Journal of Renewable and Sustainable Energy,
Journal Year:
2023,
Volume and Issue:
15(6)
Published: Nov. 1, 2023
CO2
heat
pump
air
conditioning
(HPAC)
systems
for
electric
vehicles
(EVs)
have
received
widespread
attention
their
excellent
low-temperature
heating
capabilities.
However,
the
range
of
EVs
is
limited
by
battery
energy
storage,
which
makes
demand
system
affect
use
efficiency
drive
battery.
In
order
to
measure
thermal
economy
(AC)
in
terms
heating,
index
coefficient
performance
(COP)
often
used.
Accurate
COP
prediction
can
help
optimize
HPAC
avoid
wastage
and
thus
improve
vehicle.
this
study,
we
a
backpropagation
(BP)
neural
network
combined
with
particle
swarm
optimization
(PSO)
algorithm
predict
EVs.
First,
model
was
established,
consider
variety
influencing
factors,
key
parameters
affecting
AC
were
obtained
through
experiments.
Second,
BP
used
system,
overcome
shortcomings
network,
slow
prone
fall
into
minimum
value,
PSO
introduced
weights
biases
so
as
accuracy
stability
prediction.
Through
combine
achieve
accurate
an
EV,
provides
strong
support
improvement
efficiency.
considered
such
outdoor
temperature,
compressor
speed,
EV
status,
made
more
applicable.
Finally,
method
proposed
study
validated
on
real
dataset,
using
65.8%.
