Patent Publication Number: US-2023132758-A1

Title: Method for qualifying battery quality via operando heat flow rate sensing

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is the US national phase of PCT/IB2020/000326, which was filed on Apr. 3, 2020. 
    
    
     FIELD OF THE DISCLOSURE 
     The disclosure relates to the field of batteries, and more particularly to the field of testing the formation of the solid electrolyte interface layer (SEI) for batteries, which includes, but is not limited to, Lithium ion (Li-ion) and Sodium-ion (Na-ion) batteries. 
     BACKGROUND 
     With batteries being increasingly used in both the transport and power sectors, there exists a need to increase their reliability and performance. 
     It is well-known in the field of batteries that the formation of the SEI layer, a passivating film that results from the self-limited partial catalytic decomposition of the electrolyte at the electrode surfaces for potentials beyond its range of thermodynamic stability, is one of the major factors influencing the performance of the battery over time. Indeed, even though the formation of the SEI Layer is essential for the battery to function, if it occurs in excess, it may lead to undesirable lithium ions consumption, significant increases in impedance, and the reduction of the active electrode area, leading to a decrease of the performance of the battery over time. As such, the formation of the SEI layer, which mainly controls the cell lifetime, is a critical and expensive step in cell manufacturing, rendering the protocols as trade secrets among the manufacturers. 
     In order to improve the formation of the SEI layer of a battery for given electrodes, it is common practice for battery manufacturers to introduce additives into its electrolyte. Such additives alter the overall electrochemistry of the battery and usually help stabilizing the SEI layer. However, at present it is not possible to know whether the modification of the electrolyte has improved the SEI layer formation, that is, in a way that will not affect the long-term performance of the battery, at an early stage of the battery life. It is only after performing a long series of charge-discharge cycles, i.e. after actually witnessing the effects of a wrongly formed SEI layer on the battery performance, that it can be realized. 
     There is therefore a need to be able to determine how the composition of an electrolyte can improve the formation of the SEI layer of a battery has formed correctly at an early stage of the battery life. 
     SUMMARY 
     The disclosure provides 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 a 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 a 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 and 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.   
               

     The term “first charge” here relates to the very first time the battery cell is ever charged, i.e. the charge that is usually performed by the battery cell manufacturer before it is even commercialized. In addition, the term “over a first charge” is to be understood as over the time necessary to obtain a full charge of the battery cell. 
     The disclosure is based on the realization that, considering the SEI layer formation is caused by a surface decomposition of the electrolyte that is governed by electrochemical/chemical reactions, it can be monitored through the heat flow rate associated to such reactions. In other words, by observing and analysing thermal events, such as a sharp rise in heat flow rate, one can determine if a SEI layer has been correctly formed. 
     Hence, by recording heat flow rate data emitted by a first battery over its first charge, during which the SEI layer is formed, and comparing it to the heat flow rate data emitted by a second battery over its first charge, one can predict which battery will perform better in the long run. Indeed, by comparing thermal events, such as sharp rises in heat flow rate between two batteries, or by comparing the heat emitted by a battery at a particular moment of the charge, the battery whose SEI layer has formed in a more stable way can be identified. 
     The disclosure therefore provides a way of benchmarking and identifying suitable electrolyte formulae and defining optimized battery formatting protocols in a much faster and much cheaper way, which is a tremendous improvement for battery manufacturers. 
     Preferably, in order to facilitate the comparison, the electrodes of the two batteries are of the same type. They can even have the same composition. 
     Preferably, also in order to facilitate the comparison, the sensing and recording steps for the first and second batteries are performed at the same temperature. 
     Preferably, the sensing of the temperature is performed using at least one optical fiber Bragg grating sensor. 
     Indeed, owing to the temperature sensing using an optical fiber Bragg sensor, the heat flow rate measurement inside the battery cell can be made in a precise, non-invasive and cheap way. 
     The small size of an optical fiber Bragg grating sensor (less than 200 μm in diameter) enables the non-destructive insertion of a temperature sensing element, which in turn will give access to the heat flow rate, into the battery cells. For instance it can fit in the hollow part of batteries cells, such as 18650-format cylindrical cells. This makes the operando measurements of internal temperatures feasible. 
     Moreover, the optical fibers can be made of silicon with a polyamide coating, making them able to sustain the harsh chemical environment within the electrolyte of batteries. An optical fiber Bragg grating sensor also does not generate any electromagnetic interferences as it relies on optical signals. 
     According to a preferred embodiment of the disclosure, the selecting 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 the total span of the first charge of the first battery,   detecting, 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.       

     Indeed, a criterion for determining if the formation of the SEI layer is satisfactory is to consider the heat flow rate over an important span of the charge, i.e. the “width” of the peak of heat flow rate over the first charge of the battery. If the heat flow rate is high over more than 50% of the span of the first charge, it implies the formation of an unstable SEI layer. Thus, if one of the two batteries presents such a feature it can already be considered as a battery cell that will not perform well. 
     According to a particular embodiment of the disclosure, the selecting 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 second battery cells being performed according to the comparison between the first heat value, and the second heat value.       

     The first heat value is a value of heat, and can thus be expressed in either milliwatts-hour (mWh) or joules (J), or, if normalized, in either milliwatts-hour per gram (mWh/g) or joules per gram (J/g) of an electrode, for example of the negative electrode considering the SEI layer is formed in majority of the negative electrode. 
     The magnitude of the heat released by the battery cell is an indicator of the electrochemical/chemical reactions occurring within the battery cell, and thus of the formation of the SEI layer. Hence, if one of the two batteries emits more heat at the same moment of their respective first charges, it is likely that its SEI layer is less stable than the SEI layer of the other battery. Therefore, one battery can be chosen over the other. As an alternative, the second heat value can also be the theoretical heat value associated to the chemical reaction associated to the formation of the SEI layer, which can allow to detect if more heat than expected is recorded, meaning that the SEI layer is unstable. 
     Preferably, the steps of calculating and comparing the first and second heat values are not performed if the result of one of the detection steps is positive. Indeed in that case, the detection steps are sufficient to be able to select between the two batteries: the battery with a positive detection result will not be chosen. 
     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 before a predetermined percentage of the first charge, for example before 30% of the first charge of the first battery, and the second heat value corresponds to the integral of the heat flow rate generated by the second battery over said predetermined percentage of the first charge of the second battery. 
     Indeed it has been observed that most of the reactions linked to the formation of the SEI layer occur at the beginning of the first charge of a battery, for example within the first 30% of the charge, and that heat emitted afterwards is probably due to other electrochemical/chemical reactions. Thus, it is more efficient for the testing method to compare the heat values emitted at the beginning of the first charge. 
     According to a 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 before a predetermined percentage of the first charge, for example before 30% of the first charge of the first battery, and the second heat value corresponds to the integral of the heat flow rate generated by the second battery over said predetermined percentage of the first charge of the second battery. This is because the reactions linked to the formation of the SEI layer are linked to peaks of heat flow rate as such reactions are electrochemical and/or chemical reactions. 
     The disclosure also relates to a selecting device for selecting between two battery cells, comprising:
         a first heat flow rate sensor able to sense the heat flow rate emitted by a first battery cell and a second battery cell,   a second heat flow rate sensor able to sense the heat flow rate emitted by a second battery cell,   a memory for recording a first set of heat flow rate data sensed by first the 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,       

     the processor being able to compare the first set of heat flow rate data with the second set of heat flow rate data, and to select between 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. 
     Preferably, for the reasons explained above, the heat flow rate sensor of the device includes at least one optical fiber Bragg grating sensor. 
    
    
     
       BRIEF DESCRIPTION OF THE FIGURES 
       The disclosure will be better understood in view of the following description, referring to the annexed Figures in which: 
         FIG.  1    is a schematic view of a first and second battery cell and a selecting device according to the disclosure; 
         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; 
         FIG.  3    is a series of graphs showing the voltage and heat flow rate for a Na-ion Na 3 V 2 (PO 4 )2F 3 /hard carbon (NVPF/HC) cell with 1M NaPF 6  in DMC electrolyte over a state of charge of the battery, at a temperature of 25° C.; 
         FIG.  4    is a series of graphs showing the voltage and heat flow rate for a Na-ion Na 3 V 2 (PO 4 )2F 3 /hard carbon (NVPF/HC) cell with a 1M NaPF 6  in EC-DMC (NP30) electrolyte over a state of charge of the battery, at a temperature of 25° C.; 
         FIG.  5    is a series of graphs showing the voltage and heat flow rate for a Na-ion Na3V 2 (PO4)2F 3 /hard carbon (NVPF/HC) cell with a 1M NaPF 6  in EC-DMC (NP30) electrolyte over a state of charge of the battery, at a temperature of 55° C.; and 
         FIG.  6    is a series of graphs showing the voltage and heat flow rate for a Na-ion Na 3 V 2 (PO 4 )2F 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 
     A first battery cell  10 A, a second battery cell  10 B and a selecting device for selecting between two battery cells, hereinafter named selecting device  12 , according to the disclosure are shown on  FIG.  1   . 
     Battery cells  10 A and  10 B, one of which (battery cell  10 A) 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  10 H within a jelly roll  10 J. The jelly roll  10 J 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. 
     Testing device  12  comprises a heat flow rate sensor  13  able to sense the heat flow rate emitted by first battery cell  10 A and a heat flow rate sensor  13  to sense the heat flow rate emitted by second battery cell  10 B. 
     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 Ambient  of the environment surrounding the battery cell  10 A,  10 B. 
     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 . 
     Each calorimeter  13  also comprises a temperature sensor  16  intended to sense and measure an internal temperature T internal  inside the battery cell  10 A,  10 B. Internal temperature sensor  16  is preferably placed inside the hollow section  10 H 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 . 
     Each calorimeter  13  also comprises a temperature sensor  18  intended to sense and measure the surface temperature T surface  of the battery cell  10 A,  10 B. Here, the surface temperature  18  sensor is placed on the radial surface  10 S 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   . 
     Calorimeter  13  also comprises an electrical power source  20  for charging/discharging the batteries  10 A,  10 B. In a variant, the selecting device  12  may comprise just one electrical power source  20  for charging/discharging the batteries  10 A,  10 B. Said source may be a potentiostat able to generate an alternate galvanostatic pulse at a medium frequency such as 2 Hz. 
     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  10 A and a second set of heat flow rate data sensed by the calorimeter  13  relating to the second battery cell  10 B. 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. 
     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. 
     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  10 A or second  10 B 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. 
     In this particular embodiment of the disclosure, the processor  24  also computes, during calibration of the device, characteristic thermal attributes of each battery cell  10 A,  10 B 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  10 A,  10 B. 
     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: 
     
       
         
           
             
               
                 
                   
                     Q 
                     . 
                   
                   = 
                   
                     
                       
                         MC 
                         p 
                       
                       ⁢ 
                       
                         dT 
                         dt 
                       
                     
                     + 
                     
                       q 
                       . 
                     
                   
                 
               
               
                 
                   [ 
                   
                     Math 
                     ⁢ 
                         
                     1 
                   
                   ] 
                 
               
             
           
         
       
     
     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 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.
         The thermal equivalent circuit is also based on the assumption that the internal temperature, T internal  and the surface temperature T 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 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 out .       

     Based on the thermal equivalent circuit, the heat flow rate {dot over (q)} follows the two following equations: 
     
       
         
           
             
               
                 
                   
                     q 
                     . 
                   
                   = 
                   
                     
                       
                         
                           
                             T 
                             Surface 
                           
                           - 
                           
                             T 
                             Ambient 
                           
                         
                         
                           R 
                           out 
                         
                       
                       ⁢ 
                       
                            
                           
                       
                       ⁢ 
                       or 
                       ⁢ 
                           
                       
                         q 
                         . 
                       
                     
                     = 
                     
                       
                         
                           T 
                           Internal 
                         
                         - 
                         
                           T 
                           Surface 
                         
                       
                       
                         R 
                         in 
                       
                     
                   
                 
               
               
                 
                   [ 
                   
                     Math 
                     ⁢ 
                         
                     2 
                   
                   ] 
                 
               
             
           
         
       
     
     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 in  between the centre and the surface of the battery cell, the outside thermal resistance R out  between the surface of the battery cell and the ambient environment, and the product MC p  of the cell&#39;s mass M and isobaric heat capacity C p . 
     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=     cycle   IV   [Math 3]
 
     where P is the electrical power, with I and V being the current and voltage, respectively. 
     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. 
     Using the set of calibration temperatures assigned to the steady state, hereby named steady temperatures T SInternal , T SSurface  and T SAmbient , and the electrical power delivered to the battery cell by the power source  20 , processor  24  computes the internal thermal resistance R in  and the outside thermal resistance R out . 
     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 SInternal , T SSurface  and T SAmbient , measured by the internal FBG  16 , the surface FBG  18  and the ambient FBG  14 , processor  24  can compute R out  and R in  using the equations: 
     
       
         
           
             
               
                 
                   
                     q 
                     . 
                   
                   = 
                   
                     
                       
                         
                           
                             T 
                             SSurface 
                           
                           - 
                           
                             T 
                             SAmbient 
                           
                         
                         
                           R 
                           out 
                         
                       
                       ⁢ 
                           
                       or 
                       ⁢ 
                           
                       
                         q 
                         . 
                       
                     
                     = 
                     
                       
                         
                           T 
                           SInternal 
                         
                         - 
                         
                           T 
                           SSurface 
                         
                       
                       
                         R 
                         in 
                       
                     
                   
                 
               
               
                 
                   [ 
                   
                     Math 
                     ⁢ 
                         
                     4 
                   
                   ] 
                 
               
             
           
         
       
     
     Having computed the characteristic thermal attributes R out , R in  based on the set of calibration temperatures assigned to the steady state T SInternal , T SSurface  and T SAmbient , processor  24  computes the dissipation heat flow rate q dissipated from the battery cell to its environment in a steady state. 
     Subsequently, processor  24  obtains the factor MC 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. 
     More particularly, the factor MC p  is obtained using the equation: 
     
       
         
           
             
               
                 
                   
                     
                       Q 
                       . 
                     
                     - 
                     
                       q 
                       . 
                     
                   
                   = 
                   
                     
                       MC 
                       p 
                     
                     ⁢ 
                     
                       dT 
                       dt 
                     
                   
                 
               
               
                 
                   [ 
                   
                     Math 
                     ⁢ 
                         
                     5 
                   
                   ] 
                 
               
             
           
         
       
     
     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 
     
       
         
           
             
               dT 
               dt 
             
             , 
           
         
       
     
     the coefficient MC p  can be obtained a linear fitting performed by processor  24 . 
     After calibration, the characteristic thermal attributes R out , R in  and C p  (here MC 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 Internal , T Surface  and T Ambient . 
     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 . 
     According to a first step, the total generated heat flow rate {dot over (Q)} emitted by the first battery cell  10 A is sensed by the first calorimeter  13 . The total generated heat flow rate {dot over (Q)} emitted by the second battery cell  10 B is also sensed by the second calorimeter  13 , for example at the same time, or sequentially. 
     A first set of heat flow rate data related to the total generated heat flow rate emitted by the first battery cell  10 A over a first charge of the first battery cell  10 A 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  10 B are then recorded. 
     For example, the heat flow rates {dot over (Q)} are recorded at regular intervals of time over the first charge of the batteries  10 A,  10 B, 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   . 
     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  10 A or second  10 B battery cells according to the comparison between the first set of heat flow rate data with the second set of heat flow rate data. 
     Preferably, before comparing the first and second set of heat flow rate data, a preliminary detection step is performed for each battery  10 A,  10 B. 
     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  10 A. 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 . 
     Preferably, the electrodes of the two batteries  10 A,  10 B are of the same type, so that the composition of their electrolytes as regards to the formation of the SEI layer can be compared. 
     Hence, for example, a first battery cell  10 A, a Na-ion Na3V 2 (PO4)2F3/hard carbon (NVPF/HC) cell with 1M NaPF 6  in DMC electrolyte (NaPF 6 /DMC) is compared to a second battery cell  10 B, a Na-ion Na 3 V 2 (PO 4 )2F 3 /hard carbon (NVPF/HC) battery cell with 1M NaPF 6  (NP30) in EC-DMC electrolyte. Both batteries have the same electrodes, Na-ion Na3V 2 (PO4)2F3/hard carbon (NVPF/HC), but different electrolytes. 
     Also preferably, the sensing and recording steps for the first  10 A and second  10 B batteries are performed at the same temperature, here at 25° C. for both. 
     The results are shown on  FIG.  3    for the first battery cell, the one with the NaPF 6 /DMC electrolyte and on  FIG.  4    for the second battery cell, the one with the NP30 electrolyte. 
     As can be seen on  FIG.  3   , a heat flow rate above 20 mW g −1 , is recorded for a span of more than 50% of the first charge of the first battery cell. 
     On the other hand, as can be seen on  FIG.  4   , the heat flow rate is above 20 mW g −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. 
     The result of the detection steps are thus positive for the first battery cell, i.e. the one with the 1M NaPF 6  in DMC electrolyte, and negative for the second battery cell, i.e. the one with 1M NaPF 6  (NP30) in EC-DMC electrolyte. 
     Here, the detection steps are sufficient to be able to select between the two batteries: the second battery, the one with 1M NaPF 6  (NP30) in EC-DMC electrolyte, will be chosen. Indeed, a heat flow rate over 20 mW g −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 2 (PO4)2F3/hard carbon (NVPF/HC) electrolytes. 
     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  10 A or second  10 B battery cells is performed according to the comparison between the first heat value and the second heat value. 
     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  10 A, a Na-ion Na3V 2 (PO4)2F3/hard carbon (NVPF/HC) cell with 1M NaPF 6  in DMC electrolyte (NaPF 6 /DMC) and the second battery cell  10 B, a Na-ion Na 3 V 2 (PO 4 )2F 3 /hard carbon (NVPF/HC) battery cell with 1M NaPF 6  (NP30) in EC-DMC electrolyte, such a calculation needs not be performed. 
     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  10 A over a predetermined percentage of the first charge, for example before 30% of the first charge of the first battery  10 A, and the second heat value corresponds to the integral of the heat flow rate generated by the second battery  10 B over said predetermined percentage of the first charge of the second battery  10 B. 
     For example, a first battery cell  10 A, a Na 3 V 2 (PO 4 )2F 3 /hard carbon (NVPF/HC) battery cell with 1M NaPF 6  (NP30) in EC-DMC electrolyte is compared to a second battery cell  10 B, Na-ion Na 3 V 2 (PO 4 )2F 3 /hard carbon (NVPF/HC) cell with a customized electrolyte (denoted “Magic B”). Both batteries have the same electrodes, Na-ion Na3V 2 (PO4)2F3/hard carbon (NVPF/HC), but different electrolytes. 
     Also preferably, the sensing and recording steps for the first  10 A and second  10 B batteries are performed at the same temperature, here at 55° C. for both. 
     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. 
     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 −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. 
     Since the results of the detection steps are negative, the first and second heat values are calculated and then compared.
         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 −1 .   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 −1 .   From the comparison between the first and second heat values it can be noted that the second heat value (385 J g −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 −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.       

     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  10 A over a predetermined percentage of the first charge, for example before 30% of the first charge of the first battery  10 A, and the second heat value corresponds to the integral of the peaks of heat flow rate generated by the second battery  10 B over a predetermined percentage of the first charge, for example before 30% of the first charge of the second battery  10 B. 
     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 −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 −1  and 603 J g −1 , respectively.
         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 −1 , which is the value of the integral of the sole peak of heat flow rate occurring before 30% of the first charge.   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 −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 −1 ) associated to the first battery with the NP30 electrolyte ( FIG.  5   ), allowing for a selection of the second battery.       

     The disclosure is not limited to the presented embodiments and other embodiments will clearly appear to the person of ordinary skill in the art. 
     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 
     
         
           10 : Battery 
           10 J: Jelly roll of the battery 
           10 H: Hollow part of the battery 
           12 : Testing device 
           13 : Heat flow rate sensor (Calorimeter) 
           16 : Internal temperature sensor 
           18 : Surface temperature sensor 
           14 : Ambient temperature sensor 
           20 : Electrical power source 
           22 : Memory 
           24 : Processor 
         C p : specific heat capacity of the battery cell at constant pressure 
         M: mass of the battery cell 
         {dot over (Q)}: total heat flow rate released by a battery 
         {dot over (q)}: dissipation heat flow rate 
         R in : internal thermal resistance 
         R out : external thermal resistance 
         T Internal : internal temperature of the battery cell 
         T Surface : surface temperature of the battery cell 
         T Ambient : ambient environment temperature 
         T SInternal : steady internal temperature of the battery cell 
         T SSurface : steady surface temperature of the battery cell T SAmbient : steady ambient environment temperature