Automotive Engineering - March 2023 - BET14

Battery Management Systems
Global: Temperature (degC)
4.1
4.2
3.1
3.2
3.3
3.4
3.5
3.6
3.7
3.8
3.9
4
2.5
2.6
2.7
2.8
2.9
3
20000
Time (S)
40000
2.02
2.01
2
1.99
1.98
1.97
1.96
1.95
1.94
1.93
1.92
95
90
85
80
75
70
65
60
55
50
45
40
35
30
25
20
1000
2000
Model Temperature
Experiment_20degC
3000
Figure 3. Simulated and experimental data during external short-circuit testing. (Image: Exicom)
resistance. The COMSOL®
software's
lumped approach-based thermal model
was validated against experimental data
for charge-discharge profiles of the cell.
They also developed:
* Cyclic and calendric capacity-fade models
for cylindrical cells based on the
optimization features available in
COMSOL®
* A high-fidelity pseudo two-dimensional
(P2D) model for cylindrical cells using
extracted electrochemical parameters
They found that the lumped approach
enabled them to construct models using
a minimal number of parameters - such
as cell geometry, electrode thickness,
thermal conductivity, heat capacity, drive
cycle, and open-circuit voltage (OCV)-SOC
table - that are readily available from
battery pack manufacturers.
Extracting these parameters experimentally
is not only a time-consuming
process but also prone to errors due to
variable experimental conditions. For example,
ambient temperature fluctuates,
so extracting an accurate heat profile of a
cell requires performing an extensive
series of tests at different ambient
temperatures.
Using simulation, however, Dr. Singh
and the team were able to perform these
experiments with great ease. They were
×10-11
Cathode
External magnetic field
Applied current density
10.0
Magnetic field response_ at epsl_neg = 0.12
Magnetic field response_ at epsl_neg = 0.36
9.0
Separator
8.0
Anode
7.0
6.0
5.0
z
y
x
4.0
500
100
Time (s)
1500
Battery polarization at epsl_neg = 0.36
Battery polarization at epsl_neg = 0.12
0.52
0.47
0.42
0.37
0.32
0.27
0.22
0.17
0.12
2000
able to efficiently study charge and discharge
profiles, thermal behavior at different
charge and discharge rates, and
thermal runaway (Figure 2) due to external
or internal short circuits for different
cell chemistries (Figure 3).
The team was also able to identify
the hotspots in the battery pack and
determine the cell grading based on
capacity fade analysis with high accuracy.
These results had direct applications
in reducing the development cycle
time of the BMS, as the hotspots indicated
the best positions for deploying
the thermal sensors within the BMS to
function most efficiently.
3D-designed cell geometry (left). Variation of magnetic field response and polarization behavior during discharging at 0.12 and 0.36 anode
porosity values (right). (Image: Exicom)
14
Battery & Electrification Technology, March 2023
Cell potential (V)
Magnetic field response (A/m)
Battery polarization (V)

Automotive Engineering - March 2023

Table of Contents for the Digital Edition of Automotive Engineering - March 2023

Automotive Engineering - March 2023 - INTRO1
Automotive Engineering - March 2023 - SPONSOR1
Automotive Engineering - March 2023 - CVR1
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