World Electric Vehicle Journal,
Год журнала:
2024,
Номер
15(11), С. 532 - 532
Опубликована: Ноя. 18, 2024
Precise
modeling
and
state
of
charge
(SoC)
estimation
a
lithium-ion
battery
(LIB)
are
crucial
for
the
safety
longevity
systems
in
electric
vehicles.
Traditional
methods
often
fail
to
adapt
dynamic,
nonlinear,
time-varying
behavior
LIBs
under
different
operating
conditions.
In
this
paper,
an
advanced
joint
approach
model
parameters
SoC
is
proposed
utilizing
enhanced
Sigma
Point
Kalman
Filter
(SPKF).
Based
on
second-order
equivalent
circuit
(2RC-ECM),
was
compared
two
most
widely
used
simultaneously
estimating
SoC,
including
hybrid
recursive
least
square
(RLS)-extended
filter
(EKF)
method,
simple
SPKF.
The
adaptive
SPKF
(ASPKF)
method
addresses
limitations
both
RLS+EKF
SPKF,
especially
dynamic
By
dynamically
adjusting
changes
battery’s
characteristics,
significantly
enhances
accuracy
performance.
results
demonstrate
robustness,
computational
efficiency,
reliability
ASPKF
traditional
methods,
making
it
ideal
solution
management
(BMS)
modern
EVs.
Batteries,
Год журнала:
2025,
Номер
11(1), С. 31 - 31
Опубликована: Янв. 17, 2025
Lithium-ion
(Li-ion)
batteries
have
become
essential
in
modern
industries
and
domestic
applications
due
to
their
high
energy
density
efficiency.
However,
they
experience
gradual
degradation
over
time,
which
presents
significant
challenges
maintaining
optimal
battery
performance
increases
the
risk
of
unexpected
system
failures.
To
ensure
reliability
longevity
Li-ion
applications,
various
methods
been
proposed
for
health
monitoring
remaining
useful
life
(RUL)
prediction.
This
paper
provides
a
comprehensive
review
analysis
primary
approaches
employed
RUL
estimation
under
categories
model-based,
data-driven,
hybrid
methods.
Generally
speaking,
model-based
use
physical
or
electrochemical
models
simulate
behaviour,
offers
valuable
insights
into
principles
that
govern
degradation.
Data-driven
techniques
leverage
historical
data,
AI,
machine
learning
algorithms
identify
trends
predict
RUL,
can
provide
flexible
adaptive
solutions.
Hybrid
integrate
multiple
enhance
predictive
accuracy
by
combining
with
statistical
analytical
strengths
data-driven
techniques.
thoroughly
evaluates
these
methodologies,
focusing
on
recent
advancements
along
respective
limitations.
By
consolidating
current
findings
highlighting
potential
pathways
advancement,
this
serves
as
foundational
resource
researchers
practitioners
working
advance
prediction
across
both
academic
industrial
fields.
Sustainability,
Год журнала:
2025,
Номер
17(7), С. 3232 - 3232
Опубликована: Апрель 4, 2025
To
address
the
critical
challenge
of
high
energy
consumption
in
single-source
electric
vehicles,
this
study
proposes
a
hybrid
storage
system
(HESS)-integrated
management
strategy
(EMS).
Firstly,
car-following
and
HESS
models
are
constructed.
Secondly,
multi-objective
optimization
framework
balancing
adaptive
cruise
control
(ACC)
optimal
tracking
quality
economy
is
developed,
where
fast,
non-dominated
sorting
genetic
algorithm
(NSGA-II)
resolves
dynamic
power
demands.
Thirdly,
third-order
Haar
wavelet
enables
online
rolling
decomposition
profiles.
The
high-frequency
transient
matched
by
supercapacitor,
while
low-frequency
steady-state
utilized
as
an
input
variable
to
controller.
Then,
fuzzy
logic
controller
dynamically
optimizes
HESS’s
distribution
based
on
state-of-charge
(SOC)
load
conditions.
Finally,
simulation
model
has
been
constructed
utilizing
MATLAB/Simulink
platform.
Comparative
analysis
under
Urban
Dynamometer
Driving
Schedule
(UDDS)
demonstrates
3.71%
reduction
total
demand
ego
vehicle
compared
front
vehicle.
Compared
configurations,
ensures
smoother
SOC
dynamics
lithium-ion
batteries.
After
employing
for
power,
battery
substantially
reduced.
three
strategies
that
wavelet-fuzzy
approach
exhibits
superior
comprehensive
performance.
Consequently,
proposed
effectively
mitigates
peak
charge/discharge
currents
entire
This
provides
novel
solution
systems
vehicles
(HESEV)
ACC
scenarios.
American Journal of Applied Chemistry,
Год журнала:
2024,
Номер
12(4), С. 77 - 88
Опубликована: Авг. 27, 2024
The
field
of
sustainable
battery
technologies
is
rapidly
evolving,
with
significant
progress
in
enhancing
longevity,
recycling
efficiency,
and
the
adoption
alternative
components.
This
review
highlights
recent
advancements
electrode
materials,
focusing
on
silicon
anodes
sulfur
cathodes.
Silicon
improve
capacity
through
lithiation
delithiation
processes,
while
cathodes
offer
high
energy
density,
despite
inherent
challenges.
Recycling
are
also
advancing,
mechanical
methods
achieving
60%
hydrometallurgical
processes
reaching
75%,
pyrometallurgical
85%
efficiency.
These
improvements
contribute
to
a
more
lifecycle
for
batteries.
Moreover,
shift
towards
components,
such
as
organic
batteries,
sodium-ion
solid-state
gaining
momentum,
representing
10%,
20%,
15%
market,
respectively.
alternatives
address
environmental
concerns
enhance
performance
reliability.
developments
underscore
importance
ongoing
innovation
materials
overcome
current
As
industry
continues
evolve,
these
pave
way
efficient
environmentally
friendly
storage
solutions,
promising
future
technologies.
Electronics,
Год журнала:
2024,
Номер
13(24), С. 4999 - 4999
Опубликована: Дек. 19, 2024
Accurate
estimation
of
the
state
charge
(SOC)
lithium
batteries
is
critical
for
safe
and
optimal
operation
battery
management
systems
(BMSs).
Traditional
SOC
methods
are
often
limited
by
model
inaccuracy
noise
interference.
In
this
study,
a
novel
type-2
fuzzy
cerebellar
neural
network
(Type-2
FCMNN)
proposed
accurately
estimating
batteries.
Based
on
traditional
(FCMNN),
rules
innovatively
introduced
to
enhance
robustness
against
uncertainties
disturbances.
This
enables
better
cope
with
nonlinear
complexity
external
disturbances
when
dealing
significantly
improves
accuracy
prediction.
On
basis,
analyzing
working
principle
batteries,
equivalent
circuit
successfully
established
simulated
tested
Simulink
R2022b,
which
provides
theoretical
basis
selection
size
input
parameters
subsequent
network.
Then,
paper
designs
implements
based
Type-2
FCMNN
tests
it
in
Matlab.
Finally,
carries
out
simulation
comparison
experiments
between
various
classical
algorithms
Matlab
R2022b
including
FCMNN,
backpropagation
network,
radial
function
Kalman
filtering
algorithm.
The
results
show
that
exhibits
significant
advantage
accuracy,
mean
absolute
error
root
square
values
only
43.1%
36.0%
FCMNN’s,
respectively,
while
achieves
best
among
compared
methods.
Journal of Marine Science and Engineering,
Год журнала:
2024,
Номер
12(10), С. 1888 - 1888
Опубликована: Окт. 21, 2024
Developing
an
efficient
power
system
is
important
way
for
icebreakers
to
respond
high
maneuverability
and
strong
fluctuation
loads
under
icebreaking
conditions.
The
performance
of
systems
short-period,
regularly
fluctuating
load-sea
conditions
has
been
intensively
studied.
However,
the
in
face
a
long-period,
stochastic
multi-frequency
process
not
fully
explored,
especially
parameter
uncertainty
battery
cycle
life.
In
this
study,
integrated
electric
propulsion
with
optimal
control
strategy
suggested
improving
system’s
dynamic
First,
energy
flow
model
diesel–electric
unit
as
main
body
coupled
storage
system/hybrid
constructed.
A
comparative
analysis
rule-based
optimization-based
management
strategies
performed,
optimized
programming
global
regulation
at
upper
level
predictive
lower
integrate
slow
fast
powers
achieve
adaptability
loads.
strategy,
uncertainties
parameters
have
introduced
eliminate
their
impact
on
performance.
Then,
simulated,
hybrid
supercapacitor
recommended
reach
multi-objective
lowest
unit,
highest
efficiency,
minimum
degradation.
Finally,
fuel
oil
consumption
emissions
discussed,
can
save
by
up
5.33%
reduce
CO2
emission
22%
during
process,
exhibiting
great
potential
environmental
friendliness
significant
advantages
terms
low
consumption.
