Tech Briefs Magazine - March 2023 - BET-12

Battery Management Systems
This BMS is also chemistry agnostic; it can
be used with Li-ion batteries of a range of
chemistries such as lithium ferrophosphate,
or lithium iron phosphate (LFP), lithium
nickel manganese cobalt oxide (NMC), and
lithium nickel cobalt aluminum oxide (NCA).
The precision of the BMS depends on the
quality and accuracy of the inputs used for
programming or calibrating the system. For
example, the BMS includes a number of
thermal sensors distributed across the battery
pack. In order to accurately monitor a
battery pack's temperature distribution and
predict corresponding performance, it is
imperative that the sensors be placed at
the right locations. This requires a detailed
understanding of the heat profile of each
battery cell as well as how heat varies
throughout the pack. This is where COMSOL
Multiphysics® plays an integral part, by allowing
for accurate computation and collation
of the inputs, like heat profile information,
that are required to develop a BMS
with surgical precision.
Predicting and Preventing
Potential Thermal Runaway
Dr. Singh's team at Exicom used COMSOL
Multiphysics to perform a number of analyses
on the thermal behavior of battery
cells. They also used simulation to analyze
potential external short circuits, which
could cause thermal runaway - an uncontrolled
self-heating process that can damage
equipment or even cause fires. The
Temperature change
R_short_ext=0.08 Ώ, Mean Temperature
R_short_ext=0.08 Ώ, Max Temperature
R_short_ext=0.08 Ώ, Min Temperature
220
4
200
180
160
140
120
100
80
60
40
20
500
1000
1500
Time (s)
2000
2000
3000
3500
1.5
1
0.5
500
1000
1500
2000 2500
Time (s)
3000
3500
2.5
2
R_short_ext=0.008 Ω, Cell potential
R_short_ext=0.008 Ω, Cell open circuit voltage
R_short_ext=0.008 Ω, Cell potential
3.5
3
Global: Cell potential (V) Global: Cell open circuit voltage (V) Global: Cell current (A)
-10
-20
-30
-40
-50
-60
-70
-80
-90
-100
-110
-120
-130
-140
-150
-160
-170
4000
R_short_ext(3)=0.8 Ω Time=4000 s
Surface: Temparature (k)
K
314.1
313.65
Figure 1. The temperature distribution in a cylindrical cell at 1C discharge (left) and the contour
distribution of temperature (right). (Image: Exicom)
Exicom team began by analyzing the heat
generated in cylindrical cells with different
form factors and further extended this
model to the pack level using the heat
profile generated for the cells. " We were
especially interested in improving the temperature
gradient across the pack for aircooled
battery packs, " said Dr. Singh.
The results for thermal modeling at the
cell level for cylindrical cells during a 1C
discharging are shown in Figure 1. The visualization
on the left in Figure 1 shows the
temperature distribution, where the maximum
temperature is observed in the middle
of the cell. The visualization on the right
shows the contour distribution of temperature,
where the maximum temperature is
located in the active material of the cell.
The simulation results, when validated
with experimental findings, were observed
to be within the error limits of ±5 percent
at the standard charge-discharge profile.
The model was then further extended for
2C discharge at 100 percent state of charge
(SOC) according to Standard UL1642, which
is defined for external short circuit testing.
The positive and negative terminals of
the cell were shorted via an 80 ±20 mΩ
Figure 2. The temperature profile in a cell after thermal runaway (left) and the electrochemical profile in a cell after thermal runaway (right).
(Image: Exicom)
12
Battery & Electrification Technology, March 2023
∆T (K)
Cell potential (V)
Cell current (A)

Tech Briefs Magazine - March 2023

Table of Contents for the Digital Edition of Tech Briefs Magazine - March 2023