Batteries,
Год журнала:
2023,
Номер
9(3), С. 181 - 181
Опубликована: Март 20, 2023
The
accuracy
of
capacity
estimation
is
great
importance
to
the
safe,
efficient,
and
reliable
operation
battery
systems.
In
recent
years,
data-driven
methods
have
emerged
as
promising
alternatives
due
higher
accuracy.
Despite
significant
progress,
are
mainly
developed
by
experimental
data
under
well-controlled
charge–discharge
processes,
which
seldom
available
for
practical
health
monitoring
realistic
conditions
uncertainties
in
environmental
operational
conditions.
this
paper,
a
novel
method
estimate
large-format
LiFePO4
batteries
based
on
real
from
electric
vehicles
proposed.
A
comprehensive
dataset
consisting
85
that
has
been
running
around
one
year
diverse
nominal
derived
cloud
platform
generated.
classification
aggregation
prediction
developed,
combining
aging
experiment
with
big
analysis
data.
Based
degradation
mechanisms,
IC
curve
features
extracted,
linear
regression
model
established
realize
high-precision
slow-charging
constant-current
charging.
selected
highly
correlated
(Pearson
correlation
coefficient
<
0.85
all
vehicles),
MSE
results
less
than
1
Ah.
On
basis
protocol
mechanism
studies,
feature
set
including
internal
resistance,
temperature,
statistical
characteristics
voltage
constructed,
neural
network
(NN)
multi-stage
variable-current
fast-charging
Finally,
above
two
models
integrated
achieve
complex
changeable
working
conditions,
relative
error
0.8%.
An
using
battery,
same
those
equipped
dataset,
carried
out
verify
methods.
To
best
authors’
knowledge,
our
study
first
field
an
type
battery.
Energy Material Advances,
Год журнала:
2023,
Номер
4
Опубликована: Янв. 1, 2023
High-capacity
Li-rich
oxide
materials
have
received
extensive
attention
due
to
their
unique
anion–cation
charge
compensation
involvement.
However,
the
high
operating
voltage,
poor
cycling
performance,
unsafe
oxygen
evolution,
and
voltage
decay
limit
industrial
application.
The
emergence
development
of
solid-state
batteries
offer
a
great
opportunity
solve
these
issues
by
replacing
flammable
unstable
liquid
electrolytes
with
solid
electrolytes.
Meanwhile,
utilization
high-capacity
cathodes
enables
establish
high-energy-density
wide
ranges,
light
weight,
mechanical
properties.
This
review
summarizes
recent
progress
electrolytes,
emphasizing
major
advantages,
interface
challenges,
modification
approaches
in
batteries.
We
also
propose
possible
characterization
strategies
for
effective
interfacial
observation
analyses.
It
is
hoped
that
this
should
inspire
rational
design
better
application
portable
devices,
electric
vehicles,
as
well
power
grids.
Advanced Materials,
Год журнала:
2024,
Номер
36(27)
Опубликована: Апрель 18, 2024
Abstract
Quasi‐solid‐state
batteries
(QSSBs)
are
gaining
widespread
attention
as
a
promising
solution
to
improve
battery
safety
performance.
However,
the
improvement
and
underlying
mechanisms
of
QSSBs
remain
elusive.
Herein,
novel
strategy
combining
high‐safety
ethylene
carbonate‐free
liquid
electrolyte
in
situ
polymerization
technique
is
proposed
prepare
practical
QSSBs.
The
Ah‐level
with
LiNi
0.83
Co
0.11
Mn
0.06
O
2
cathode
graphite–silicon
anode
demonstrate
significantly
improved
features
without
sacrificing
electrochemical
As
evidenced
by
accelerating
rate
calorimetry
tests,
exhibit
increased
self‐heating
temperature
onset
(
T
),
decreased
rise
during
thermal
runaway
(TR).
has
maximum
increase
48.4
°C
compared
conventional
batteries.
Moreover,
do
not
undergo
TR
until
180
(even
200
°C)
hot‐box
presenting
significant
that
run
into
at
130
°C.
Systematic
investigations
show
formed
polymer
skeleton
effectively
mitigates
exothermic
reactions
between
lithium
salts
lithiated
anode,
retards
oxygen
release
from
cathode,
inhibits
crosstalk
elevated
temperatures.
findings
offer
an
innovative
for
open
up
new
sight
building
safer
high‐energy‐density
Scientific Reports,
Год журнала:
2024,
Номер
14(1)
Опубликована: Янв. 9, 2024
With
the
development
of
electric
vehicle
industry,
number
power
batteries
has
increased
dramatically.
Establishing
a
recycling
EOL
(end-of-life)
battery
network
for
secondary
use
is
an
effective
way
to
solve
resource
shortage
and
environmental
pollution.
However,
existing
networks
are
challenging
due
high
uncertainty
batteries,
e.g.,
quantity
quality,
resulting
in
low
rate
recovery
network.
To
fill
this
gap,
paper
proposes
stochastic
programming
approach
design
under
uncertain
conditions
batteries.
Firstly,
multi-objective
model
established,
considering
carbon
emissions
economic
benefits.
Secondly,
proposed
clarify
model.
Subsequently,
genetic
algorithm
employed
Finally,
case
Region
T
given
verify
credibility
superiority
method.
The
results
demonstrate
that
reduces
by
20
metric
tons
increases
overall
benefits
10
million
yuan
compared
deterministic
Furthermore,
two
portions
affecting
optimization
also
discussed
provide
reference
reducing
improving
efficiency
networks.
