 is depicted in FIG. 7. The computing device 700 is merely an illustrative example of a suitable computing environment and in no way limits the scope of the present disclosure. A “computing device,” as represented by FIG. 7, can include a “workstation,” a “server,” a “laptop,” a “desktop,” a “hand-held device,” a “mobile device,” a “tablet computer,” or other computing devices, as would be understood by those of skill in the art. Given that the computing device 700 is depicted for illustrative purposes, embodiments of the present disclosure may utilize any number of computing devices 700 in any number of different ways to implement a single embodiment of the present disclosure. Accordingly, embodiments of the present disclosure are not limited to a single computing device 700, as would be appreciated by one with skill in the art, nor are they limited to a single type of implementation or configuration of the example computing device 700.

(51) The computing device 700 can include a bus 710 that can be coupled to one or more of the following illustrative components, directly or indirectly: a memory 712, one or more processors 714, one or more presentation components 716, input/output ports 718, input/output components 620, and a power supply 724. One of skill in the art will appreciate that the bus 710 can include one or more busses, such as an address bus, a data bus, or any combination thereof. One of skill in the art additionally will appreciate that, depending on the intended applications and uses of a particular embodiment, multiple of these components can be implemented by a single device. Similarly, in some instances, a single component can be implemented by multiple devices. As such, FIG. 7 is merely illustrative of an exemplary computing device that can be used to implement one or more embodiments of the present disclosure, and in no way limits the present disclosure.

(52) The computing device 700 can include or interact with a variety of computer-readable media. For example, computer-readable media can include Random Access Memory (RAM); Read Only Memory (ROM); Electronically Erasable Programmable Read Only Memory (EEPROM); flash memory or other memory technologies; CDROM, digital versatile disks (DVD) or other optical or holographic media; magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices that can be used to encode information and can be accessed by the computing device 700.

(53) The memory 712 can include computer-storage media in the form of volatile and/or nonvolatile memory. The memory 712 may be removable, non-removable, or any combination thereof. Exemplary hardware devices are devices such as hard drives, solid-state memory, optical-disc drives, and the like. The computing device 700 can include one or more processors that read data from components such as the memory 712, the various I/O components 716, etc. Presentation component(s) 716 present data indications to a user or other device. Exemplary presentation components include a display device, speaker, printing component, vibrating component, etc.

(54) The I/O ports 718 can enable the computing device 700 to be logically coupled to other devices, such as I/O components 720. Some of the I/O components 720 can be built into the computing device 700. Examples of such I/O components 720 include a microphone, joystick, recording device, game pad, satellite dish, scanner, printer, wireless device, networking device, and the like.

(55) While the presently disclosed embodiments have been described with reference to certain embodiments thereof, it should be understood by those skilled in the art that various changes may be made and equivalents may be substituted without departing from the true spirit and scope of the presently disclosed embodiments. In addition, many modifications may be made to adapt to a particular situation, indication, material and composition of matter, process step or steps, without departing from the spirit and scope of the present presently disclosed embodiments. Where applicable all individual features illustrated in the embodiment examples can be combined with and/or exchanged for each other without leaving the scope of the present disclosure.