Journal of Power Sources 612 (2024) 234807

Contents lists available at ScienceDirect

Journal of Power Sources
journal homepage: www.elsevier.com/locate/jpowsour

A cost-effective alternative to accelerating rate calorimetry: Analyzing
thermal runaways of lithium-ion batteries through thermocouples
Yang Yang a, b, David Raymand a, Daniel Brandell b, *ab

Scania Technical Centre, Scania CV AB, Södertälje, 151 87, Sweden
Department of Chemistry - Ångström Laboratory, Uppsala University, Box 358, Uppsala, 751 21, Sweden

H I G H L I G H T S• Thermal propagation of large format lithium-ion battery cells was tested.
• Results were analyzed and data compared to accelerating rate calorimetry.
• Critical parameters can be obtained from analysis of thermal propagation tests.
• Different stages of thermal runaway were observed during its propagation.
• A linear correlation between heat release and capacity was observed as 10.65 kJ/Ah.

A R T I C L E I N F O

A B S T R A C T

Keywords:
Li-ion batteries
Battery safety
Thermal runaway propagation
Heat release
Thermocouples

In order to facilitate safety of heavy-duty batteries, approaches for studying thermal runaway (TR) need to be
developed. So far, these have relied on accelerating rate calorimetry as a standard technique. This method,
however, is costly, generally has size limitations, and is therefore of limited use for large format batteries. In thisstudy, we examined the TR behavior of battery cells through a thermal propagation test at module level
employing 157 Ah battery cells, using simple thermocouples. This constitutes one of the largest prismatic cell
format analyzed to date, while the utilization of thermocouples enables a cost-effective method to study its TR.
Parameters such as TR onset temperature, maximum temperature, heat release, and trigger time of the cells werecomprehensively evaluated and compared, using this method. An onset temperature for TR at around 144 ◦ C anda maximum temperature from 757 ◦ C to 863 ◦ C were observed. Heat release was estimated as 1.59 MJ per
battery cell, deviating within ~1 % compared to nail penetration tests. Moreover, six distinct stages during TR
could be observed, in accordance with literature. This shows that the thermal propagation test using thermo­
couples is able to align well with other methods such as accelerating rate calorimetry, but is considerably easierto employ.

1. Introduction
Large format prismatic lithium-ion battery (LiB) cells constitute a
popular choice for battery electric vehicles (BEVs), partly due to theirhigher energy density and the limited manufacturing cost as comparedto smaller cell formats. Nickel-rich nickel manganese cobalt oxide(NMC; e.g. NMC811 which is LiNi0.8Mn0.1Co0.1O2) battery cells arefavorable for traction batteries in heavy-duty BEVs, given their highpower and energy density [1]. However, there are safety concerns withusing large format cells with nickel rich NMC that must be addressed
before deployment [2–4]. The thermal stability of this cathode material

is a concern for battery safety due to the increased risk for a thermal
runaway (TR) [5,6].
Determining the heat release from a cell during a TR event isnecessary for assessing the risk of cell-to-cell thermal propagation,
which is triggered by heat transmission. Inside the traction battery, thecells are typically arranged into modules, each housing multiple cells.
The mechanical structure of the module could make the TR behavior
different from cell level due to the internal heat transmission from one
cell to another. Therefore, methods for characterizing the TR process
and the corresponding heat release from a battery cell inside a battery
module or a pack are desired for developing safe high-capacity batteries.

* Corresponding author.
E-mail address: daniel.brandell@kemi.uu.se (D. Brandell).
https://doi.org/10.1016/j.jpowsour.2024.234807
Received 31 January 2024; Received in revised form 22 May 2024; Accepted 27 May 2024
Available online 30 May 2024
0378-7753/© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

Y. Yang et al.

Journal of Power Sources 612 (2024) 234807

With the rapid expansion of battery technology in vehicle applications,the demand for studying the thermal properties is expected to rise.
The TR chain reactions involve self-sustaining mechanisms and apositive feedback loop once TR is triggered [7–11]. In principle, thedecomposition of the cathode materials produces oxygen that supplies
the combustion of electrolyte and anode materials, thereby escalating
the temperature of the system. Furthermore, a high temperature in­creases the reaction rate of the exothermic chain reactions, which inreturn generates heat at an increasing rate.
Feng et al. introduced a framework of characteristic temperatures{T1, T2, T3} to describe the TR process in a battery [8,12–19]. T1 is theonset temperature for self-heating where a temperature increase
exceeding the ambient temperature can be noticed. T2 is the onset
temperature for TR, where rapid chain reactions are triggered andmassive heat is released. T3, in turn, represents the highest temperatureduring the TR process. The increment from T2 to T3 is directly related tothe total heat release under adiabatic condition.
To achieve a deeper understanding of TR mechanisms, segmenting
the process into distinct stages according to temperature ranges andtheir associated heat transfer characteristics have proven useful. Several
studies have described the TR event as a four-stage process [20–22].
Within the framework developed by the Feng et al., on the other hand, amore comprehensive depiction of TR comprises six stages (I-VI) [12,23,24]. Stage I corresponds to the initiation of thermal event when thebattery temperature rises, leading to slightly lower voltage and capacity
under elevated temperatures. In stage II (often 57–190 ◦ C), the battery
undergoes self-heating driven by the decomposition of the solid elec­
trolyte interphase (SEI), with concurrent SEI regeneration and con­sumption [25,26] and T1 is reached. Then in stage III, the self-heating
rate is slowed down when the separator undergoes melting. Poly­
ethylene (PE) based separators typically have a melting point between
130 ◦ C and 140 ◦ C and polypropylene (PP) at around 170 ◦ C [27,28].
Stage IV is characterized by the release of the stored electrical energy as
a consequence of internal short circuits (ISC) and combustion reactions
consuming the negative electrode active materials. The inner pressurebuilds and the cell swells until venting. In Stage V, separation between
the electrodes is lost when the ceramic coating breaks down, causingmajor ISC and a complete voltage drops. Massive heat is released fromanode combustion, cathode decomposition, electrolyte decomposition,etc. The temperature increases drastically in this stage, corresponding to
T2. Finally, in stage VI, the temperature rate is decelerated due to lim­
itations of active materials or oxygen supply. The remaining reactions
keep raising the temperature to its maximum, T3.
The rate of temperature increase (dT/dt) is another parameter that
describes the intensity of the TR reactions. A high temperature rate
predominantly resultis from low thermal instability of the battery ma­
terials. Assuming constant heat capacity and constant mass of the bat­tery through TR, it also provides insights about the heating power fromthe TR chain reactions as described in Eq. (1):
P=

dT
• cH
dt

as T1-T3. When the cooling mode is on, adiabatic conditions do not apply
and heat dissipation occurs by forced convection around the vessel.
However, the amount of heat loss is often neglected as the time spanfrom cooling mode to T3 is relatively short, typically seconds, and thecooling effect on the sample is limited.
For NMC batteries, standard parameters in ARC thermal runaway
experiments include raising the temperature by 5 ◦ C and then waitingfor 30 min to observe when the self-heating threshold temperature isexceeded. These self-heating thresholds typically range from 0.01 to
0.02 ◦ C per minute [12,13,21–23,32,33]. The choice of this thresholdrate affects the temperature at which self-heating is detected, with ahigher exothermic threshold resulting in a higher detected self-heating
temperature and a longer trigger time, as noted in Ref. [12].
The ARC methodology is limited by the size of the measurement
chamber. For example, a standard ARC typically involves a cylindricalcontainment vessel of 9 cm diameter and 10 cm depth, limiting thesample to 0.64 L [34]. Therefore, extended volume (EV + ARC) [34],yielding a space of ca. 50 L, are often necessary, but involves extra costs.
Another constrain is the that a test battery of too high capacity may
damage the ARC facility.
The limitation of ARC is thereby partly the limitations in size of thetest object, and partly to the availability of ARC testing facility due to thehigh cost. These can amount to above 0.2 million € [35]. Thereby, it isdesirable for relevant industries and research institutes to have a moreaccessible method to explore safety properties of batteries.
Here, we investigate the possibility to use thermal propagation test
data to develop an alternative to ARC measurements with better avail­ability. Thermal propagation tests are frequently employed in battery
safety testing [11,36,37] in order to study safety properties of battery at
module level. These tests usually include thermocouples at critical po­sitions on the battery cells. However, the data from such tests have so far
not being employed to find critical safety parameters such as T2, T3,
temperature increase rate and heat release at cell level. In this study, we
explore the possibility to utilize thermal propagation test data to
determine these parameters. For the purpose of verification, publisheddata of temperature increase rate obtained from ARC testing arecompared in the discussion [1,13,20–22,29–31]. Some of these ARC
studies also provide the possibility of estimating the heat releasethrough the specific heat capacity of their experiment samples, and arealso used for comparison.
Considering the challenges with ARC measurement, this study aims
at developing an alternative and comprehensive method to study TR
parameters, specifically employed on large format prismatic LiB cells
and modules through the use of readily accessible instruments. To thisend, a series of thermal propagation tests has been carried out at module
level. The cell temperature is captured at several positions on the outersurfaces of the cells in order to follow the temperature distribution andevolution. A substitutional method is thereby proposed to investigate
the TR processes, determining T2 and T3, temperature rate, and totalheat release during TR.

(1)

Nomenclature

Accelerating rate calorimetry (ARC) is a standard technique forstudying thermal events of batteries, such as TR, examples of suchstudies on NMC batteries are available in the literature [1,13,20–22,
29–31]. ARC uses a heat-wait-seek (HWS) cyclic operation mode, where
each cycle contains one step where the test object is heated and one stepwhich is a waiting period to allow for temperature homogenization
while seeking for the temperature at which self-heating starts. The cycle
is repeated until the temperature increase rate exceeds a predefined
threshold due to self-heating. When the threshold is found, the calo­
rimeter switches to an adiabatic mode where the temperature evolutionof the battery is monitored. Once the calorimeter has reached a pre­defined end temperature of a few hundred degrees, it switches to a
non-adiabatic cooling mode in order to protect the test equipment andheater [12,22]. ARC tests can clearly identify critical temperatures such

Abbreviations
LiB
BEV
TR
ARC
DMC
SEI
PE
PP
ISC
SoC
HWS
SymbolsP

lithium-ion battery
battery electric vehicle
thermal runaway
accelerating rate calorimetry
dimethyl carbonate
solid electrolyte interphase
Polyethylene
Polypropyleneinternal short circuit
state of charge
heat-wait-seekheating power of thermal runaway, W(continued on next page)2

Y. Yang et al.

Journal of Power Sources 612 (2024) 234807(continued )
dT/dt
cH
t
Qtot (t)nTt,nTt=0,n
T1
T2
T3
tTR

experience short circuits in an electric field. The measurements resulted
in a large extent of signal noise and unexpected missed logging of data,
especially during the TR event. Therefore, a specific data postprocessing routine was necessary to implement (section 2.5).

temperature increase rate, ◦ C/sheat capacity of the battery cell, J/K
time, stotal heat release of the measured cells as a function of time, MJ
the sequence of a cell in the moduletemperature of Cell no. n as a function of time, ◦ C
initial temperature of Cell no. n, ◦ C
the onset temperature for self-heating, ◦ C
the onset temperature for thermal runaway, ◦ C
the maximum temperature during thermal runaway, ◦ C
trigger time of thermal runaway, s

2.2. Test setup
The tests were carried out on a module that was enclosed in a box,
mimicking the use condition in a battery pack. The module included one
trigger cell (the right cell in Fig. 1) comprising several heating elements
and 17 battery cells, where thermal pads were inserted in between eachcell. The thermal pads in the module are normally applied to hinder heattransfer from a thermal event, and thereby to prevent or stop thermal
propagation. In practice, this allows the vehicle user significantly moretime to escape from an observed event than if no thermal isolation exists.
The front measurement point (F) on a cell was located at the geo­
metric center of the wide lateral surface facing the direction of heattransmission, and the back point (B) was the center of the opposite
lateral surface. The left (L) and right (R) side measurement points,
named according to the direction of heat transmission, were positioned
at two thirds of the height on the narrow lateral surfaces. The top
measurement point (T) was on the top surface next to the safety vent.
The lateral measurement positions (F, B, L and R) rendered infor­
mation on the temperature distribution within the battery module, andthe top measurement positions uncovered the venting behaviors of thecells.
The TR was triggered by direct contact of a block heating device
according to the recommended triggering method by Chinese national
standard GB 38031-2020 [42]. This heated up the first neighboring cellat the front side (F) on its wide lateral surface until TR was observed byeither exponential temperature increase or smoke. This, in turn, resulted
in a similar triggering event for the next battery cell, and so on.

2. Method
2.1. Battery and thermocouples
Prismatic NMC811/graphite LiBs were used for the test. The cell has
been co-developed by Scania CV AB and Northvolt AB, and will be
employed in an upcoming commercial vehicle model [38]. Every pris­
matic LiB cell featured a capacity of 157 Ah, rendering this one of thelargest existing commercial cells [39–41]. The cells have a nominal
voltage of 3.6 V, and were fully charged to 100 % state of charge (SoC)
for the test. The heat capacity of the complete cell was estimated by the
manufacturer as nearly 2000 J/K, which was utilized in the estimationsof heat release.
The battery module (Fig. 1) comprised 17 cells and a heating elementthat took up the space of one extra cell in the module. Temperatures ofthe first five cells in the module were measured through installed ther­mocouples, thereby rendering it possible to follow the process of thermal
propagation. Only the first five battery cells were measured, due to thelimit of data logging channels, but this was considered sufficient to
extract the main thermal parameters. As illustrated in Fig. 1, each cell
had 5 thermocouples at different positions to capture the temperature
evolution of a cell.
The thermocouples utilized were of K type, i.e. temperature sensors
made of Chromel and Alumel. These generally have a wide operationaltemperature range, reasonable accuracy, low cost, and were primarily
selected for their good accessibility. It should be noted, however, that it
is challenging to obtain high-quality data using these sensors in a ther­mal propagation test, possibly due to that the thermocouples may

2.3. Determination of characteristic temperatures
The front (F) and back (B) side measurement points, compared to theleft (L) and right (R) side measurement points, are closer to the core of
the jelly rolls inside the cells and experience less heat dissipation to themodule frame. Therefore, to determine the characteristic temperatures,a more trustworthy representation of the cell temperature was con­ducted from front (F) and back (B) side measurement data. The
maximum temperature, T3, was by estimated from the average of thefront and back measurement data, thus accounting for the uneven heat
distribution due to the large geometry of the battery cell. Moreover, T2
was derived solely from the back side measurement data, since themeasurement at the front side was affected by the previous cell that had
been heated through TR.
2.4. Estimation of heat release
The heat transmission within a battery module causes heat transferfrom a high temperature cell to the other cells, its surrounding air andmodule frame. The heat transfer to the surroundings was neglected in all
estimations. However, the heat transfer to the other cells could be sig­
nificant considering high thermal mass of the battery cells. The accu­
mulated heat release was estimated by summing up the contributions of
all five the measured cells in the module through Eq. (2); this approachthus includes heat transfer between the cells:
Qtot (t) =Fig. 1. The test setup of thermal propagation and thermocouple locations. F:
middle of font surface facing the heating source; B: middle of back surface to­wards heat flux direction; L: 2/3 height at the left surface facing the heating
source; R: 2/3 height at the right surface facing the heating source; T: top
surface next to the vent.

∫ t=t ∑
5
t=0

n=1

(

)
Tt,n − Tt=0,n • cH dt(2)

Eq. (2) quantifies the total heat release of the first five measured cells
as a function of time, and the heat release from TR of each individual
cells can then be separated in the time domain. In order to perform thecalculation, the temperature of each cell during TR (Tt,n) needs to be3

Y. Yang et al.

Journal of Power Sources 612 (2024) 234807

defined. Here, the average of front (F) and back (B) measurement data
was applied.
A similar method using temperature measurement has been
employed previously to calculate heat release from adiabatic ARC tests[20,43,44]. Moreover, the propagation test setup was open to atmo­
sphere, but considering the short time span from the onset of TR to theend of heat release of the cell, typically around 15 s, the heat dissipationfrom the module frame should be negligible.
For example, Fig. 7 (discussed below) shows explicitly how the totalheat release of the first five battery cells developed by each individual
TR event. Additionally, the decay of the curve between each TR event
indicates heat dissipation to the module frame and ambient air envi­
ronment, and the rate of heat dissipation can be also assessed from theslope of the decay.

both Cell no. 1 and 2 show a rapid increase in temperature due to thethermally triggered TR on Cell no. 2. A similar sequential phenomenon isthen taking place along the series of cells. It is notable that the timeintervals between these TR events become shorter from Cell no. 1 to 5.
It can be also seen from Fig. 2 that the heat transfer to the former cells
where TRs have been triggered are much more significant than to thecells where TRs have not been triggered, e.g., when TR is triggered on
Cell no. 3, there are substantial temperature peaks on Cell no. 1 and Cell
no. 2, but only a comparatively minor increase on Cell no. 4 and 5. Thismight be due to that the aluminum cell casing melts during TR as thetemperature reaches the melting point of 660 ◦ C. Probably, the thermal
pad also collapses under such high temperatures. The lack of thermal
barriers makes heat transfer more significant to a battery cell that isalready burnt by TR.
The TR behavior, including characteristic temperatures and different
stages of TR were analyzed based on these temperature profiles. More­over, some published ARC results are utilized for comparison.

2.5. Data processing
The random signal noise mentioned above makes it difficult to derive
accurate values from the sensors. Drastic oscillation and interruption of
the signal in many channels were observed in the original dataset,especially after initiation of the TR when massive heat starts to begenerated. Data processing, including cleaning, low-pass filtering andsmoothing, was therefore necessary for both numerical and graphicalanalysis.
Outliers were screened for physical plausibility in the visual pre­sentation of the results. This includes unfeasible data points, for example
when the cell temperature during TR drops to negative values and shifts
back to over 1000 ◦ C in a time scale of seconds.
A Butter-Worth low-pass filter was implemented after data cleaning
within the numerical differentiation framework developed by Floris van
Breugel et al. [45,46]. The Python-based library was published on
Github [47]. The level of noise was reduced by applying a filter with acut-off frequency that was determined in the power spectra analysis of
the dataset.

3.1. Characteristic temperatures
The average T2 for all five cells was 144 ◦ C, i.e., somewhat higher
than the PE melting point. This means that separation was sustained
10–15 ◦ C above the melting point of PE before ISC occurred. In theliterature there are examples of NMC batteries where separation issustained until 243 ◦ C [1].
Fig. 3 shows a decrease in the TR trigger time (tTR) from Cell no. 1 to5. This is likely due to that when the TR process propagates further into
the module, e.g., to Cell no. 5, the cell was not only heated by its adjacentcell (Cell no. 4), but also had been preheated by the module frame. In
Fig. 4, the module frame displays an increasing temperature along with
the TR propagation, which preheats the later cells in the module. The
preheating phenomenon makes TR propagation in a battery module
faster and faster. Preheating is observed on the other cells already when
TR is triggered on Cell no. 1, as can be seen from Fig. 2.
Regarding T3, Cell no. 1 presented the highest value of 863 ◦ C, while
Cell no. 3 to 5 exhibited relatively low T3 between 804 ◦ C and 821 ◦ C.
This might be the result of extra heat input from the heater to Cell no. 1,
as will be shown later, and can be attributed to the variation of TR
trigger time. A long heating duration would lead to that more energy isaccumulated by heating up more active materials of the cell before
reaching the onset temperature of TR (T2), and thereby generating sig­
nificant exothermic chain reactions.

3. Results and discussion
In the following text, the TR reactions of the battery cells are char­acterized based on the thermal propagation through the module. An
overview is given in Fig. 2, which displays the temperature profiles ofthe first five cells. As can be seen, the temperature increase in themodule starts at Cell no. 1, which undergoes an exponential temperatureburst from 136 ◦ C to 863 ◦ C. This event triggers a small rise in tem­
perature in the adjacent cells, where Cell no. 2 displays an increase ofabout 65 ◦ C. At the same time, the temperature declines in Cell no. 1 dueto heat dissipation to Cell 2 and the module frame, until ca. 1300 s. Then,

3.2. Stages of thermal runaway
Fig. 5 illustrates Stage I to V of the mechanisms of TR propagation in
the respective cells within the battery module. In this temperature

Fig. 3. The onset temperature T2, the maximum temperature T3, and thetrigger time tTR (green line) for the first five battery cells in the module. (Forinterpretation of the references to colour in this figure legend, the reader isreferred to the Web version of this article.)

Fig. 2. Measured temperature on the back side (B) of the first five cells.
4

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Journal of Power Sources 612 (2024) 234807

heated. At these high temperatures, it is known that metal ions in thecathode materials can dissolve to the electrolyte, with corresponding
battery degradation in terms of both capacity and voltage [12,23,
24].
• In Stage II, the temperature increase of each cell slowed down ataround 90 ◦ C. The reason for this is likely that the dimethyl car­bonate (DMC) in the electrolyte solvent started boiling [48]. The
lower temperature increase rate is thereby caused by vaporization,
which consumes significant amount of heat.
• In Stage III, the temperature increase rate started to rise again ataround 120 ◦ C. This is likely due to the coexisting exothermic re­actions of SEI decomposition and regeneration. The decompositionof the SEI generally starts at around 100 ◦ C with reactions of meta­
stable complex compounds, thereby generating porous SEI layer
structures that expose anode materials to the electrolyte. New SEI isconsequentially formed upon contact between the electrode and theelectrolyte [26].
• In Stage IV, the temperature displays a modest temperature increase
rate near 140 ◦ C for most of the cells. This could possibly be a resultof the separator melting, as the PE base of separators has an endo­
thermic peak in this temperature range [27,28]. Micro-scale ISCs
may arise due to partial loss of separation. Solvent vaporization
continues under the rising temperature, and internal pressure builds
up in the cells until venting occurs. It is evident that venting behavior
resulted in a temperature drop of 10–20 ◦ C, as can be seen at the endof Stage IV.
• In Stage V, an exponential escalation in temperature was observed,
indicating a tremendous release of heat. The TR chain reactions were
triggered at T2, including decomposition and reactions of the NMC

Fig. 4. Temperature of the module frame on left and right sides of Cell no. 5.
The temperature increases indicate the onset of TR from Cell no. 1 to Cell no. 5.

profile, six stages of the TR development could be observed based on thetemperature ranges and their corresponding temperature increase rates(with Stage I to V explicitly pointed out in Fig. 5).
The stages seen here are similar to those identified by Feng et al. anddescribed in the introduction. However, the temperature ranges areslightly different due to the differences in battery chemistry and format.
• In Stage I, the temperature of a cell increases with a high rate bymeans of heat transfer from its adjacent cell that has already beenFig. 5. Different stages of TR for (a) Cell no. 2; (b) Cell no. 3; (c) Cell no. 4; (d) Cell no. 5 indicated from the temperature evolution measured on the back side (B) of
each cell during the TR event.
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Journal of Power Sources 612 (2024) 234807

cathode, electrolyte, binder, anode, etc. Extensive fire and smoke
were observed in this stage.

higher capacity, resulting in a higher concentration of active material in
the testing enclosure that is competing for the oxygen in the ambient air.

Fig. 5 also displays some differences between the different cells in themodule; for example, different temperature intervals for the identified
stages. The initiate temperatures of Stage III and Stage IV increased from
Cell no. 2 to 5. This may be because of an increasing ambient
temperature.
In this TR propagation setup, the distinct heat transfer through thebattery module enables explicit illustration of these stages. This further
strengthens this method for investigation of the thermal processes. For
other methods, e.g., cell lateral heating, it is difficult to generate thistype of analysis.

3.4. Heat release
The total heat release profile of the first five battery cells (see Fig. 7(a)), calculated through Eq. (2), shows a step-like progression, with each“step” corresponding to the TR event of an individual cell (propagatingfrom Cell no. 1 to 5). The vertical dimension of these “steps” quantify theheat release of the respective cell. The cell number is indicated by thetiming of the heat increase step, as the input parameters are timedependent temperature data.
As can be seen in Fig. 7 (b), the first 5 battery cells within the module
released a similar amount of heat, between 1.45 MJ and 1.74 MJ,
yielding an average of 1.59 MJ. Consistently, the heat release amountassessed from a nail penetration test conducted on the same specifica­tion of the cell was 1.60 MJ [49]. Noticeably, Cell no. 1 released thehighest amount of heat, most likely because there was more energy input
from the heater to the first battery cell compared to the other cells. Cell
no. 5, in turn, released the lowest amount of heat, but also due to theabsence of estimating the heat loss to Cell no. 6 (where the temperature
was not measured).
The average heat release was 1.59 MJ per cell, including heattransfer to other cells in the module, but not to the module frame and theambient environment. This is still lower than the stored electric energy
in a 100 % SoC cell, which is approximately 2.07 MJ. Besides the heatrelease, there is also gas emission during TR. This means that there is alarge amount of energy released also by gas emissions.
The calculation of heat release using Eq. (2) neglects the change of
specific heat capacity due to the mass loss during TR, which could beover 40 % for a high SoC level [50]. This results in an overestimation ofheat release. However, this is compensated by underestimations of heatrelease from e.g., undermeasurement of the cell temperature by notdirectly measuring the jellyrolls and through heat loss to the module
frames.
Fig. 8 plots heat release of TR reactions from published ARC testing
results and the research of this study. A linear relationship between heatrelease amount and the capacity of an NMC battery can be observed,
displaying a slope of 10.65 kJ/Ah [1,13,20–22,29–31]. The findings
from the thermal propagation test demonstrates a nominal heat releaseof 10.13 kJ/Ah, thus exhibiting an average heat release of 1.59 MJ per
battery cell. As can be seen in Fig. 8, this value is closely aligned with the
ARC-based regression line. This fact makes the thermal propagation test
a credible approach for assessing heat release during TR.
The main difference of a non-adiabatic thermal propagation test andan ARC test is the test condition. While rapid heat dissipation can be
expected in a thermal propagation test due to air turbulence, ARC offers
an adiabatic experimental environment. However, in the ARC test
vessel, the adiabatic condition is not ideal since the cooling mode is on ate.g., 300 ◦ C, and there is also a heat exchange along the test vesselboundaries towards the calorimeter. The comparison above instead
shows that considering the short time interval from the start to the endof a TR event, heat loss in both setups appears to be still minor.
As the heat capacity of the entire battery cell is in linear relationshipwith the heat release according to Eq. (2), is it of great importance toaccurately determine this parameter. Nonetheless, the heat capacities ofthe specific cells are not always available from previous studies inliterature. On the one hand, it is not straight-forward to measure heat
capacity of such complex multi-materials objects as batteries andgeneralize from the obtained values.
On the other hand, there are more interests in TR behaviors than theheat release amount. Some studies examined heat capacity for the jellyrolls only, ending up at 1100 J kg− 1 K− 1 in the case of NMC532. This
could exaggerate the heat release, because of an overestimated heatrelease for the aluminum cell container [12,13,20,21,29].
Some of the deviations seen in Fig. 8 can be explained from

3.3. Temperature increase rate
In Fig. 6, the results for temperature increase rate from present study
is compared to the state of art ARC studies on NMC batteries found inliterature [1,20,22,29]. The thick black curve in Fig. 6 illustrates thecomputed average temperature increase rate from Cell no. 2 to 5. The
maximum temperature rate highlights the intensity of the TR reactions
under thermal propagation in the module. The average temperature
increase rate from Cell no. 2 to 5 reached a maximum of about 35 ◦ C/s,
corresponding to a peak heat release power of 70 kW according to Eq.
(1).
As can be seen from Fig. 6, a similar exothermic behavior is observed
from the published ARC data and the thermal propagation test. The
temperature increase rate exhibits an exponential growth at T2, and issustained around a high temperature rate until reaching close to the
maximum temperature. Then it decreases, most probably due to the lackof reactants, e.g., active material. The tested 157 Ah prismatic cell bat­teries present an immediate increase when reaching a T2 around 144 ◦ C.
This is a comparatively low temperature, considering the NMC batteries
in the referred studies exhibited a similar growth between 140 ◦ C and260 ◦ C. This might be due to that the ceramic coatings of the separatorsin the tested cells lost their separating capability earlier than in the otherstudies, but has yet to be confirmed. It is noteworthy that Cell no. 1 has
higher temperature increase rate than the average temperature increase
rate from Cell no. 2 to 5, indicating more drastic TR reactions for Cell no.
1. The intensity of TR could be caused by the heat input from the heater
to the first battery cell, as well as higher oxygen content in the testing
enclosure for the TR event of the first cell.
Moreover, it is noteworthy that the TR propagation test in this study
displayed a comparatively low maximum temperature increase rate incontrast to the ARC testing that had been conducted at cell level. One
contributing factor may lie in that this study utilized battery cells with

Fig. 6. Temperature rate and heat release rate during TR for the cells tested
here (black thick line) and from ARC data in literature [1,20,22,29].
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Journal of Power Sources 612 (2024) 234807

Fig. 7. (a). Total heat release of the first five cells; (b). Heat release for each cell derived from the curve of Qtot(t).

battery module consisting of prototype prismatic 157 Ah cells,
mimicking an energy storage solution for heavy-duty vehicles. Six stagesof thermal runaway development were observed. These could bedetermined from various temperature ranges and different temperature
increase rates, based on the framework defined in previous studies. The
average heat release is very close to the nail penetration test result on thesame cell configuration. The difference between these two methods waswithin 1 %.
There are, however, some limitations depending on the applied test
setup. T1 could not be identified due to the non-adiabatic experimental
conditions, and thus the relatively small exothermic threshold of T1 (e.g.,
0.01 ◦ C/min) could not be successfully observed. Moreover, highquality data is required to obtain credible knowledge, which requires
data post-processing. Nevertheless, with development of the numericaldifferentiation framework of noisy time-series data, it is feasible to clean
the data scientifically. Further improvements to generalize the method
would include a wider range of battery formats and chemistries, andmore thermocouple positions.

Fig. 8. Correlation between heat production during TR and the battery ca­
pacity. Regression line slop = 10.65 kJ/Ah. The data is based on informationfrom literature [1,13,20–22,29–31], apart from the thermal propagation test
data from this current study.

CRediT authorship contribution statement
Yang Yang: Writing – original draft, Visualization, Investigation,
Formal analysis, Data curation, Conceptualization. David Raymand:
Writing – review & editing, Supervision, Resources, Formal analysis.
Daniel Brandell: Writing – review & editing, Supervision.

uncertainties caused by using a general estimate of heat capacity rather
than one specific for each cell. There is clear evidence that nickel content
NMC-batteries releases great heat because of large amounts of oxygen
evolution [50]. Different heat flux also influences the total mass loss andreaction intensity [51]. Moreover, a high SoC augments the TR reactions[52].

Declaration of competing interest
The authors declare that they have no known competing financial
interests or personal relationships that could have appeared to influence
the work reported in this paper.

4. Conclusions
As has been shown, a well-designed thermal propagation test con­stitutes a feasible approach for a comprehensive analysis of battery cell
thermal runaway. It provides comparable results to other test method
such as accelerating rate calorimetry and nail penetration. The results
include the identified stages of the thermal runaway event, the heatrelease, the onset temperature (T2), the maximum temperature (T3), andthe temperature increase rate. Considering the costs associated withaccelerating rate calorimetry measurements, this alternative method
could open up for more extensive safety testing of battery prototypes.
Compared to accelerating rate calorimetry experiments, the thermal
propagation test offers flexibility with respect to battery size and ca­
pacity, and its required temperature sensors have better accessibility
and lower cost.
In this study, the thermal propagation test was performed on a

Data availability
The authors do not have permission to share data.
Acknowledgment
This work has been conducted with support from the Swedish Energy
Agency (project no. 51787-1) and from Batteries Sweden (grant no.
Vinnova 2019-00064). We acknowledge feedback from project partners:
Lars Fast and Ola Willstrand, RISE, and Tomas Verhallen and Seungbok
Lee, Northvolt AB. We also acknowledge support from Tommy Pham,
Carl Tengstedt and the Battery safety value creation team at Scania CV
AB for assistance with the thermal propagation tests. Jolla Kullgren at
Uppsala University is acknowledged for assistance with data analysis.
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Journal of Power Sources 612 (2024) 234807

DB acknowledges STandUP for Energy.

[25] Q. Wang, J. Sun, X. Yao, C. Chen, Thermal stability of lipf6/ec+ dec electrolytewith charged electrodes for lithium ion batteries, Thermochim. Acta 437 (1–2)(2005) 12–16.
[26] M. Richard, J. Dahn, Accelerating rate calorimetry study on the thermal stability oflithium intercalated graphite in electrolyte. i. experimental, J. Electrochem. Soc.
146 (6) (1999) 2068.
[27] A.-Y. Wong, F. Lam, Study of selected thermal characteristics of polypropylene/
polyethylene binary blends using dsc and tga, Polym. Test. 21 (6) (2002) 691–696.
[28] X. Huang, Separator technologies for lithium-ion batteries, J. Solid StateElectrochem. 15 (4) (2011) 649–662.
[29] D. Ren, X. Liu, X. Feng, L. Lu, M. Ouyang, J. Li, X. He, Modelbased thermal
runaway prediction of lithium-ion batteries from kinetics analysis of cellcomponents, Appl. Energy 228 (2018) 633–644.
[30] K. Li, H. Wang, C. Xu, W. Wu, W. Zhang, J. Hou, X. Rui, Y. Chen, L. Fan, X. Feng, etal., Multi-objective optimization of side plates in a large format battery module tomitigate thermal runaway propagation, Int. J. Heat Mass Tran. 186 (2022) 122395.
[31] K. Li, C. Xu, H. Wang, C. Jin, X. Rui, S. Chen, X. Feng, L. Fan, M. Ouyang,
Investigation for the effect of side plates on thermal runaway propagation
characteristics in battery modules, Appl. Therm. Eng. 201 (2022) 117774.
[32] T. Waldmann, M. Wohlfahrt-Mehrens, Effects of rest time after li plating on safety
behavior—arc tests with commercial high-energy 18650 li-ion cells, Electrochim.
Acta 230 (2017) 454–460.
[33] L. Zhang, S. Yang, L. Liu, P. Zhao, Cell-to-cell variability in li-ion battery thermal
runaway: experimental testing, statistical analysis, and kinetic modeling, J. Energy
Storage 56 (2022) 106024.
[34] T. H. T. Limited, “Ev+ Accelerating Rate Calorimeter,” May 18, 2022.
[35] R.R.I.O.S. Ab, Large Battery Accelerating Rate Calorimeter, Jun 6, 2022.
[36] X. Feng, X. He, M. Ouyang, L. Lu, P. Wu, C. Kulp, S. Prasser, Thermal runaway
propagation model for designing a safer battery pack with 25 ah linixcoymnzo2
large format lithium ion battery, Appl. Energy 154 (2015) 74–91.
[37] Q. Sun, H. Liu, M. Zhi, C. Zhao, J. Jia, P. Lv, S. Xie, Y. He, X. Chen, Lithium-ion
battery thermal runaway propagation characteristics under 20 kpa with different
airflow rates, Fire Technol. 59 (3) (2023) 1157–1179.
[38] E. Bratthall, Scania and Northvolt Unveil Green Battery Capable of Powering
Trucks for 1.5 Million Kilometers, Apr. 19, 2023.
[39] Z. Huang, X. Li, Q. Wang, Q. Duan, Y. Li, L. Li, Q. Wang, Experimental investigationon thermal runaway propagation of large format lithium ion battery modules withtwo cathodes, Int. J. Heat Mass Tran. 172 (2021) 121077.
[40] P. Liu, Y. Li, B. Mao, M. Chen, Z. Huang, Q. Wang, Experimental study on thermal
runaway and fire behaviors of large format lithium iron phosphate battery, Appl.
Therm. Eng. 192 (2021) 116949.
[41] O. Willstrand, M. Pushp, P. Andersson, D. Brandell, Impact of different li-ion cell
test conditions on thermal runaway characteristics and gas release measurements,
J. Energy Storage 68 (2023) 107785.
[42] Electric Vehicles Traction Battery Safety Requirements, 2020.
[43] C.-Y. Jhu, Y.-W. Wang, C.-M. Shu, J.-C. Chang, H.-C. Wu, Thermal explosion
hazards on 18650 lithium ion batteries with a vsp2 adiabatic calorimeter,
J. Hazard Mater. 192 (1) (2011) 99–107.
[44] C.-Y. Jhu, Y.-W. Wang, C.-Y. Wen, C.-M. Shu, Thermal runaway potential of licoo2
and li (ni1/3co1/3mn1/3) o2 batteries determined with adiabatic calorimetry
methodology, Appl. Energy 100 (2012) 127–131.
[45] F. Van Breugel, J.N. Kutz, B.W. Brunton, Numerical differentiation of noisy data: aunifying multi-objective optimization framework, IEEE Access 8 (2020)
196865–196877.
[46] F. Van Breugel, Y. Liu, B.W. Brunton, J.N. Kutz, Pynumdiff: a python package fornumerical differentiation of noisy time-series data, J. Open Source Softw. 7 (71)(2022) 4078.
[47] F. van Breugel, Y. Liu, B.W. Brunton, J.N. Kutz, PyNumDiff: A Python Package for
Numerical Differentiation of Noisy Time-Series Data, Mar. 2022.
[48] V. Pokorny, V. Stejfa, M. Fulem, C. Cervinka, K. Ruzicka, Vapor pressures andthermophysical properties of dimethyl carbonate, diethyl carbonate, and dipropyl
carbonate, J. Chem. Eng. Data 62 (10) (2017) 3206–3215.
[49] L. Seungbok, Nail Penetration Results, Private email communication, Date, 2023,
2023-11-09.
[50] M. Chen, D. Zhou, X. Chen, W. Zhang, J. Liu, R. Yuen, J. Wang, Investigation on thethermal hazards of 18650 lithium ion batteries by fire calorimeter, J. Therm. Anal.
Calorim. 122 (2015) 755–763.
[51] P. Ping, D. Kong, J. Zhang, R. Wen, J. Wen, Characterization of behaviour andhazards of fire and deflagration for high-energy li-ion cells by over-heating,
J. Power Sources 398 (2018) 55–66.
[52] Y. Fu, S. Lu, K. Li, C. Liu, X. Cheng, H. Zhang, An experimental study on burning
behaviors of 18650 lithium ion batteries using a cone calorimeter, J. Power Sources
273 (2015) 216–222.

References[1] X. Feng, M. Ouyang, X. Liu, L. Lu, Y. Xia, X. He, Thermal runaway mechanism oflithium ion battery for electric vehicles: a review, Energy Storage Mater. 10 (2018)
246–267.
[2] J.-M. Tarascon, M. Armand, Issues and challenges facing rechargeable lithium
batteries, nature 414 (6861) (2001) 359–367.
[3] J. Zhu, T. Wierzbicki, W. Li, A review of safety-focused mechanical modeling ofcommercial lithium-ion batteries, J. Power Sources 378 (2018) 153–168.
[4] P. Jindal, J. Bhattacharya, Understanding the thermal runaway behavior of li-ion
batteries through experimental techniques, J. Electrochem. Soc. 166 (10) (2019)
A2165.
[5] W. Liu, P. Oh, X. Liu, M.-J. Lee, W. Cho, S. Chae, Y. Kim, J. Cho, Nickel-rich layered
lithium transition-metal oxide for highenergy lithium-ion batteries, Angew. Chem.
Int. Ed. 54 (15) (2015) 4440–4457.
[6] J. Chen, L. Zhu, D. Jia, X. Jiang, Y. Wu, Q. Hao, X. Xia, Y. Ouyang, L. Peng,
W. Tang, et al., Lini0. 8co0. 15al0. 05o2 cathodes exhibiting improved capacity
retention and thermal stability due to a lithium iron phosphate coating,Electrochim. Acta 312 (2019) 179–187.
[7] A. Börger, J. Mertens, H. Wenzl, Thermal runaway and thermal runaway
propagation in batteries: what do we talk about? J. Energy Storage 24 (2019)100649.
[8] X. Feng, D. Ren, X. He, M. Ouyang, Mitigating thermal runaway of lithium-ion
batteries, Joule 4 (4) (2020) 743–770.
[9] S. Shahid, M. Agelin-Chaab, A review of thermal runaway prevention andmitigation strategies for lithium-ion batteries, Energy Convers. Manag. X (2022)
100310.
[10] L. Song, Y. Zheng, Z. Xiao, C. Wang, T. Long, Review on thermal runaway oflithium-ion batteries for electric vehicles, J. Electron. Mater. 51 (1) (2022) 30–46.
[11] S. Mallick, D. Gayen, Thermal behaviour and thermal runaway propagation inlithium-ion battery systems–a critical review, J. Energy Storage 62 (2023) 106894.
[12] X. Feng, M. Fang, X. He, M. Ouyang, L. Lu, H. Wang, M. Zhang, Thermal runaway
features of large format prismatic lithium ion battery using extended volume
accelerating rate calorimetry, J. Power Sources 255 (2014) 294–301.
[13] D. Ren, H. Hsu, R. Li, X. Feng, D. Guo, X. Han, L. Lu, X. He, S. Gao, J. Hou, et al.,
A comparative investigation of aging effects on thermal runaway behavior oflithium-ion batteries, ETransportation 2 (2019) 100034.
[14] X. Feng, S. Zheng, X. He, L. Wang, Y. Wang, D. Ren, M. Ouyang, Time sequence
map for interpreting the thermal runaway mechanism of lithium-ion batteries withlini x co y mn z o2 cathode, Front. Energy Res. 6 (2018) 126.
[15] X. Liu, D. Ren, H. Hsu, X. Feng, G.-L. Xu, M. Zhuang, H. Gao, L. Lu, X. Han, Z. Chu,
et al., Thermal runaway of lithium-ion batteries without internal short circuit,
Joule 2 (10) (2018) 2047–2064.
[16] X. Feng, S. Zheng, D. Ren, X. He, L. Wang, X. Liu, M. Li, M. Ouyang, Keycharacteristics for thermal runaway of li-ion batteries, Energy Proc. 158 (2019)4684–4689.
[17] X. Feng, S. Zheng, D. Ren, X. He, L. Wang, H. Cui, X. Liu, C. Jin, F. Zhang, C. Xu, etal., Investigating the thermal runaway mechanisms of lithium-ion batteries basedon thermal analysis database, Appl. Energy 246 (2019) 53–64.
[18] Y. Li, X. Feng, D. Ren, M. Ouyang, L. Lu, X. Han, Thermal runaway triggered byplated lithium on the anode after fast charging, ACS Appl. Mater. Interfaces 11 (50)(2019) 46839–46850.
[19] D. Ren, X. Feng, L. Liu, H. Hsu, L. Lu, L. Wang, X. He, M. Ouyang, Investigating therelationship between internal short circuit and thermal runaway of lithium-ion
batteries under thermal abuse condition, Energy Storage Mater. 34 (2021)
563–573.
[20] H. Li, Q. Duan, C. Zhao, Z. Huang, Q. Wang, Experimental investigation on thethermal runaway and its propagation in the large format battery module with li(ni1/3co1/3mn1/3) o2 as cathode, J. Hazard Mater. 375 (2019) 241–254.
[21] S. Zheng, L. Wang, X. Feng, X. He, Probing the heat sources during thermal
runaway process by thermal analysis of different battery chemistries, J. Power
Sources 378 (2018) 527–536.
[22] J. Chen, X. Rui, H. Hsu, L. Lu, C. Zhang, D. Ren, L. Wang, X. He, X. Feng,
M. Ouyang, Thermal runaway modeling of lini0. 6mn0. 2co0. 2o2/graphite
batteries under different states of charge, J. Energy Storage 49 (2022) 104090.
[23] X. Feng, J. Sun, M. Ouyang, X. He, L. Lu, X. Han, M. Fang, H. Peng,
Characterization of large format lithium ion battery exposed to extremely hightemperature, J. Power Sources 272 (2014) 457–467.
[24] X. Feng, J. Sun, M. Ouyang, F. Wang, X. He, L. Lu, H. Peng, Characterization ofpenetration induced thermal runaway propagation process within a large format
lithium ion battery module, J. Power Sources 275 (2015) 261–273.

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