Vibration-assisted active and passive collaborative cooling thermal management system: Performance study of thermoelectric cooling and phase change materials to enhance thermal stability of lithium-ion batteries
Yao Zhao,
No information about this author
Zhaoying He,
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Wenyi Liu
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et al.
Journal of Energy Storage,
Journal Year:
2025,
Volume and Issue:
117, P. 116256 - 116256
Published: March 15, 2025
Language: Английский
Thermal performance of an active battery thermal management system combining annular thermoelectric coolers and phase change materials
Ding Luo,
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Zihao Wu,
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Hao Chen
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et al.
Renewable Energy,
Journal Year:
2025,
Volume and Issue:
unknown, P. 123278 - 123278
Published: April 1, 2025
Language: Английский
A novel battery thermal management system with air–liquid coupled cooling based on particle swarm optimization
Feifei Liu,
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Qilong Yang,
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Daoyue Zheng
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et al.
Applied Thermal Engineering,
Journal Year:
2025,
Volume and Issue:
unknown, P. 126391 - 126391
Published: March 1, 2025
Language: Английский
Thermal management of electric bus batteries simulation study using heat pipes and phase change materials under varying passenger capacity and actual driving routes
Yannan Li,
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Xiangfen Bian,
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Haodong Li
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et al.
Applied Thermal Engineering,
Journal Year:
2025,
Volume and Issue:
unknown, P. 126402 - 126402
Published: April 1, 2025
Language: Английский
Optimal Structure Design and Temperature Control Strategy of Air‐Cooled Battery Thermal Management System
Energy Technology,
Journal Year:
2025,
Volume and Issue:
unknown
Published: May 11, 2025
Safety
concerns
in
lithium‐ion
batteries
pose
significant
challenges
for
electric
vehicle
systems.
A
reliable
battery
thermal
management
system
is
essential
to
maintain
optimal
performance.
In
this
article,
simulation
carried
out
the
design
of
air‐cooled
packs
with
aligned,
equally
spaced
staggered,
and
nonequally
staggered
arrangements,
based
on
experimental
validation.
The
spacing
positioning
are
optimized
cooling
heating
conditions
determine
heat
dissipation
configuration.
results
reveal
that
arrangements
enhance
transfer,
configuration
reducing
maximum
temperature
difference
by
15.6%
energy
consumption
36.6%,
compared
setup.
Furthermore,
considering
control
demands
pack
wind
speed,
state
equation
model
predictive
constructed
solved
particle
swarm
optimization
algorithm.
Subsequently,
cosimulation
employed
verify
its
effectiveness.
proposed
strategy
efficiently
regulates
reduces
consumption,
demonstrating
potential
improving
practical
applications.
Language: Английский