METHOD FOR QUALIFYING BATTERY QUALITY VIA OPERANDO HEAT FLOW RATE SENSING

Abstract

A method for selecting between a first battery cell and a second battery cells includes sensing a total generated heat flow rate emitted by the first battery cell and the second battery cells. The method further includes recording, for the first and second battery cells, first and second sets of heat flow rate data related to the total generated heat flow rate emitted by the first and second battery cells, respectively, over their first charge. The method further includes comparing the first set of heat flow rate data with the second set of heat flow rate data, and selecting one of the first or second battery cells according to the comparison between the first set of heat flow rate data with the second set of heat flow rate data.

Claims

1. A method for selecting between a first battery cell and a second battery cell, wherein the method comprises the following steps: sensing a total generated heat flow rate emitted by the first battery cell; recording a first set of heat flow rate data related to the total generated heat flow rate emitted by the first battery cell over a first charge of the first battery cell; sensing a total generated heat flow rate emitted by the second battery cell; recording a second set of heat flow rate data related to the total generated heat flow rate emitted by the second battery cell over a first charge of the second battery cell; comparing the first set of heat flow rate data with the second set of heat flow rate data; and selecting between one of the first or second battery cells according to a comparison between the first set of heat flow rate data with the second set of heat flow rate data.

2. The selecting method according to claim 1, wherein electrodes of the first and the second battery cells batteries are of a same type.

3. The selecting method according to claim 2, wherein the sensing and recording steps for the first and second battery cells are performed at a same temperature.

4. The selecting method according to claim 1, wherein the sensing of the total generated heat flow rate is performed using at least one optical fiber Bragg grating sensor.

5. The selecting method according to claim 1, wherein the method comprises, before the comparison step, the steps of: detecting, within the first set of heat flow rate data, if a heat flow rate above a predetermined threshold lasts over 50% of a total span of the first charge of the first battery; and detecting, within the second set of heat flow rate data, if a heat flow rate above a predetermined threshold last over 50% of a total span of the first charge of the second battery.

6. The selecting method according to claim 1, wherein the method also comprises the following steps: calculating a first heat value based on the first set of heat flow rate data; calculating a second heat value based on the second set of heat flow rate data; and comparing the first heat value and the second heat value, the selection between the first and the second battery cells being performed according to the comparison between the first heat value, and the second heat value.

7. The selecting method according to claim 5, wherein the method also comprises the following steps: calculating a first heat value based on the first set of heat flow rate data; calculating a second heat value based on the second set of heat flow rate data; comparing the first heat value and the second heat value, the selection between the first and the second battery cells being performed according to the comparison between the first heat value, and the second heat value; and wherein the steps of calculating and comparing the first and the second heat values are not performed if a result of one of the detection steps is positive.

8. The selecting method according to claim 6, wherein the first heat value corresponds to an integral of the heat flow rate generated by the first battery cell before a predetermined percentage of the first charge, and the second heat value corresponds to an integral of the heat flow rate generated by the second battery cell over said predetermined percentage of the first charge of the second battery.

9. The selecting method according to claim 6, wherein the first heat value corresponds to an integral of peaks of heat flow rate generated by the first battery cell before a predetermined percentage of the first charge, and the second heat value corresponds to an integral of peaks of heat flow rate generated by the second battery cell over a predetermined percentage of the first charge.

10. A selecting device for selecting between a first battery cell and a second battery cell, comprising: a first heat flow rate sensor able to sense a heat flow rate emitted by the first battery cell; a second heat flow rate sensor able to sense a heat flow rate emitted by the second battery cell; a memory for recording a first set of heat flow rate data sensed by the first heat flow rate sensor relating to the first battery cell, and a second set of heat flow rate data sensed by the second heat flow rate sensor relating to the second battery cell; and a processor configured to compare the first set of heat flow rate data with the second set of heat flow rate data, and to select one between the first second battery cells according to a comparison between the first set of heat flow rate data with the second set of heat flow rate data.

11. A testing device comprising the selecting device according to claim 10, wherein the heat flow rate sensor includes at least at least one optical fibre Bragg grating sensor.

Description

BRIEF DESCRIPTION OF THE FIGURES

[0045] The disclosure will be better understood in view of the following description, referring to the annexed Figures in which:

[0046] FIG. 1 is a schematic view of a first and second battery cell and a selecting device according to the disclosure;

[0047] FIG. 2 is a cut-out view in perspective of one of the first and second battery cell of FIG. 1 in which an internal temperature sensor of the selecting device according to the disclosure is inserted;

[0048] FIG. 3 is a series of graphs showing the voltage and heat flow rate for a Na-ion Na.sub.3V.sub.2(PO.sub.4)2F.sub.3/hard carbon (NVPF/HC) cell with 1M NaPF.sub.6 in DMC electrolyte over a state of charge of the battery, at a temperature of 25° C.;

[0049] FIG. 4 is a series of graphs showing the voltage and heat flow rate for a Na-ion Na.sub.3V.sub.2(PO.sub.4)2F.sub.3/hard carbon (NVPF/HC) cell with a 1M NaPF.sub.6 in EC-DMC (NP30) electrolyte over a state of charge of the battery, at a temperature of 25° C.;

[0050] FIG. 5 is a series of graphs showing the voltage and heat flow rate for a Na-ion Na3V.sub.2(PO4)2F.sub.3/hard carbon (NVPF/HC) cell with a 1M NaPF.sub.6 in EC-DMC (NP30) electrolyte over a state of charge of the battery, at a temperature of 55° C.; and

[0051] FIG. 6 is a series of graphs showing the voltage and heat flow rate for a Na-ion Na.sub.3V.sub.2(PO.sub.4)2F.sub.3/hard carbon (NVPF/HC) cell with a customized electrolyte (Magic B) over a state of charge of the battery, at a temperature of 55° C.

DETAILED DESCRIPTION

[0052] A first battery cell 10A, a second battery cell 10B and a selecting device for selecting between two battery cells, hereinafter named selecting device 12, according to the disclosure are shown on FIG. 1.

[0053] Battery cells 10A and 10B, one of which (battery cell 10A) is shown in FIG. 2, are for example a commercial Na-ion 18650 battery cell which comprises a circular cross-section and a central hollow section 10H within a jelly roll 10J. The jelly roll 10J itself comprises the positive electrode and negative electrode and a plurality of separators. Obviously, other formats of the battery cells such as pouch, prismatic, and coin cells can be used, as well as other electrode and electrolyte compositions as will be mentioned below.

[0054] Testing device 12 comprises a heat flow rate sensor 13 able to sense the heat flow rate emitted by first battery cell 10A and a heat flow rate sensor 13 to sense the heat flow rate emitted by second battery cell 10B.

[0055] In this particular embodiment of the disclosure, the heat flow rate sensors 13 are calorimeters. Each calorimeter 13 comprises a temperature sensor 14 intended to sense and measure the ambient temperature T.sub.Ambient of the environment surrounding the battery cell 10A, 10B.

[0056] Preferably, the ambient temperature sensors 14 are optical Fiber Bragg grating sensors, which will be from now on designated as “FBGs”. Said FBG will be referred to as “ambient FBGs” 14.

[0057] Each calorimeter 13 also comprises a temperature sensor 16 intended to sense and measure an internal temperature T.sub.internal inside the battery cell 10A, 10B. Internal temperature sensor 16 is preferably placed inside the hollow section 10H of the jelly roll. Internal temperature sensor 16 is an optical Fiber Bragg grating sensors, which will be from now on designated as internal FBGs 16.

[0058] Each calorimeter 13 also comprises a temperature sensor 18 intended to sense and measure the surface temperature T.sub.surface of the battery cell 10A, 10B. Here, the surface temperature 18 sensor is placed on the radial surface 10S of the battery so that the surface temperature sensor 18 and the internal temperature sensor 16 are aligned on a local radius of the circular cross-section, as shown on FIG. 1.

[0059] Calorimeter 13 also comprises an electrical power source 20 for charging/discharging the batteries 10A, 10B. In a variant, the selecting device 12 may comprise just one electrical power source 20 for charging/discharging the batteries 10A, 10B. Said source may be a potentiostat able to generate an alternate galvanostatic pulse at a medium frequency such as 2 Hz.

[0060] Selecting device 12 also comprises a memory 22 for recording a first set of heat flow rate data sensed by the calorimeter 13 relating to the first battery cell 10A and a second set of heat flow rate data sensed by the calorimeter 13 relating to the second battery cell 10B. Such a memory can be an external flash disk, a hard disk, a flash memory, etc. or any type of data recording device, or be part of the same device as the temperature sensors. For instance, when using an optical interrogator which obtains and converts the optical signal (variation of the wavelength due to the variation of temperature) from the optical fiber Bragg grating sensor into a temperature signal, said interrogator may also record the temperature signal.

[0061] In this particular embodiment of the disclosure, memory 22 also records the temperatures sensed by the temperature sensors 14, 16, 18, which will be used to compute the first and second sets of heat flow rate data as will be seen below. It should be noted that a separate memory may be used to record the temperatures.

[0062] Selecting device 12 also comprises a processor 24 able to compare the first set of heat flow rate data with the second set of heat flow rate data, and to select one of the first 10A or second 10B battery cells according to the comparison between the first set of heat flow rate data with the second set of heat flow rate data as will be explained below.

[0063] In this particular embodiment of the disclosure, the processor 24 also computes, during calibration of the device, characteristic thermal attributes of each battery cell 10A, 10B using a set of internal, surface and ambient temperatures recorded over a predetermined calibration time period, named calibration temperatures, during which the battery is subjected to current emitted by the electrical power source 20, as will be explained below. It should be noted that a separate processor may be used to obtain characteristic thermal attributes of the battery cells 10A, 10B.

[0064] Here the characteristic thermal attributes computed by processor 24 are based on a predetermined thermal equivalent circuit of the battery. For example, said thermal equivalent circuit is based on the partition of the overall generated heat flow rate, between the capacitive heat flow rate remaining within the battery and the dissipation heat flow rate dissipated from the battery to its ambient environment, as expressed in the equation below:

[00001]$\begin{array}{cc}\stackrel{.}{Q}={\mathrm{MC}}_p\frac{\mathrm{dT}}{\mathrm{dt}}+\stackrel{.}{q}& \left[\mathrm{Math}1\right]\end{array}$

[0065] where {dot over (Q)} is the overall generated heat flow rate, q is the dissipation heat flow rate from the battery cell to its ambient environment, i.e. the dissipated heat flow rate, M is the mass of the battery cell, C.sub.p is the specific heat capacity of the battery cell at constant pressure, i.e. isobaric heat capacity, T is the temperature of the battery cell (here the volume-weighted average temperature is used), and t is time. {dot over (Q)} and {dot over (q)} are defined as positive if heat is released by the battery cell. [0066] The thermal equivalent circuit is also based on the assumption that the internal temperature, T.sub.internal and the surface temperature T.sub.surface of the battery are uniform, respectively, that the internal heat transfer resistances within the battery can be combined into a single one hereby named R.sub.in and that similarly, the external heat resistances between the surface of the battery and its ambient environment are combined into a single one hereby named R.sub.out.

[0067] Based on the thermal equivalent circuit, the heat flow rate {dot over (q)} follows the two following equations:

[00002]$\begin{array}{cc}\stackrel{.}{q}=\frac{T_{\mathrm{Surface}}-T_{\mathrm{Ambient}}}{R_{\mathrm{out}}}\mathrm{or}\stackrel{.}{q}=\frac{T_{\mathrm{Internal}}-T_{\mathrm{Surface}}}{R_{\mathrm{in}}}& \left[\mathrm{Math}2\right]\end{array}$

[0068] Considering this choice of thermal equivalent circuit, in this particular embodiment of the disclosure, the characteristics thermal attributes of the battery computed by the processor 24 during calibration of calorimeter 13 are the internal thermal resistance R.sub.in between the centre and the surface of the battery cell, the outside thermal resistance R.sub.out between the surface of the battery cell and the ambient environment, and the product MC.sub.p of the cell's mass M and isobaric heat capacity C.sub.p.

[0069] In order to calibrate these parameters, an alternate galvanostatic pulse of 2 Hz is applied by the electrical power source 20 to the battery cell and the evolution of potential is recorded over time by memory 22. The total generated heat flow rate is known from the equation:

{dot over (Q)}=P=.sub.cycleIV  [Math 3]

[0070] where P is the electrical power, with I and V being the current and voltage, respectively.

[0071] Then, processor 24 determines, based on the set of calibration temperatures, a steady state of the temperatures and a transient state of the temperatures, and assigns the temperatures recorded in the memory 22 to either the steady state or the transient state. The steady state is reached when all the generated heat is dissipated, i.e. when the total generated heat flow rate {dot over (Q)} is equal to the dissipation heat flow rate {dot over (q)}, because the temperatures become stable.

[0072] Using the set of calibration temperatures assigned to the steady state, hereby named steady temperatures T.sub.SInternal, T.sub.SSurface and T.sub.SAmbient, and the electrical power delivered to the battery cell by the power source 20, processor 24 computes the internal thermal resistance R.sub.in and the outside thermal resistance R.sub.out.

[0073] In other words, knowing the total generated heat flow rate Q linked to the electrical power delivered to the battery cell by the power source 20 and the steady temperatures T.sub.SInternal, T.sub.SSurface and T.sub.SAmbient, measured by the internal FBG 16, the surface FBG 18 and the ambient FBG 14, processor 24 can compute R.sub.out and R.sub.in using the equations:

[00003]$\begin{array}{cc}\stackrel{.}{q}=\frac{T_{\mathrm{SSurface}}-T_{\mathrm{SAmbient}}}{R_{\mathrm{out}}}\mathrm{or}\stackrel{.}{q}=\frac{T_{\mathrm{SInternal}}-T_{\mathrm{SSurface}}}{R_{\mathrm{in}}}& \left[\mathrm{Math}4\right]\end{array}$

[0074] Having computed the characteristic thermal attributes R.sub.out, R.sub.in based on the set of calibration temperatures assigned to the steady state T.sub.SInternal, T.sub.SSurface and T.sub.SAmbient, processor 24 computes the dissipation heat flow rate q dissipated from the battery cell to its environment in a steady state.

[0075] Subsequently, processor 24 obtains the factor MC.sub.p based on the set of calibration temperatures assigned to the transient state, the electrical power delivered to the battery cell by the power source 20 during the calibration period, which is related to the overall generated heat flow rate {dot over (Q)} as mentioned earlier and the dissipation heat flow rate q dissipated from the battery cell to its environment.

[0076] More particularly, the factor MC.sub.p is obtained using the equation:

[00004]$\begin{array}{cc}\stackrel{.}{Q}-\stackrel{.}{q}={\mathrm{MC}}_p\frac{\mathrm{dT}}{\mathrm{dt}}& \left[\mathrm{Math}5\right]\end{array}$

[0077] Here {dot over (Q)}-{dot over (q)} are known as described above. Using the recorded temperature assigned to the transient state, which represents the term

[00005]$\frac{\mathrm{dT}}{\mathrm{dt}},$

the coefficient MC.sub.p can be obtained a linear fitting performed by processor 24.

[0078] After calibration, the characteristic thermal attributes R.sub.out, R.sub.in and C.sub.p (here MC.sub.p) are recorded in memory 22 and can be used for measuring the total heat flow rate generated {dot over (Q)} by the battery cell towards its ambient environment from a set of internal, surface and ambient temperatures T.sub.Internal, T.sub.Surface and T.sub.Ambient.

[0079] A method for operando testing of the solid electrolyte interface (SEI) layer formation of a battery cell according to the disclosure will now be described. This method is carried out using the testing device 12.

[0080] According to a first step, the total generated heat flow rate {dot over (Q)} emitted by the first battery cell 10A is sensed by the first calorimeter 13. The total generated heat flow rate {dot over (Q)} emitted by the second battery cell 10B is also sensed by the second calorimeter 13, for example at the same time, or sequentially.

[0081] A first set of heat flow rate data related to the total generated heat flow rate emitted by the first battery cell 10A over a first charge of the first battery cell 10A and a second set of heat flow rate data related to the total generated heat flow rate emitted by the second battery cell over a first charge of the second battery cell 10B are then recorded.

[0082] For example, the heat flow rates {dot over (Q)} are recorded at regular intervals of time over the first charge of the batteries 10A, 10B, from 0% of charge to 100% of the first charge (in practice, the pre-set upper-limit voltage). Then, heat flow rate values may be plotted against the percentage of charge, as shown on FIGS. 3 to 6.

[0083] The processor 24 then compares the first set of heat flow rate data with the second set of heat flow rate data, and selecting one of the first 10A or second 10B battery cells according to the comparison between the first set of heat flow rate data with the second set of heat flow rate data.

[0084] Preferably, before comparing the first and second set of heat flow rate data, a preliminary detection step is performed for each battery 10A, 10B.

[0085] In particular, the processor 24 detects, within the first set of heat flow rate data, if a heat flow rate above a predetermined threshold lasts over 50% of the total span of the first charge of the first battery 10A. In the same way, the processor 24 detects, within the second set of heat flow rate data, if a heat flow rate above a predetermined threshold last over 50% of the total span of the first charge of the second battery 10.

[0086] Preferably, the electrodes of the two batteries 10A, 10B are of the same type, so that the composition of their electrolytes as regards to the formation of the SEI layer can be compared.

[0087] Hence, for example, a first battery cell 10A, a Na-ion Na3V.sub.2(PO4)2F3/hard carbon (NVPF/HC) cell with 1M NaPF.sub.6 in DMC electrolyte (NaPF.sub.6/DMC) is compared to a second battery cell 10B, a Na-ion Na.sub.3V.sub.2(PO.sub.4)2F.sub.3/hard carbon (NVPF/HC) battery cell with 1M NaPF.sub.6 (NP30) in EC-DMC electrolyte. Both batteries have the same electrodes, Na-ion Na3V.sub.2(PO4)2F3/hard carbon (NVPF/HC), but different electrolytes.

[0088] Also preferably, the sensing and recording steps for the first 10A and second 10B batteries are performed at the same temperature, here at 25° C. for both.

[0089] The results are shown on FIG. 3 for the first battery cell, the one with the NaPF.sub.6/DMC electrolyte and on FIG. 4 for the second battery cell, the one with the NP30 electrolyte.

[0090] As can be seen on FIG. 3, a heat flow rate above 20 mW g.sup.−1, is recorded for a span of more than 50% of the first charge of the first battery cell.

[0091] On the other hand, as can be seen on FIG. 4, the heat flow rate is above 20 mW g.sup.−1 for only 10% of the total span of the first charge, here between 20% and 30% of the first charge of the second battery cell.

[0092] The result of the detection steps are thus positive for the first battery cell, i.e. the one with the 1M NaPF.sub.6 in DMC electrolyte, and negative for the second battery cell, i.e. the one with 1M NaPF.sub.6 (NP30) in EC-DMC electrolyte.

[0093] Here, the detection steps are sufficient to be able to select between the two batteries: the second battery, the one with 1M NaPF.sub.6 (NP30) in EC-DMC electrolyte, will be chosen. Indeed, a heat flow rate over 20 mW g.sup.−1 throughout the first charge indicates the inability in forming a good protective SEI, owing to the high solubility of DMC-reduced species such as MeOCOONa and MeONa as can be experimentally observed, indicating that the first battery will not perform well. This is consistent with the fact that this type of electrolyte is identified as a badly performing as compared to other Na-ion Na3V.sub.2(PO4)2F3/hard carbon (NVPF/HC) electrolytes.

[0094] In this preferred embodiment of the disclosure, the processor 24 first calculates a first heat value based on the first set of heat flow rate data, a second heat value based on the second set of heat flow rate data, and compares the first heat value and the second heat value. The selection between the first 10A or second 10B battery cells is performed according to the comparison between the first heat value and the second heat value.

[0095] However, as mentioned above, since the detection steps are sufficient to select between the two batteries if the result of one of the detection is positive, the steps of calculating and comparing the first and second heat values are preferably not performed if the result of one of the detection steps is positive. Therefore, in the example above with the first battery cell 10A, a Na-ion Na3V.sub.2(PO4)2F3/hard carbon (NVPF/HC) cell with 1M NaPF.sub.6 in DMC electrolyte (NaPF.sub.6/DMC) and the second battery cell 10B, a Na-ion Na.sub.3V.sub.2(PO.sub.4)2F.sub.3/hard carbon (NVPF/HC) battery cell with 1M NaPF.sub.6 (NP30) in EC-DMC electrolyte, such a calculation needs not be performed.

[0096] According to a first variant of the disclosure, the first heat value corresponds to the integral of the heat flow rate generated by the first battery 10A over a predetermined percentage of the first charge, for example before 30% of the first charge of the first battery 10A, and the second heat value corresponds to the integral of the heat flow rate generated by the second battery 10B over said predetermined percentage of the first charge of the second battery 10B.

[0097] For example, a first battery cell 10A, a Na.sub.3V.sub.2(PO.sub.4)2F.sub.3/hard carbon (NVPF/HC) battery cell with 1M NaPF.sub.6 (NP30) in EC-DMC electrolyte is compared to a second battery cell 10B, Na-ion Na.sub.3V.sub.2(PO.sub.4)2F.sub.3/hard carbon (NVPF/HC) cell with a customized electrolyte (denoted “Magic B”). Both batteries have the same electrodes, Na-ion Na3V.sub.2(PO4)2F3/hard carbon (NVPF/HC), but different electrolytes.

[0098] Also preferably, the sensing and recording steps for the first 10A and second 10B batteries are performed at the same temperature, here at 55° C. for both.

[0099] The results are shown on FIG. 5 for the first battery cell, the one with the NP30 electrolyte and on FIG. 6 for the second battery cell, the one with the “Magic B” electrolyte.

[0100] First, the detection steps are performed. For both batteries, the one with the NP30 electrolyte and the one with the “Magic B” electrolyte, a heat flow rate above 20 mW g.sup.−1 is recorded for less than 50% of the span of the first charge, to be more precise for 20% of the span of the first charge for the NP30 (between 10% and 30% of the charge) and for 10% of the span of the first charge for the Magic B. Thus, the result of both detection steps are negative.

[0101] Since the results of the detection steps are negative, the first and second heat values are calculated and then compared. [0102] Referring to FIG. 5, illustrating the results of the recordings for the first battery, the one with the NP30 electrolyte, it can be noted that the first heat value, associated to the integral of the heat flow rate occurring before 30% of the first charge, is 688 J g.sup.−1. [0103] Referring to FIG. 6 illustrating the results of the recordings for the second battery, the one with the “Magic B” electrolyte, it can be noted that the second heat value, associated to the integral of the heat flow rate occurring before 30% of the first charge, is 385 J g.sup.−1. [0104] From the comparison between the first and second heat values it can be noted that the second heat value (385 J g.sup.−1) associated to the second battery with the “Magic B” electrolyte (FIG. 6) is nearly twice less than the first heat value (688 J g.sup.−1) associated to the first battery with the NP30 electrolyte (FIG. 5). This allows for a selection of the second battery. Again, this is consistent with experimental results showing a better performance of the “Magic B” battery, which is not a surprise as it is the purpose of using additives.

[0105] According to another variant of the disclosure, the first heat value corresponds to the integral of the peaks of heat flow rate generated by the first battery 10A over a predetermined percentage of the first charge, for example before 30% of the first charge of the first battery 10A, and the second heat value corresponds to the integral of the peaks of heat flow rate generated by the second battery 10B over a predetermined percentage of the first charge, for example before 30% of the first charge of the second battery 10B.

[0106] Referring back to FIG. 5, illustrating the results of the recordings for the first battery, the one with the NP30 electrolyte, it can be noted that the first heat value is 660 J g.sup.−1, which is the sum of the values of the integrals of the two peaks of heat flow rate occurring before 30% of the first charge of the first battery, amounting to 57 J g.sup.−1 and 603 J g.sup.−1, respectively. [0107] Referring to FIG. 6 illustrating the results of the recordings for the second battery, the one with the “Magic B” electrolyte, it can be noted that the second heat value is 239 J g.sup.−1, which is the value of the integral of the sole peak of heat flow rate occurring before 30% of the first charge. [0108] The result of the comparison and the selection steps are the same as in the first variant, as it can be noted that the second heat value (239 J g.sup.−1) associated to the second battery with the “Magic B” electrolyte (FIG. 6) is nearly twice less than the first heat value (660 J g.sup.−1) associated to the first battery with the NP30 electrolyte (FIG. 5), allowing for a selection of the second battery.

[0109] The disclosure is not limited to the presented embodiments and other embodiments will clearly appear to the person of ordinary skill in the art.

[0110] For instance, conventional calorimeters sensors may be used to sense the heat flow rate values, a multiplicity of processors may be used in order to perform the computing required by the testing device, and other formats of the battery cells such as pouch, prismatic, and coin cells can be tested.

LIST OF REFERENCES

[0111] 10: Battery [0112] 10J: Jelly roll of the battery [0113] 10H: Hollow part of the battery [0114] 12: Testing device [0115] 13: Heat flow rate sensor (Calorimeter) [0116] 16: Internal temperature sensor [0117] 18: Surface temperature sensor [0118] 14: Ambient temperature sensor [0119] 20: Electrical power source [0120] 22: Memory [0121] 24: Processor [0122] C.sub.p: specific heat capacity of the battery cell at constant pressure [0123] M: mass of the battery cell [0124] {dot over (Q)}: total heat flow rate released by a battery [0125] {dot over (q)}: dissipation heat flow rate [0126] R.sub.in: internal thermal resistance [0127] R.sub.out: external thermal resistance [0128] T.sub.Internal: internal temperature of the battery cell [0129] T.sub.Surface: surface temperature of the battery cell [0130] T.sub.Ambient: ambient environment temperature [0131] T.sub.SInternal: steady internal temperature of the battery cell [0132] T.sub.SSurface: steady surface temperature of the battery cell T.sub.SAmbient: steady ambient environment temperature