DOUGHERTY THOMAS J (US)
TIEDEMANN WILLIAM H (US)
MILES RONALD C (US)
DOUGHERTY THOMAS J (US)
TIEDEMANN WILLIAM H (US)
| WO2002097456A2 | 2002-12-05 |
| JPH117985A | 1999-01-12 | |||
| US20030008201A1 | 2003-01-09 |
WHAT IS CLAIMED IS:
1. A method for determining the internal resistance of a lithium-based battery comprising: (1) calculating the internal resistance of a lithium-based battery that has been used at a first temperature for a first period of time based on the expected increase in the internal resistance of the battery resulting from such use; (2) using the calculated internal resistance of the battery to determine the expected age of the battery if the battery had been held at a second temperature for the entire life of the battery, the second temperature differing from the first temperature; and (3) using the determined expected age of the battery to calculate a new internal resistance of the battery after the battery has been used at the second temperature for a second period of time.
2. The method of claim 1 , wherein the step of calculating the internal resistance of a lithium-based battery that has been used at a first temperature for a first period of time utilizes a formula representative of the relationship between the initial internal resistance of the battery, the temperature of the battery, and the time that the battery is used at the temperature.
3. The method of claim 1 , wherein the step of calculating the internal resistance of a lithium-based battery that has been used at a first temperature for a first period of time utilizes a graph illustrating the relationship between internal resistance and time at a plurality of constant temperatures.
4. The method of claim 1, further comprising using the new internal resistance to determine the expected age of the battery if the battery had been held at a third temperature for the entire life of the battery, the third temperature differing from the second temperature. ι
5. The method of claim 1 , further comprising measuring the initial internal resistance of the battery.
6. The method of claim 1 , further comprising calculating the initial internal resistance utilizing a formula representative of the relationship between internal resistance of a lithium-based battery that has been used at a first temperature for a first period of time, the first temperature, and the first period of time.
7. The method of claim 1, wherein the step of using the determined expected age of the battery to calculate a new internal resistance of the battery after the battery has been used at the second temperature for a second period of time utilizes a formula representative of the relationship between the initial internal resistance of the battery, the second temperature of the battery, the determined expected age of the battery, and the duration of the second period of time.
8. The method of claim 1, wherein the step of using the determined expected age of the battery to calculate a new internal resistance of the battery after the battery has been used at the second temperature for a second period of time utilizes the equation R = R 0 + [A * exp(B/T)]*(to + ti)° 5 , where A and B are constants, R 0 is the initial internal resistance of the battery, T is the second temperature, t 0 is the expected age of the battery if the battery had been held at the second temperature for its entire life, t ! is the duration of the second period of time , and R is the resistance after the second period of time.
9. The method of claim 8, further comprising deriving the values for the constants A and B by holding representative batteries of the same type as the battery at constant temperatures and measuring the increase in resistance.
10. The method of claim 1 , wherein the step of using the calculated internal resistance of the battery to determine the expected age of the battery if the battery had been held at a second temperature for its entire life utilizes a formula representative of the relationship between the initial internal resistance of the battery, the second temperature of the battery, the expected age of the battery, and the calculated internal resistance of the battery.
11. The method of claim 7 or 10, wherein the formula representative of the relationship between the initial internal resistance of the battery, the second temperature of the battery, the expected age of the battery, and the calculated internal resistance of the battery utilizes specific constants for the particular type of battery.
12. The method of claim 11 , wherein the specific constants are derived by holding representative batteries of the particular type of battery at constant temperatures and measuring the increase in resistance.
13. The method of claim 1 , wherein the step of using the calculated internal resistance of the battery to determine the expected age of the battery if the battery had been held at a second temperature for its entire life utilizes the equation to = [(R - Ro)/(A * exp(B/T))] 2 , where A and B are constants, R 0 is the initial internal resistance of the battery, T is the second temperature, to is the expected age of the battery if the battery had been held at the second temperature for its entire life, and R is the calculated internal resistance of the battery.
14. The method of claim 13, further comprising deriving the values for the constants A and B by holding representative batteries of the same type as the battery at constant temperatures and measuring the increase in resistance.
15. The method of claim 1, further comprising repeating steps (2) and (3) of the method in iterative fashion for subsequent temperatures and time periods.
16. The method of claim 15, wherein the step of repeating steps (2) and (3) comprise determining a new expected age from the calculated internal resistance from a previous iteration and using the temperature of the battery during a subsequent iteration and its time at such temperature to calculate the expected internal resistance of the battery at the end of the subsequent iteration.
17. The method of claim 15, wherein iterating the method utilizes the formulas: R n+1 = R 0 + [A * exp(B/T n+1 )]*(t n+1 ) 0 - 5 ; to = [(R n - RoV(A * exp(B/T n+1 ))] 2 ; and t n+1 = to + ti, where R n+1 is the new internal resistance of the battery after its has been used at a constant temperature for a period of time during one iteration, R 0 is the initial internal resistance of the battery, A and B are constants, T n+1 is the temperature of the battery at the current iteration of the method, t n+1 is resultant time or expected age at the temperature T n+1 after the current iteration of the method, to is an expected age of the battery before the current iteration of the method which may be calculated using the internal resistance from the previous iteration of the method R n , and tj is the duration of the current iteration of the method.
18. The method of claim 17, further comprising deriving the values for the constants A and B by holding representative batteries of the same type as the battery at constant temperatures and measuring the increase in resistance.
19. The method of claim 1 , further comprising predicting the status of the battery through correlation to the internal resistance.
20. The method of claim 19, wherein predicting the status of the battery through correlation to the internal resistance comprises determining a resistance level at which the battery is no longer useful and checking to see if the internal resistance of the battery is at or nearing that level. ' |
PROCESS TO MODELAGE FOR LITHIUM ION BATTERIES
STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR
DEVELOPMENT
[0001] The Government of the United States has rights in this invention pursuant to Contract No. DE-FC26-95EE50425 awarded by the U.S. Department of Energy.
CROSS-REFERENCE TO RELATED PATENT APPLICATIONS
[0002] This application claims the benefit of U.S. Provisional Patent Application No. 60/710,053, which was filed on August 22, 2005, the entire disclosure of which is incorporated herein by reference.
BACKGROUND
[0003] The present invention relates to batteries and battery systems. More specifically, the present invention relates to lithium batteries (e.g., lithium-ion batteries, lithium-polymer batteries, etc.) and systems using such batteries that include systems for managing one or more batteries, battery modules, or battery cells when predetermined conditions have been met.
[0004] It is known to provide batteries for use in vehicles such as automobiles. For example, lead-acid batteries have been used in starting, lighting, and ignition applications. More recently, hybrid vehicles have been produced which utilize a battery (e.g., a nickel- metal-hydride battery) in combination with other systems (e.g., an internal combustion engine) to provide power for the vehicle.
[0005] It is generally known that lithium-ion batteries perform differently than nickel- metal-hydride batteries. In some applications, it may be desirable to obtain the enhanced power/performance of a lithium-ion battery. However, the application of lithium-ion battery technology may present design and engineering challenges beyond those typically presented in the application of conventional nickel-metal-hydride battery technology.
[0006] The design and management of a lithium-ion battery system that can be advantageously utilized in a hybrid vehicle may involve considerations such as electrical performance monitoring, thermal management, and containment of effluent (e.g., gases that may be vented from a battery cell). For example, it may be desirable to model the age of a lithium-ion battery (e.g., to predict when the battery will reach the end of its useful life, etc.)
[0007] Lithium-ion battery cells depend upon the free movement of ions. As a result, anything that impedes the movement of ions reduces the utility of a lithium-ion battery cell. Because the internal resistance of a battery cell impedes the movement of ions, the effectiveness of lithium-ion battery cells decreases as their internal resistance increases. When the internal resistance passes a certain threshold, the ions are sufficiently impeded from motion and the cells become unusable.
[0008] Current literature describes the modeling of resistance values of lithium-ion cells using time and temperature as inputs. Current methods, however, do not consider the impact of changing temperatures. In practice, lithium-ion battery cells experience a broad range of temperatures during their useful life. A model that holds temperature constant does little to predict the actual lifetime of lithium-ion cells because rarely, if ever, do lithium-ion cells operate at the same temperature throughout their life.
[0009] Accordingly, it would be advantageous to provide a system and/or method that more accurately models lithium-based batteries or battery systems. It would also be advantageous to provide a system and/or method that takes into account temperature differences experienced by the battery or battery system and its effect on the internal resistance thereof. It would be desirable to provide a system and/or method that includes any one or more of these or other advantageous features as will be apparent to those reviewing the present disclosure.
SUMMARY
[0010] An exemplary embodiment of the invention relates to a method for determining the internal resistance of a lithium-based battery including calculating the internal resistance of a lithium-based battery that has been used at a first temperature for a first period of time based on the expected increase in the internal resistance of the battery resulting from such use. The method also includes using the calculated internal resistance of the battery to
determine the expected age of the battery if the battery had been held at a second temperature for the entire life of the battery, the second temperature differing from the first temperature. The method also includes using the determined expected age of the battery to calculate a new internal resistance of the battery after the battery has been used at the second temperature for a second period of time.
BRIEF DESCRIPTION OF THE DRAWINGS
[0011] FIGURE 1 is a perspective view of a lithium-ion battery or cell according to an exemplary embodiment.
[0012] FIGURE 2 is another perspective view of the battery shown in FIGURE 1.
) •
[0013] FIGURE 3 is an exploded perspective view of a battery system in the form of a module that includes a plurality of lithium-ion batteries or cells according to an exemplary embodiment.
[0014] FIGURE 4 is a flow chart detailing a method for modeling the increase in resistance of a lithium-ion battery cell according to an exemplary embodiment.
[0015] FIGURE 5 is a graph of a sample run of the method described in FIGURE 4.
[0016] FIGURE 6 is an explanatory chart for describing step 440 from FIGURE 4.
[0017] FIGURE 7 is a data table representing a sample run of the method described in FIGURE 4 and graphed in.FIGURE 5.
[0018] FIGURE 8 is a data table representing sample uses of an equation for modeling increases in resistance at a constant temperature.
[0019] FIGURE 9 is a graph of the data contained in FIGURE 8.
DETAILED DESCRIPTION
[0020] According to an exemplary embodiment, a lithium-ion battery system is provided that includes a system or mechanism for managing (e.g., balancing or disconnecting) one or more lithium-ion batteries, battery modules, or cells (e.g., lithium-ion cells, lithium-polymer
cells, etc. of any presently known configuration or other configuration that may be developed in the future) in the event that a predetermined condition occurs. Such a lithium- ion battery system may be applied to individual lithium-ion batteries or to one or more lithium-ion batteries that are included in a module that includes a plurality of lithium-ion batteries or cells. Further, according to an exemplary embodiment in which a module including a plurality of lithium-ion batteries is provided, the module may be included in a system that includes a plurality of lithium-ion battery modules of any presently known configuration or any other configuration that may be developed in the future.
[0021] Various nonexclusive exemplary embodiments of lithium-ion batteries and lithium-ion battery systems are shown and described in U.S. Patent Application No. 10/976,169, filed October 28, 2004, the entire disclosure of which is hereby incorporated by reference. FIGURES 1-2 illustrate a lithium-ion battery or cell and FIGURE 3 illustrates a module that includes a plurality of lithium-ion batteries according to exemplary embodiments shown and described in U.S. Patent Application No. 10/976,169 (reference numerals shown in FIGURES 1-3 correspond to the reference numerals used in U.S. Patent Application No. 10/976, 169).
[0022] While FIGURES 1-3 illustrate particular exemplary embodiments of lithium-ion batteries and battery systems, any of a variety of lithium-ion batteries or battery systems may be used according to various other exemplary embodiments. For example, according to various exemplary embodiments, the physical configuration of the individual cells and/or the modules may be varied according to design objectives and considerations. According to one exemplary embodiment, a system may include a module having ten cells. According to other exemplary embodiments, a different number of cells may be included in a module.
[0023] A preferred embodiment of the present invention provides a method that accounts for temperature changes over the life of a lithium-ion cell when determining changes in internal resistance of the battery, which may provide more accurate predictions as to the life of lithium-ion batteries used in real-world applications. For example, real time prediction of battery life could provide consumers with an estimate for time remaining so they can plan use and replacement strategies accordingly. Also, predictions could be used to cost- effectively set warranty lengths and terms. These uses are just examples and the current disclosure is not limited to them.
[0024] According to an exemplary embodiment, the method includes modeling resistance at constant temperature that can be derived empirically. The resistance for a lithium-ion battery cell at a constant temperature may be calculated according to the equation
R = R 0 + [A * exp(B/T)]*t . l 0.5 (Equation 1)
where R 0 is the initial resistance, A and B are constants for a type of lithium-ion cell, T is the temperature in Kelvin, and t is the time in days. Equation 1 can also be solved for time(t):
t = [(R - Ro) / (A * exp(B/T))] 2 (Equation 2)
[0025] Constants A and B in Equations 1 and 2 are specific to a particular type of lithium- ion battery cell. Constants A and B can be derived for a particular type of cell by holding lithium-ion battery cells at constant temperature and measuring the increase in resistance. The measurement is repeated for multiple temperatures to produce a set of data for that type of lithium-ion battery cell. The resulting set of data can then be used to solve for constants A and B. This process is demonstrated in currently available literature.
[0026] A method 400 for predicting lithium-ion battery life using Equations 1 and 2 is detailed in FIGURE 4 according to an exemplary embodiment. Generally, the method 400 (FIGURE 4) described uses Equation 1, Equation 2, expected time intervals, and expected temperatures to model the resistance gains of lithium-ion battery cells. An example of a theoretical battery cell life cycle with time intervals and temperatures is displayed below in Table 1:
Table 1
[0027] Given an expected use pattern of a lithium-ion battery cell like that described in Table 1, method 400 (FIGURE 4) is used to predict increases in internal resistance in the battery. FIGURE 7 is a sample run of method 400 for predicting resistance values of a lithium ion battery cell with changing temperature. The Constants A and B correspond to the equation constants for a particular lithium ion battery cell and are used in the above equation. Generally, the Resistance from the previous interval (R n ) and the interval temperature (T n H -1 ) are used in the given equation to solve for the age at interval temperature (to). The interval duration (tj) is added to the age at interval temperature (to) to get the resultant end time (t n+1 ). The resultant end time is used along with the Temperature (T n +i), and Initial Resistance (R 0 ) to find the new resistance (R n+ O- The process then starts over with the next interval.
[0028] The curve 500 (FIGURE 5) represents the output of method 400 (FIGURE 4). The source data for the curve 500 (FIGURE 5) is contained in FIGURE 7. Each segment of curve 500 (FIGURE 5) represents an iteration of step 440 (FIGURE 4) through step 460 (FIGURE 4) of method 400 (FIGURE. 4). For example, segment 518 (FIGURE 5) represents the increase in resistance of the battery when the battery is used at a temperature of 45 degrees Celsius for a duration of 2 days. FIGURE 7 includes the segment number noted on curve 500 (FIGURE 5) corresponding to each interval. Note that in each segment, the resistance increases at differing rates depending on the age and temperature.
[0029] According to Equation 1, a lithium-ion battery cell increases resistance at a rate dependent on its temperature and age. A graph illustrating the increase in resistance at various constant T is shown in FIGURE 9. The graph shown in FIGURE 9 was produced using Equation 1 at different constant temperatures. The data used to construct the graph in FIGURE 9 is contained in FIGURE 8. The example data of FIGURE 8 for predicted resistance at constant temperature shows resistance increases faster at higher temperatures. For example, FIGURES 8 and 9 show that Equation 1 predicts a battery cell held constant at 30 degrees Celsius has a resistance of 0.07614 ohms after seven days. FIGURES 8 and 9 show that Equation 1 predicts the same battery cell held constant at 70 degrees Celsius after seven days has a resistance of 0.07736 ohms. As a result, when shifting time intervals, the age must be found for the current resistance value. This ensure the resistance increases will be modeled correctly in the equations based on constant temperature.
[0030] Line 910 (FIGURE 9) represents the predicted increase in resistance according to Equation 1 for a temperature of 70 degrees Celsius. Line 912 (FIGURE 9) represents the predicted increase in resistance according to Equation 1 for a temperature of 60 degrees Celsius. Line 914 (FIGURE 9) represents the predicted increase in resistance according to Equation 1 for a temperature of 50 degrees Celsius. Line 916 (FIGURE 9) represents the predicted increase in resistance according to Equation 1 for a temperature of 40 degrees Celsius. Line 918 (FIGURE 9) represents the predicted increase in resistance according to Equation 1 for a temperature of 30 degrees Celsius. Line 920 (FIGURE 9) represents the predicted increase in resistance according to Equation 1 for a temperature of 25 degrees Celsius. Line 922 (FIGURE 9) represents the predicted increase in resistance according to Equation 1 for a temperature of 20 degrees Celsius.
[0031] Inspection of the slopes of the lines of the graph in FIGURE 9 also show that the rate differs depending on the age of the cell. For example, Line 910 (FIGURE 9) predicts an increase in resistance of 0.00401 ohms between 0 and 7 days, a span of 7 days. The same line 910 (FIGURE 9) predicts an increase in resistance for the same cell of 0.00215 between 84 and 112 days, a span of 28 days. The predicted increase in resistance is approximately twice as much between 0 and 7 days as between 84 and 112 days even though the time span was only 25% as long.
[0032] Because the increase in resistance in a lithium-ion battery cell depends on both age arid temperature, a method that accurately predicts the increase in resistance must consider both of these variables. The method 400 (FIGURE 4) considers both when predicting internal resistance of the battery. Equation 1 models the resistance in a lithium-ion battery cell held at constant temperature. Method 400 (FIGURE 4) leverages Equation 1 and considers both age and temperature by treating each interval of the life cycle as if the battery cell had experienced the temperature of that interval over its entire life. This is accomplished by method 400 (FIGURE 4) by using Equation 1 with an adjusted battery cell age (the t variable) depending on the current resistance (R n ) and temperature of the current interval (T n+1 ) An explanation of the steps of method 400 (FIGURE 4) now follow.
[0033] In a step 410 of method 400, the values of constants A and B are derived for the subject type of lithium-ion battery cell. As described above, the constants A and B may
vary depending on the type of battery being modeled. According to an exemplary embodiment, the values are derived experimentally.
[0034] In a step 420 of method 400, the initial resistance (Ro) is determined. According to an exemplary embodiment, the initial resistance (R 0 ) is determined by measuring the initial resistance of the battery cell. This initial resistance will be used as (R 0 ) in Equation 1.
[0035] Once the initial resistance (R 0 ), A, and B are known, the initial resistance (Ro), temperature of the first interval (T 1 ), and the duration of the first interval (ti) are used in a step 430 to solve for the first predicted resistance value (R 1 ). This initial step reflects a straight forward use of Equation 1, because the temperature to this point is constant. This resistance value (R 1 ) can now be used as the input R n , to step 440 of method 400.
[0036] Step 440 starts the iterative portion of method 400, which comprises steps 440, 450, and 460 as shown in FIGURE 4.
[0037] The current resistance value (R n ) reflects the current predicted state of the battery cell. As the graph in FIGURE 9 demonstrates, age significantly affects the rate of resistance increase. Because of this, determining the correct starting age is important to accurately predicting increases in resistance.
[0038] Step 440 begins with the current resistance R n , taken from the outcome of the previous interval. The temperature T n+1 of the next interval is used in combination with R n to solve Equation 2 for the relative age t 0 of the current interval. The resultant formula is to = [(R n - Ro)/(A * exp(B/T n+1 ))] 2 . The variable t 0 represents the time it would take for a battery cell held at a temperature T n+ i to reach the current resistance R n . In this way, the resistance increase predicted in method 400 accurately reflects how a battery cell would age given that resistance and temperature. Essentially, the battery cell is treated as if it had spent its entire life at temperature T n+1 . It should be noted that to is not the actual age of the battery, but rather, a derived value that represents the estimated time the battery would have spent at temperature T n+I based on the current resistance R n .
[0039] An example may provide further explanation of how step 440 is performed. Line 910 (FIGURE 9) represents a battery cell held constant at 70 degrees Celsius. After 7 days, Equation 1 predicts a resistance of 0.07736 ohms (FIGURE 8). For the next 7 days, it is assumed the temperature of the battery cell drops to 30 degrees Celsius. Equation 1 predicts
resistance values for battery cells held at constant temperature for their entire life. In order to accurately use Equation 1 then, the age as if the battery cell was at a constant temperature of 30 degrees Celsius is necessary. If the current resistance of 0.07736 is used with a temperature of 30 degrees Celsius and Equation 2 is solved for time, that time represents the age of the battery cell had it aged at 30 degrees for its entire lifetime. Using FIGURE 8, this time would correspond to approximately 14 days. When the battery cell ages for the next seven days at 30 degrees, an accurate rate of resistance increase corresponds to the battery cell held at a constant temperature of 30 degrees Celsius between 14 and 21 days of age. Equation 2 may be solved to find the age at interval temperature (to) at any constant ' temperature (T). Ia the above example t 0 corresponds to 14 days, and T corresponds to 30 degrees Celsius. A battery cell may then age for any number of days or the interval duration (tj). In the above example, ti corresponds to the 7 days between 14 and 21 days of age. The accurate rate of resistance increase at a constant temperature due to aging the interval duration (t;) starting at the age at interval temperature (to) may therefore be modeled by Equation 1 as the formula R = R 0 + [A * exp(B/T)]*(t 0 + t;) 0'5 .
[0040] The same process may be illustrated with respect to graph 600 shown in FIGURE 6, the data for which is provided in FIGURE 7. Note that the X-axis corresponds to time to the square root of the time in days (giving lines such as line 650 a linear shape, unlike those shown in FIGURE 9). Segment 610 represents the predicted resistance increase when the battery is held at 25 degrees Celsius for 0.5 days. For the next period at 40 degrees Celsius for a period of 0.5 days, the increase in resistance will be at a higher rate as compared to the first period in which the battery was at a lower temperature. In order for Equation 1 to be used accurately, the battery cell must be treated as if it has been at 40 degrees Celsius for its entire life. The current resistance (R n ), and the new temperature of 40 degrees Celsius (Tn+0 are used with Equation 2 to solve for the age (to) of the battery cell as if it had been at 40 degrees Celsius for its entire life. Segment 612 as shown in FIGURE 6 reflects the transition to tie relative age of the battery cell at 40 degrees Celsius, where cell resistance is held constant. This relative age represents the starting point for predicting the next increase in resistance.
[0041] Segment 614 is thus provided as representing the predicted increase in resistance of the battery when it is held at a temperature of 40 degrees Celsius for 0.5 days. The endpoint of segment 614 reflects the predicted resistance at the end of this period. Next, the
battery is held at a temperature of 30 degrees Celsius for 1.0 days. Because of the lower temperature during this period as compared to the previous period, the increase in resistance will be slower than that at 40 degrees Celsius. Again, the current resistance (R n ), and the new temperature of 30 degrees Celsius (TVK) are used with Equation 2 to solve for the age (t 0 ) of the battery cell had it been at 30 degrees Celsius for its entire life. Segment 616 reflects the transition to the relative age of the battery cell at 30 degrees Celsius. The increase in resistance can now be predicted using the relative age (to) of the battery cell as a starting point. Segment 618 represents the predicted increase in resistance when the battery is held at a temperature of 30 degrees Celsius for 1.0 days. The other unmarked segments in FIGURE 6 represent this process continuing as described based on the data shown in FIGURE 7.
[0042] After the starting age (to) of the current interval is known from step 440 (FIGURE 4), the duration of the current interval (t;) can be added to it to find the resultant time (t n +i). The resultant formula is t n+1 = to + tj. The resultant time (t n+1 ) is the value used in Equation 1 to predict the resistance (R n+ i). The resultant time (t n+1 ) is calculated in step 450.
[0043] Finally, using the temperature (T n+1 ), initial resistance (Ro), and resultant time (t n+1 ), Equation 1 is used in a step 460 to calculate the predicted resistance at the end of the current interval. This value is then used as R n in step 440 for a new interval. The resultant formula is R n+1 = R 0 + [A * exp(B/T n+1 )]*(t n+1 ) α5 .
[0044] Curve 500 shown in FIGURE 5 represents the outcome of method 400. Each segment of the curve 500 represents an iteration of step 440 through step 460 of method 400. Equation 1 is used in each iteration of these steps to predict the resistance increase using each interval's temperature and duration. FIGURE 7 contains the data used to construct curve 500 and includes a short explanation of method 400.
[0045] The use of the term battery "management" or "battery management system" is not intended as a term of limitation insofar as any function relating to the battery, including monitoring, charging, discharging, recharging, conditioning, connecting, disconnecting, reconnecting, etc., is intended to be within the scope of the term.
[0046] The input signals (or combination of signals) may be representative of conditions of the battery system such as voltage, current drawn by loads connected to the battery,
resistance, temperature, state of health, deliverable power, deliverable energy, capacity, time, battery condition, period since last discharge, etc. according to exemplary embodiments. The input signals provided to the battery management system may also be representative of a condition of the systems, subsystems and/or components of systems and/or subsystems of the vehicle (e.g., loads of the electrical system) according to other exemplary embodiments. The various signals may be measured directly or may be determined indirectly from a signal obtained from a sensor, alone or in combination with other signals or parameters used by computation, etc. The range of pre-selected values (e.g., operating or pre-selected parameters) that are compared to the input signals may be preprogrammed and/or determined during operation, use, testing, etc. of the vehicle. The range of pre-selected values may be adjusted or calibrated over time according to other exemplary embodiments. The range of pre-selected values that may be reset or otherwise adjusted or calibrated for changes in use or other factors relating to the vehicle or the battery system according to other exemplary embodiments.
[0047] Accordingly, various input signals may be used with other model equations, or the ' like, that predict model age of lithium-ion batteries, or the like, operating with some constant signal. The predicted resistance at that signal value may be used in the same manner as the above-described embodiments of the invention to model the age at different signal values in order to more accurately predict the lifetime of a battery.
[0048] The battery management system may comprise a computing device, microprocessor, controller or programmable logic controller (PLC) for implementing a control program, and which provides output signals based on input signals provided by a sensor or that are otherwise acquired. Any suitable computing device of any type may be included in the battery management system according to other exemplary embodiments. For example, computing devices of a type that may comprise a microprocessor, microcomputer or programmable digital processor, with associated software, operating systems and/or any other associated programs to implement the control program may be employed. The controller and its associated control program may be implemented in hardware, software, firmware, or a combination thereof, or in a central program implemented in any of a variety of forms (e.g., hardware and/or software and/or firmware) according to other exemplary embodiments. A single control system may regulate the controller for the battery management system and the controller for the vehicle (i.e., the
battery management system may be installed on a shared component system) according to any exemplary embodiment.
[0049] Data links or wires are provided for allowing data communication between the various components of the control system. For example, data or signals may be transmitted along a data link between a device or sensor for providing an input signal representative of a condition of a component of the vehicle and the battery.
[0050] Although the current embodiments refer to a process to model age for lithium-ion batteries, the current disclosure is not limited to them. The same process can be applied to lithium-polymer batteries and is included within the scope of the present invention.
[0051] It is important to note that the method as described in the various exemplary embodiments is illustrative only. Although only a few embodiments of the present inventions have been described in detail in this disclosure, those skilled in the art who review this disclosure will readily appreciate that many modifications are possible without materially departing from the novel teachings and advantages of the subject matter recited in the claims. For example, the order or sequence of any process or method steps may be varied or re-sequenced according to other exemplary embodiments. Accordingly, all such modifications are intended to be included within the scope of the present invention as defined in the appended claims. Other substitutions, modifications, changes and omissions may be made in the design, operating conditions and arrangement of the various exemplary embodiments without departing from the scope of the present inventions.