Analyzing the Adoption of Hybrid Electric and Hydrogen Vehicles in Indonesia: A Multi-Criteria and Total Cost of Ownership Approach
Cleaner Engineering and Technology,
Год журнала:
2025,
Номер
unknown, С. 100893 - 100893
Опубликована: Янв. 1, 2025
Язык: Английский
Influence of uncertainties in a battery pack with air cooling for electric vehicles on temperature difference and volume of battery module
Journal of Energy Storage,
Год журнала:
2025,
Номер
113, С. 115643 - 115643
Опубликована: Фев. 1, 2025
Язык: Английский
Tube-Based Robust Nonlinear Model Predictive Control for Thermal Processes with Variable with Long-Time Delay
Опубликована: Янв. 1, 2025
Язык: Английский
Experimental Analysis of Battery Thermal Management Techniques for Electric Vehicle Lithium-Ion Batteries Using MATLAB Simulink, Simscape, and Stateflow Simulations
Shanmuganathan Thangaraju,
N. Meenakshi,
M. Ganesan
и другие.
SAE technical papers on CD-ROM/SAE technical paper series,
Год журнала:
2025,
Номер
1
Опубликована: Апрель 1, 2025
<div
class="section
abstract"><div
class="htmlview
paragraph">The
use
of
lithium-ion
batteries
in
electric
vehicles
marks
a
major
progression
the
automotive
sector.
Energy
storage
systems
extensively
make
these
batteries.
The
extended
life
cycle,
low
self-discharge
rates,
high
energy
density,
and
eco-friendliness
are
well-known.
However,
Temperature
sensitivity
has
an
adverse
effect
on
battery
safety,
durability,
performance.
Thus,
maintaining
ideal
operating
conditions
reducing
chance
thermal
runaway
depend
heavily
efficient
management.
To
address
this,
experimental
study
was
conducted
various
management
techniques,
including
active,
passive,
hybrid
approaches.
These
techniques
were
investigated
for
their
cooling
efficiencies
under
different
conditions.
electro-thermal
behavior
cylindrical
cells,
packs,
supervisory
control
simulated
using
MATLAB
Simulink,
Simscape,
Stateflow.
This
conductivity
Liquid
Cooling
(LC),
Air
(AC),
Heat
Pipe
(HP),
Phase
Change
Material
(PCM)
evaluated
performance
both
individual
according
to
C
rate
battery.
Simulation
results
analyzed
high-power
charging
discharging
typical
vehicles.
investigation
identified
that,
active
can
reduce
temperature
rise
during
deep
cycle.
not
all
driving
situations
environmental
factors
call
cooling.
For
modest
vehicle
speeds
regular
ambient
temperatures,
passive
is
adequate.
analysis
indicates
strategies
offer
better
trade-off
between
efficiency
effective
depending
runtime
requirements.</div></div>
Язык: Английский
Research on Energy-Saving Control Strategy of Nonlinear Thermal Management System for Electric Tractor Power Battery Under Plowing Conditions
World Electric Vehicle Journal,
Год журнала:
2025,
Номер
16(5), С. 249 - 249
Опубликована: Апрель 25, 2025
To
address
the
issue
of
over-regulation
temperature
a
liquid-cooled
power
battery
thermal
management
system
under
plowing
condition
electric
tractors,
which
leads
to
high
energy
consumption,
nonlinear
model
prediction
control
(NMPC)
algorithm
for
tractors
applicable
is
proposed.
Firstly,
control-oriented
tractor
heat
production
and
transfer
were
established
based
on
operating
conditions
Bernardi’s
theory
production.
Secondly,
in
order
improve
accuracy
prediction,
method
future
working
information
moving
average
Finally,
predictive
cooling
optimization
strategy
proposed,
with
objectives
quickly
achieving
regulation
reducing
compressor
consumption.
The
proposed
validated
by
simulation
hardware-in-the-loop
(HIL)
testbed.
results
show
that
NMPC
can
better,
holding
phase
reduces
speed
variation
range
24.6%
compared
PID,
it
consumption
23.1%
whole
phase.
Язык: Английский
A Critical Review of Advancements and Challenges in Thermal Management Systems For Lithium-Ion Batteries
Journal of Advanced Research in Numerical Heat Transfer,
Год журнала:
2025,
Номер
35(1), С. 117 - 161
Опубликована: Май 6, 2025
Battery
thermal
management
systems
(BTMS)
ensure
the
safety
and
performance
of
lithium-ion
batteries,
which
power
electric
vehicles.
However,
designing
an
effective
BTMS
is
challenging
due
to
batteries'
complex
behaviour
sensitivity
temperature
variations.
This
review
comprehensively
explores
current
vital
technologies
trends
in
BTMS,
explicitly
focusing
on
analysing
various
cooling
control
strategies.
To
discuss
four
primary
technologies:
air
cooling,
liquid
immersion
phase
change
material
(PCM)
cooling.
The
advantages
disadvantages
each
technology
are
compared
terms
cost-effectiveness,
applicability,
limitations
when
dealing
with
high-energy-density
batteries.
Furthermore,
delves
into
discussion
strategies
data
prediction
methods
for
emphasizing
importance
advanced
analysis
optimising
battery
safety.
Different
strategies,
such
as
passive,
active,
hybrid
control,
introduced
evaluated.
Data
methods,
artificial
neural
networks,
fuzzy
logic,
machine
learning,
also
presented
discussed.
comprehensive
provides
in-depth
understanding
while
serving
a
valuable
reference
future
research
application.
Язык: Английский
Enhancing E-Bike Efficiency with Intelligent Battery Temperature Control
World Electric Vehicle Journal,
Год журнала:
2025,
Номер
16(6), С. 289 - 289
Опубликована: Май 22, 2025
This
work
presents
an
innovative
approach
to
battery
thermal
management
for
e-bikes
by
addressing
heat
generation
at
its
source
rather
than
relying
on
conventional
cooling
techniques.
Traditional
systems
rely
sinks,
fans,
phase
change
materials,
or
fluids,
which
increase
cost
and
complexity.
In
contrast,
this
study
integrates
embedded
algorithms
into
the
e-bike’s
motor
controller,
enabling
temperature
regulation
through
performance
limitation.
Two
models
are
investigated:
a
reactive
algorithm
that
reduces
speed
as
nears
critical
threshold,
predictive
forecasts
future
evolution
adjusts
accordingly.
Experimental
results
show
successfully
limited
26.7%
below
value
but
of
reductions
up
40%.
The
model,
tested
in
two
configurations,
demonstrated
improved
performance,
limiting
maximum
20%
while
maintaining
stable
profiles.
These
findings
confirm
can
effectively
manage
temperature,
with
model
being
suitable
low-complexity
applications
offering
enhanced
when
more
computational
resources
available.
Язык: Английский
A comprehensive review on lithium-ion battery thermal management (BTM) using phase change materials: advances, challenges, and future perspectives
Journal of Thermal Analysis and Calorimetry,
Год журнала:
2025,
Номер
unknown
Опубликована: Май 23, 2025
Язык: Английский
Enhancing Fire Protection in Electric Vehicle Batteries Based on Thermal Energy Storage Systems Using Machine Learning and Feature Engineering
Fire,
Год журнала:
2024,
Номер
7(9), С. 296 - 296
Опубликована: Авг. 23, 2024
Thermal
Energy
Storage
(TES)
plays
a
pivotal
role
in
the
fire
protection
of
Li-ion
batteries,
especially
for
high-voltage
(HV)
battery
systems
Electrical
Vehicles
(EVs).
This
study
covers
application
TES
mitigating
thermal
runaway
risks
during
different
charging/discharging
conditions
known
as
Vehicle-to-grid
(V2G)
and
Grid-to-vehicle
(G2V).
Through
controlled
simulations
Simulink,
this
research
models
real-world
scenarios
to
analyze
effectiveness
controlling
under
various
environmental
conditions.
also
integrates
Machine
Learning
(ML)
techniques
utilize
produced
data
by
simulation
model
predict
any
probable
spikes
enhance
system
reliability,
focusing
on
crucial
factors
like
temperature,
current,
or
State
charge
(SoC).
Feature
engineering
is
employed
identify
key
parameters
among
all
features
that
are
considered
study.
For
broad
comparison
models,
three
ML
techniques,
logistic
regression,
support
vector
machine
(SVM),
Naïve
Bayes,
have
been
used
alongside
their
hybrid
combination
determine
most
accurate
one
related
topic.
concludes
SoC
significant
factor
affecting
management
while
grid
power
consumption
has
least
impact.
Additionally,
findings
demonstrate
regression
outperforms
other
methods,
with
improving
feature
be
it
can
increase
efficiency
due
its
linearity
capture
capability.
Язык: Английский
Electric Vehicle Battery Technologies and Capacity Prediction: A Comprehensive Literature Review of Trends and Influencing Factors
Batteries,
Год журнала:
2024,
Номер
10(12), С. 451 - 451
Опубликована: Дек. 19, 2024
Electric
vehicle
(EV)
battery
technology
is
at
the
forefront
of
shift
towards
sustainable
transportation.
However,
maximising
environmental
and
economic
benefits
electric
vehicles
depends
on
advances
in
life
cycle
management.
This
comprehensive
review
analyses
trends,
techniques,
challenges
across
EV
development,
capacity
prediction,
recycling,
drawing
a
dataset
over
22,000
articles
from
four
major
databases.
Using
Dynamic
Topic
Modelling
(DTM),
this
study
identifies
key
innovations
evolving
research
themes
battery-related
technologies,
degradation
factors,
recycling
methods.
The
literature
structured
into
two
primary
themes:
(1)
“Electric
Vehicle
Battery
Technologies,
Development
&
Trends”
(2)
“Capacity
Prediction
Influencing
Factors”.
DTM
revealed
pivotal
findings:
advancements
lithium-ion
solid-state
batteries
for
higher
energy
density,
improvements
technologies
to
reduce
impact,
efficacy
machine
learning-based
models
real-time
prediction.
Gaps
persist
scaling
methods,
developing
cost-effective
manufacturing
processes,
creating
standards
impact
assessment.
Future
directions
emphasise
multidisciplinary
new
chemistries,
efficient
end-of-life
management,
policy
frameworks
that
support
circular
economy
practices.
serves
as
resource
stakeholders
address
critical
technological
regulatory
will
shape
future
vehicles.
Язык: Английский