MATEC Web of Conferences,
Journal Year:
2024,
Volume and Issue:
404, P. 01005 - 01005
Published: Jan. 1, 2024
The
concerns
about
reducing
carbon
emissions
and
dealing
with
climate
change
have
led
to
a
surge
in
interest
development
of
new
energy
Vehicles
(NEVs).
These
vehicles,
which
include
electric
vehicles
(EVs)
hybrid
(HEVs),
are
crucial
the
transition
towards
sustainable
transportation.
This
review
paper
provides
an
in-depth
analysis
current
situation
advancements
NEV
technologies,
highlighting
significant
improvements
battery
technology,
power
electronics,
charging
infrastructure.
It
also
examines
various
Energy
Management
System
(EMS)
optimization
strategies,
including
rule-based,
optimization-based,
learning-based
approaches,
their
impact
on
vehicle
performance
economic
viability.
discusses
environmental
benefits
advanced
EMS
such
as
operational
costs
enhancing
longevity
key
components.
Additionally,
explores
future
directions
for
development,
emphasizing
importance
government
policies,
technological
innovations,
research
priorities
overcome
existing
challenges
promote
widespread
adoption.
aims
analyze
growth
integration
NEVs
automotive
industry.
Atmosphere,
Journal Year:
2024,
Volume and Issue:
15(9), P. 1142 - 1142
Published: Sept. 23, 2024
Considering
the
potential
warming
and
long
lifetime
of
nitrous
oxide
(N2O)
as
a
greenhouse
gas,
exploring
its
emission
characteristics
is
great
significance
for
control
achievement
sustainable
development
goals.
As
vehicles
are
significant
source
N2O
emissions,
in
this
study
we
conducted
detailed
investigation
exhaust
light-duty
using
chassis
dynamometer.
We
selected
one
conventional
gasoline
vehicle
two
hybrid
electric
vehicles.
found
that
emissions
from
all
tested
complied
with
China
6
regulation,
factors
7.7
mg/km,
6.8
17.1
respectively,
three
Driving
conditions
played
crucial
role
generated
primarily
during
extra-high-speed
conditions,
possibly
due
to
higher
driving
speed
greater
number
acceleration/deceleration
events.
Furthermore,
while
emitted
less
NOx
compared
vehicles,
their
were
closely
tied
engine
operating
conditions.
Surprisingly,
discovered
more
frequent
start–stop
cycles,
which
could
be
related
mechanisms
generation.
These
findings
contribute
better
understanding
will
inform
strategies
promote
global
development.
Energies,
Journal Year:
2024,
Volume and Issue:
17(14), P. 3413 - 3413
Published: July 11, 2024
The
surge
in
disordered
EV
charging
demand,
driven
by
the
rapid
growth
ownership
of
electric
vehicles
(EVs),
has
highlighted
potential
for
significant
disruptions
photovoltaic
(PV)-connected
distribution
networks
(DNs).
This
escalating
demand
not
only
presents
challenges
meeting
requirements
to
satisfy
owners
and
grid
fast-charging
stations
(GFCSs)
but
also
jeopardizes
stable
operation
network.
To
address
these
challenges,
this
study
introduces
a
novel
model
called
SOR&KANO
decisions,
which
focuses
on
addressing
dual-sided
GFCSs
EVs.
proposed
utilizes
salp
swarm
algorithm-convolutional
neural
network
(SSA-CNN)
predict
PV
output
employs
Monte
Carlo
simulation
estimate
load
EVs,
ensuring
accurate
prediction
efficient
distribution.
optimize
decisions
reserved
EVs
(REVs)
non-reserved
(NREVs),
applies
multi-verse
optimizer
(MVO)
conjunction
with
time-of-use
(TOU)
tariff
guidance.
By
integrating
MVO
algorithm,
approach
enhances
satisfaction
levels
balancing
increasing
utilization
rates,
improving
voltage
quality
within
DN.
Simultaneously,
optimized
scheduling
strategy
reduces
time
costs
while
concerns
related
range
anxiety
driver
fatigue.
efficacy
is
validated
through
modified
IEEE-33
system,
confirming
effectiveness
optimal
methods
study.
