Evaluation of cargo bike program for parcel deliveries in a medium-sized city
Transportation Research Part D Transport and Environment,
Год журнала:
2025,
Номер
140, С. 104609 - 104609
Опубликована: Янв. 27, 2025
Язык: Английский
Electric Vehicles for a Flexible Energy System: Challenges and Opportunities
Energies,
Год журнала:
2024,
Номер
17(22), С. 5614 - 5614
Опубликована: Ноя. 9, 2024
As
the
adoption
of
Electric
Vehicles
(EVs)
accelerates,
driven
by
increasing
urbanization
and
push
for
sustainable
infrastructure,
need
innovative
solutions
to
support
this
growth
has
become
more
pressing.
Vehicle-to-Grid
(V2G)
technology
presents
a
promising
solution
enabling
EVs
engage
in
bidirectional
interactions
with
electrical
grid.
Through
V2G,
can
supply
energy
back
grid
during
peak
demand
periods
draw
power
off-peak
times,
offering
valuable
tool
enhancing
stability,
improving
management,
supporting
environmental
sustainability.
Despite
its
potential,
large-scale
implementation
V2G
faces
significant
challenges,
particularly
from
technological
regulatory
standpoint.
The
success
requires
coordinated
efforts
among
various
stakeholders,
including
vehicle
manufacturers,
infrastructure
providers,
operators,
policymakers.
In
addition
technical
barriers,
such
as
battery
degradation
due
frequent
charging
cycles
advanced
systems,
frameworks
must
evolve
accommodate
new
paradigm.
This
review
aims
provide
comprehensive
analysis
technology,
focusing
on
different
perspectives—such
those
users,
vehicles,
infrastructures,
electricity
study
will
also
explore
ex
ante,
post,
ongoing
assessment
studies,
alongside
experiences
pioneer
cities
implementing
V2G.
Язык: Английский
Enhancing Sustainable Last-Mile Delivery: The Impact of Electric Vehicles and AI Optimization on Urban Logistics
World Electric Vehicle Journal,
Год журнала:
2025,
Номер
16(5), С. 242 - 242
Опубликована: Апрель 22, 2025
The
rapid
growth
of
e-commerce
has
intensified
the
need
for
efficient
and
sustainable
last-mile
delivery
solutions
in
urban
environments.
This
paper
explores
integration
electric
vehicles
(EVs)
artificial
intelligence
(AI)
into
a
combined
framework
to
enhance
environmental,
operational,
economic
performance
logistics.
Through
comprehensive
literature
review,
we
examine
current
trends,
technological
developments,
implementation
challenges
at
intersection
smart
mobility,
green
logistics,
digital
transformation.
We
propose
an
operational
that
leverages
AI
route
optimization,
fleet
coordination,
energy
management
EV-based
networks.
is
validated
through
real-world
case
study
conducted
Lisbon,
Portugal,
where
logistics
provider
implemented
city
consolidation
center
model
supported
by
AI-driven
optimization
tools.
Using
key
indicators—including
time,
consumption,
utilization,
customer
satisfaction,
CO₂
emissions—we
measure
pre-
post-AI
deployment
impacts.
results
demonstrate
significant
improvements
across
all
metrics,
including
15–20%
reduction
10–25%
gain
efficiency,
up
40%
decrease
emissions.
findings
confirm
synergy
between
EVs
provides
robust
scalable
achieving
supporting
broader
mobility
climate
objectives.
Язык: Английский
Driving green change: Commercial sector adopting electric vehicles in Ireland
Transportation Research Part D Transport and Environment,
Год журнала:
2024,
Номер
135, С. 104398 - 104398
Опубликована: Сен. 3, 2024
Язык: Английский
Fuzzy Logic Approach for Evaluating Electromobility Alternatives in Last-Mile Delivery: Belgrade as a Case Study
Energies,
Год журнала:
2024,
Номер
17(24), С. 6307 - 6307
Опубликована: Дек. 13, 2024
This
paper
proposes
a
methodology
based
on
the
fuzzy
approach,
which
provides
decision-making
support
to
organizer
of
last-mile
delivery
(LMD)
in
selecting
sustainable
models
for
specific
territory.
Solving
this
task
is
essential
ensure
that
process
efficient
and
aligned
with
all
three
dimensions
development.
The
goal
select
most
suitable
electromobility
alternative
implementation
characteristics
requirements
current
circumstances.
proposed
involves
creation
mechanism
consisting
series
logic
systems
will
model
expert
opinions
produce
preference
value
as
output,
defining
suitability
applying
particular
LMD
model.
A
methodological
contribution
harmonized
membership
functions
variables
result
comparing
symmetric
asymmetric
aimed
at
achieving
valid
results.
results
guide
making
best
decision
when
choosing
from
analyzed
models.
applicability
adequacy
are
demonstrated
through
analysis
case
study
focused
evaluation
alternatives
part
city
Belgrade.
obtained
values,
range
0
1
tested
variants,
follows
within
interval:
[0.481,
0.776]
e-motorcycles,
[0.376,
0.564]
e-cargo
bikes,
[0.5,
0.624]
e-scooters.
values
these
indicators
aim
decision-makers
defined
given
constraints.
Язык: Английский