Proceedings of the Institution of Mechanical Engineers Part D Journal of Automobile Engineering,
Journal Year:
2024,
Volume and Issue:
unknown
Published: Nov. 27, 2024
Driving
conditions
prediction
plays
an
important
role
in
energy-saving
control
strategy
for
electric
vehicle.
However,
the
complexity
of
changes
road
poses
a
great
challenge
to
accurate
driving
condition.
To
address
this
problem,
paper
proposes
adaptive
Sliding
Window
(SW)
and
Gated
Recurrent
Unit
(GRU)
algorithm
predict
short
period,
enables
adjust
size
SW
promptly
when
change
frequently.
A
smaller
window
is
adopted
case
drastically
changing
speeds,
larger
smooth
speeds.
Firstly,
Principal
Component
Analysis
(PCA)
k-means
clustering
are
used
construct
sample
with
same
characteristics.
Then
instantaneous
frequency
calculated
by
Hilbert
transform
Variational
Mode
Decomposition
(VMD),
optimal
applicable
different
frequencies
quantitatively
calculated.
The
model
provides
precise
predictions
root
mean
square
error
(RMSE),
absolute
(MAE)
percentage
(MAPE)
0.8799,
0.5443
0.8362%,
respective.
ablation
experiments
show
that
improved
GRU
capture
trends
more
accurately,
improves
accuracy
robustness
model.
Green Energy and Intelligent Transportation,
Journal Year:
2023,
Volume and Issue:
2(6), P. 100128 - 100128
Published: Sept. 7, 2023
The
concept
of
the
Internet-of-Batteries
(IoB)
has
recently
emerged
and
offers
great
potential
for
control
optimization
battery
utilization
in
electric
vehicles
(EV).
This
concept,
which
combines
aspects
Internet-of-Things
(IoT)
with
latest
advancements
technology
cloud
computing,
can
provide
a
wealth
new
information
about
health
performance.
be
used
to
improve
management
number
ways,
including
continuous
prognosis
improved
vehicle
management.
In
this
paper,
we
reviewed
detail
basic
structure
IoB,
based
on
many
existing
studies.
We
also
explored
benefits
approach,
such
as
Implementing
IoB
EVs
is
not
without
challenges,
faces
security
data,
cross-platform
functionality,
technical
complexities
applying
large
scale.
However,
are
significant
continued
research
development,
it
ability
revolutionize
EV
industry.
purpose
review
paper
comprehensive
overview
discussing
its
challenges.
provides
roadmap
future
development
highlighting
key
areas
that
need
addressed
fully
realize
technology.
IET Control Theory and Applications,
Journal Year:
2024,
Volume and Issue:
18(15), P. 1910 - 1921
Published: Feb. 6, 2024
Abstract
In
this
study,
task
space
tracking
control
of
robot
manipulators
driven
by
brushless
DC
(BLDC)
motors
is
considered.
Dynamics
actuators
are
taken
into
account
and
the
entire
electromechanical
system
(i.e.
kinematic,
dynamic,
electrical
models)
assumed
to
include
parametric/structured
uncertainties.
A
novel
adaptive
controller
designed
stability
closed
loop
ensured
via
Lyapunov
type
tools.
To
demonstrate
performance
applicability
proposed
method,
a
simulation
study
conducted
using
model
two
degree
freedom,
planar
robotic
manipulator
BLDC
motors.
Renewable and Sustainable Energy Reviews,
Journal Year:
2024,
Volume and Issue:
206, P. 114857 - 114857
Published: Aug. 30, 2024
With
the
development
of
new
energy
vehicles,
EVs
have
received
ever-increasing
research
attention
as
an
essential
strategic
orientation
for
world
to
face
climate
change
and
issues.
significant
energy-saving
emission-reduction
advantages,
but
power
battery
state
estimation
accuracy
has
always
been
a
bottleneck
restricting
its
promotion.
Centered
on
cloud
management
control
methodology,
this
work
systematically
examines
models,
formulates
life
safety
strategies,
investigates
integration
technology
within
advanced
electronic
electrical
architectures.
Firstly,
overall
framework
device–cloud
fusion
is
introduced.
Secondly,
aiming
at
complex
problem
estimation,
models
methods
vehicle
are
summarized.
Then,
joint
method
outlined
states,
including
charge
health.
Finally,
viable
cloud-based
solution
elucidated
through
comprehensive
comparison
analysis
current
technologies'
strengths
limitations.
This
offers
theoretical
advancing
technology.
Energies,
Journal Year:
2024,
Volume and Issue:
17(2), P. 434 - 434
Published: Jan. 16, 2024
A
systematic
simulation
model
is
proposed
in
this
research
paper
to
estimate
the
energy
consumption
of
electric
vehicles.
The
main
advantage
that
it
made
a
generic
and
simplified
way
order
be
adaptable
different
overall
electrical
power
corresponding
performed
maneuver
estimated
considering:
tabular
form
motor
efficiency,
mechanical
losses,
generalized
efficiency
map
electronics,
auxiliary
an
electro-thermal
Lithium-Ion
battery
pack
model.
was
developed
previous
work,
which
simulates
open
circuit
voltage
curves
at
temperatures
alteration
internal
resistance
cells.
validated
with
experimental
data
from
tests.
proved
high
accuracy
estimating
values
relevant
WLTP2
driving
cycle
on
chassis
roller
test
bench.
Furthermore,
were
excellent
matching
compared
actual
field
measurements,
giving
only
measured
vehicle
speed
losses.
Finally,
state
charge
change
predicted
accurately
along
dynamic
maneuver.
Energies,
Journal Year:
2024,
Volume and Issue:
17(23), P. 6069 - 6069
Published: Dec. 2, 2024
Electromobility
contributes
to
decreasing
environmental
pollution
and
fossil
fuel
dependence,
as
well
increasing
the
integration
of
renewable
energy
resources.
The
interest
in
using
electric
vehicles
(EVs),
enhanced
by
machine
learning
(ML)
algorithms
for
intelligent
automation,
has
reduced
reliance
on.
This
shift
created
an
interdependence
between
power,
automatically,
transportation
networks,
adding
complexity
their
management
scheduling.
Moreover,
due
complex
charging
infrastructures,
such
variations
power
supply,
efficiency,
driver
behaviors,
demand,
electricity
price,
advanced
techniques
should
be
applied
predict
a
wide
range
variables
EV
performance.
As
adoption
EVs
continues
accelerate,
ML
especially
deep
(DL)
will
play
pivotal
role
shaping
future
sustainable
transportation.
paper
provides
mini
review
impacts
on
mobility
electrification.
applications
are
evaluated
various
aspects
e-mobility,
including
battery
management,
prediction,
infrastructure
optimization,
autonomous
driving,
predictive
maintenance,
traffic
vehicle-to-grid
(V2G),
fleet
management.
main
advantages
challenges
models
years
2013–2024
have
been
represented
all
mentioned
applications.
Also,
new
trends
work
strengths
weaknesses
covered.
By
discussing
reviewing
research
papers
this
field,
it
is
revealed
that
leveraging
can
accelerate
transition
mobility,
leading
cleaner,
safer,
more
systems.
states
dependence
big
data
training,
high
uncertainty
parameters
affecting
performance
vehicles,
cybersecurity
e-mobility
sector.
