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T
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[
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8
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[
9
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.
T
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in
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[
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,
[
1
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1
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As
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
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4
I
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Dr
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Vo
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16
,
No
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4
,
Dec
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b
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20
25
:
2699
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2
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[
1
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th
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th
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[
1
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as
d
em
o
n
s
tr
ated
ef
f
icac
y
in
ac
cu
r
ately
esti
m
atin
g
th
e
in
te
r
io
r
tem
p
er
atu
r
e
o
f
b
atter
ies
[
19
]
.
T
h
e
in
cr
e
d
ib
ly
h
ig
h
v
o
lu
m
e
o
f
tr
ain
i
n
g
d
ata
n
ee
d
ed
,
h
o
we
v
er
,
is
a
m
ajo
r
d
is
ad
v
an
tag
e.
Fin
d
i
n
g
t
h
e
in
ter
n
al
tem
p
er
atu
r
e
in
r
ea
l
tim
e
h
as
b
ee
n
m
a
d
e
ea
s
ie
r
with
th
e
u
s
e
o
f
th
e
v
ir
t
u
al
th
e
r
m
al
s
en
s
o
r
(
VT
S)
tech
n
iq
u
e
[
2
0]
-
[2
2
].
T
h
e
v
ar
iatio
n
s
o
f
K
alm
an
Fil
ter
s
wer
e
p
u
t
in
to
p
r
ac
tice
in
s
id
e
t
h
e
t
h
er
m
al
m
o
d
el
to
esti
m
ate
th
e
in
ter
n
al
tem
p
e
r
atu
r
e
[2
3
]
.
B
u
ilt
o
n
th
e
k
in
d
o
f
m
o
d
el
th
e
y
a
r
e
b
u
ilt
o
n
,
VT
S
tem
p
er
atu
r
e
esti
m
atio
n
tech
n
iq
u
es
ca
n
b
e
b
r
o
ad
ly
d
iv
id
e
d
i
n
to
th
r
ee
ca
teg
o
r
ies:
f
u
n
d
am
e
n
tal
co
n
tin
u
u
m
,
r
ed
u
c
ed
-
o
r
d
er
,
an
d
two
/th
r
ee
-
n
o
d
e
th
er
m
al
m
o
d
els [
2
4
]
.
T
h
e
cy
lin
d
r
ical
ce
ll'
s
two
-
n
o
d
e
m
o
d
el
is
b
u
ilt
o
n
t
h
e
k
i
n
d
o
f
m
o
d
el
th
ey
ar
e
b
u
ilt
o
n
;
VT
S
tem
p
er
atu
r
e
esti
m
atio
n
tech
n
i
q
u
es
ca
n
b
e
b
r
o
ad
ly
d
i
v
id
ed
in
to
th
r
ee
ca
teg
o
r
ies:
f
u
n
d
a
m
en
tal
co
n
tin
u
u
m
,
r
ed
u
ce
d
-
o
r
d
e
r
,
a
n
d
two
/th
r
e
e
-
n
o
d
e
t
h
er
m
al
m
o
d
els.
T
h
e
b
a
tter
y
'
s
s
im
p
lifie
d
two
-
n
o
d
e
th
er
m
al
m
o
d
el
[2
0
]
an
d
p
r
is
m
atic
ce
lls
[
2
1
]
wer
e
s
u
g
g
ested
f
o
r
th
e
esti
m
atio
n
o
f
in
ter
n
al
tem
p
er
atu
r
e.
Alo
n
g
th
e
d
ir
ec
tio
n
o
f
elec
tr
o
d
e
th
ick
n
ess
,
o
n
ly
two
n
o
d
es
ar
e
p
o
s
itio
n
ed
.
I
f
th
e
m
o
d
el
p
r
o
jectio
n
s
ar
e
to
b
e
b
eli
ev
ed
,
th
e
C
r
ate
is
lim
ited
to
b
elo
w
1
°C
d
u
e
to
t
h
e
lo
w
co
m
p
u
tin
g
c
o
s
t
an
d
lim
ited
ac
cu
r
ac
y
o
f
th
ese
two
-
n
o
d
e
th
er
m
al
m
o
d
els.
T
ak
in
g
elec
tr
ical
-
t
h
er
m
al
c
o
u
p
lin
g
in
t
o
ac
co
u
n
t
i
n
cr
ea
s
ed
t
h
e
two
-
n
o
d
e
th
er
m
al
m
o
d
el'
s
ac
cu
r
ac
y
[
2
0
]
,
b
u
t
th
e
m
o
d
els
wer
e
s
till
o
n
ly
ap
p
licab
le
to
m
o
d
est
elec
tr
ical
lo
ad
s
.
f
o
r
th
e
s
ec
o
n
d
VT
S
t
y
p
e,
th
e
th
e
r
m
al
m
o
d
el
with
r
ed
u
ce
d
o
r
d
er
h
as
d
em
o
n
s
tr
ated
ef
f
icac
y
in
esti
m
atin
g
tem
p
er
atu
r
e
v
a
r
iatio
n
s
with
in
th
e
ce
ll
as
well
as
v
o
lu
m
e
-
a
v
er
ag
e
d
tem
p
er
atu
r
e
[
2
5
]
.
A
s
im
p
le
E
I
S
co
u
ld
b
e
u
s
ed
to
esti
m
ate
co
r
e
tem
p
er
atu
r
e
[
2
6
]
.
T
h
e
s
e
e
f
f
e
c
t
i
v
e
r
e
d
u
c
e
d
-
o
r
d
e
r
m
o
d
el
i
n
g
t
e
c
h
n
i
q
u
es
,
h
o
w
e
v
e
r
,
a
r
e
o
n
l
y
a
p
p
l
i
c
a
b
le
t
o
2
D
s
i
m
p
l
i
f
i
c
at
i
o
n
a
n
d
m
il
d
d
i
s
c
h
a
r
g
e
c
u
r
r
e
n
t
c
i
r
c
u
m
s
t
a
n
c
es
.
D
u
e
t
o
t
h
e
l
at
t
e
r
l
i
m
it
a
ti
o
n
,
t
h
e
s
e
t
e
c
h
n
i
q
u
es
a
r
e
n
o
t
a
p
p
r
o
p
r
i
a
t
e
f
o
r
p
r
a
ct
i
c
a
l,
a
p
p
l
i
c
a
t
i
o
n
-
r
e
le
v
a
n
t
t
h
e
r
m
al
l
im
i
t
c
o
n
d
i
ti
o
n
s
l
i
k
e
b
o
tt
o
m
a
n
d
s
i
d
e
c
o
o
l
i
n
g
.
T
h
e
th
ir
d
VT
S
t
y
p
e
u
s
es
co
n
tin
u
u
m
m
o
d
els
b
ased
o
n
p
h
y
s
ics
to
esti
m
ate
tem
p
er
atu
r
e
[
2
7
]
.
T
h
e
av
er
ag
e
tem
p
er
atu
r
e
o
f
th
e
b
u
lk
ce
ll
is
esti
m
ated
b
ased
o
n
an
e
x
ten
d
ed
Kalm
a
n
f
ilter
(
E
KF
)
o
n
a
lu
m
p
ed
elec
tr
o
ch
em
ical
th
er
m
al
m
o
d
el.
H
o
wev
er
,
b
ec
a
u
s
e
o
f
th
eir
r
elativ
ely
h
ig
h
c
o
m
p
u
tin
g
co
s
t,
s
u
ch
co
n
tin
u
u
m
m
o
d
el
s
ar
e
n
o
t a
p
p
r
o
p
r
iate
f
o
r
esti
m
atin
g
tem
p
er
atu
r
e
at
wid
ely
d
is
tr
ib
u
ted
lo
ca
tio
n
s
[
2
1
].
T
o
o
ls
f
o
r
ef
f
ec
ti
v
ely
esti
m
atin
g
th
e
in
ter
io
r
d
is
tr
ib
u
tio
n
o
f
tem
p
er
at
u
r
es
with
ap
p
licatio
n
-
r
elev
a
n
t th
er
m
al
lim
its
an
d
a
s
p
ec
tr
u
m
o
f
e
lectr
ical
lo
ad
s
h
av
e
b
ee
n
f
ew
u
n
til
now
.
I
n
o
r
d
er
t
o
f
o
r
ec
ast
th
e
in
te
r
io
r
tem
p
er
atu
r
es
o
f
L
I
B
s
u
n
d
e
r
v
ar
io
u
s
cu
r
r
en
t
a
n
d
a
m
b
ien
t
te
m
p
er
atu
r
e
cir
cu
m
s
tan
ce
s
,
th
is
r
esear
ch
p
r
esen
ts
a
n
o
v
el
th
er
m
al
m
o
d
e
lin
g
f
r
am
ewo
r
k
.
E
ac
h
o
f
th
e
t
h
r
ee
s
o
p
h
is
ticated
ap
p
r
o
ac
h
es
in
clu
d
ed
in
th
e
f
r
am
ewo
r
k
,
NN
-
L
M,
NN
-
B
R
,
an
d
GPM
,
is
in
ten
d
ed
to
m
ax
im
ize
th
e
tr
ad
e
-
o
f
f
b
etwe
en
co
m
p
u
tatio
n
al
r
eso
u
r
ce
s
an
d
f
o
r
ec
ast
ac
cu
r
ac
y
[2
8
]
.
T
h
e
m
o
d
el'
s
d
ep
en
d
ab
ilit
y
h
as
b
ee
n
ex
ten
s
iv
ely
v
alid
ated
th
r
o
u
g
h
tr
ials
d
o
n
e
o
v
er
a
wid
e
v
ar
iety
o
f
a
m
b
ien
t te
m
p
er
atu
r
es,
f
r
o
m
-
20
°C
to
2
5
°C
.
No
tab
ly
,
th
e
GPM
s
h
o
ws
an
ex
ce
p
tio
n
all
y
lo
w
R
MSE
o
f
0
.
0
3
4
%,
m
ak
in
g
it
th
e
m
o
s
t
ac
cu
r
ate
m
o
d
el
am
o
n
g
th
o
s
e
ex
am
in
ed
.
Fu
r
th
er
m
o
r
e,
th
e
NN
-
L
M
ap
p
r
o
ac
h
tu
r
n
s
o
u
t
to
b
e
a
c
o
m
p
u
tatio
n
ally
ef
f
icien
t
s
u
b
s
titu
te,
esp
ec
ially
u
s
ef
u
l
in
s
itu
atio
n
s
wh
en
q
u
ick
c
o
m
p
u
tin
g
r
esu
lts
ar
e
cr
u
cial,
in
ad
d
itio
n
to
b
ein
g
h
ig
h
ly
ef
f
ec
tiv
e
at
p
r
ed
ictin
g
tem
p
er
atu
r
e
[
29
]
.
th
e
cr
ea
ted
th
er
m
al
m
o
d
el
is
also
u
s
ed
to
ass
ess
v
ar
iatio
n
s
i
n
b
atter
y
ca
p
ac
it
y
.
T
h
is
im
p
o
r
tan
t
d
ev
el
o
p
m
en
t
s
u
cc
ess
f
u
lly
co
n
n
ec
ts
th
eo
r
etic
al
u
n
d
e
r
s
tan
d
in
g
with
r
ea
l
-
wo
r
ld
ap
p
licatio
n
s
b
y
co
m
b
in
in
g
h
ea
t m
o
d
elin
g
a
n
d
ca
p
ac
ity
ass
ess
m
en
t.
T
h
e
s
tr
u
ctu
r
e
o
f
th
is
m
an
u
s
cr
i
p
t
is
o
r
g
an
ized
as
f
o
llo
ws:
i)
Sectio
n
1
o
f
f
er
s
a
co
m
p
r
eh
e
n
s
iv
e
r
ev
iew
o
f
th
e
liter
atu
r
e,
e
x
am
in
in
g
ex
is
tin
g
ap
p
r
o
ac
h
es
to
lith
iu
m
-
i
o
n
b
atter
y
t
h
er
m
al
m
o
d
elin
g
a
n
d
th
eir
lim
itatio
n
s
;
ii)
Sectio
n
2
p
r
esen
ts
th
e
ex
p
er
im
en
tal
s
etu
p
an
d
p
r
o
v
id
e
s
a
d
etailed
d
escr
ip
tio
n
o
f
t
h
e
d
ataset,
in
clu
d
in
g
d
r
iv
e
c
y
cle
p
r
o
f
iles
a
n
d
th
er
m
al
ch
am
b
er
c
o
n
d
itio
n
s
ac
r
o
s
s
a
r
an
g
e
o
f
am
b
ien
t
tem
p
er
a
tu
r
es
;
iii)
Sectio
n
3
o
u
tlin
es
th
e
p
r
o
p
o
s
ed
m
eth
o
d
o
lo
g
y
,
f
o
cu
s
in
g
o
n
th
e
d
e
v
elo
p
m
en
t
an
d
im
p
lem
en
tatio
n
o
f
th
r
ee
th
er
m
al
m
o
d
elin
g
ap
p
r
o
ac
h
es:
n
e
u
r
al
n
etwo
r
k
s
u
s
in
g
L
ev
e
n
b
er
g
-
M
ar
q
u
ar
d
t
(
NN
-
L
M)
an
d
B
ay
e
s
ian
re
g
u
lar
izatio
n
(
NN
-
B
R
)
,
as
well
as
Gau
s
s
ia
n
p
r
o
ce
s
s
m
o
d
elin
g
(
GPM)
a
ls
o
r
ep
o
r
ts
t
h
e
s
im
u
latio
n
an
d
v
alid
atio
n
r
esu
lts
,
in
clu
d
in
g
a
co
m
p
a
r
ativ
e
an
al
y
s
is
o
f
m
o
d
el
p
e
r
f
o
r
m
an
ce
b
ased
o
n
R
MSE
m
etr
ics
an
d
p
ar
ity
p
lo
ts
,
an
d
ex
p
lo
r
es
th
e
ap
p
licatio
n
o
f
th
e
th
er
m
al
m
o
d
el
f
o
r
p
r
ed
ictin
g
b
atter
y
ca
p
ac
ity
u
n
d
e
r
v
ar
y
in
g
th
er
m
al
co
n
d
itio
n
s
;
an
d
iv
)
Sectio
n
4
co
n
clu
d
es
th
e
s
tu
d
y
b
y
s
u
m
m
ar
izin
g
th
e
k
ey
f
in
d
i
n
g
s
an
d
p
r
o
p
o
s
in
g
f
u
tu
r
e
r
esear
ch
d
ir
ec
tio
n
s
f
o
r
en
h
an
c
ed
b
atter
y
m
a
n
ag
em
e
n
t sy
s
tem
s
.
2.
M
E
T
H
O
D
T
h
is
s
ec
tio
n
p
r
esen
ts
th
e
m
eth
o
d
o
lo
g
y
u
s
ed
to
m
o
d
el
t
h
e
in
ter
n
al
tem
p
e
r
atu
r
e
o
f
l
ith
iu
m
-
io
n
b
atter
ies
as
a
f
u
n
ctio
n
o
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e
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r
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s
with
d
ata
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llectio
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f
r
o
m
r
ea
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tic
d
r
iv
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cy
cles
f
o
llo
wed
b
y
p
r
e
p
r
o
ce
s
s
in
g
an
d
a
n
aly
s
is
.
T
h
r
ee
m
o
d
elin
g
tech
n
iq
u
es
a
r
e
ap
p
lied
n
eu
r
al
n
etwo
r
k
s
(
NN)
,
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
A
d
va
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ce
d
th
erma
l m
o
d
elin
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f lith
iu
m
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izatio
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ith
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r
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ay
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ated
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2
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1
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F
l
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T
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al
m
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p
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s
,
as
illu
s
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ated
in
Fig
u
r
e
1
,
b
eg
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s
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ata
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o
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m
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c
y
cles.
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h
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ata
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d
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u
r
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en
t
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I
)
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n
d
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i
en
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at
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e
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T
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ich
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e
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ata
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ip
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atter
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ak
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ip
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eq
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iter
ativ
e
tu
n
in
g
L
M
a
n
d
B
R
ar
e
o
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izatio
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tech
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h
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M
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im
izes
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ile
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R
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els
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ated
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ate
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GP
M
was
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MA
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M
B
C
T
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o
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ate
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ter
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ter
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u
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a
Ga
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e
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s
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th
e
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b
ased
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(
MBC
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t
o
o
lb
o
x
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MA
T
L
AB
/Si
m
u
lin
k
.
−
I
n
p
u
t
d
ata
p
r
e
p
ar
atio
n
:
T
h
e
Sig
n
al
b
u
ild
e
r
b
lo
c
k
was u
s
ed
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Simu
lin
k
to
g
e
n
er
ate
r
ea
lis
tic
in
p
u
t p
r
o
f
iles
.
−
C
o
n
s
tr
u
ctio
n
o
f
t
h
e
tr
ain
in
g
d
a
taset:
T
h
e
tr
ain
in
g
d
ataset
was c
o
n
s
tr
u
cted
u
s
in
g
th
e
tu
p
les [
I
,
T
a]
→T
i.
−
Mo
d
el
f
itti
n
g
with
GPM
(
MB
C
to
o
lb
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x
)
:
Usi
n
g
th
e
MBC
to
o
lb
o
x
,
th
e
tr
ai
n
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g
d
ataset
was
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ir
s
t
im
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o
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ted
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to
th
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ir
o
n
m
en
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.
T
h
e
in
p
u
t
v
ar
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les
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e
d
ef
in
ed
as
cu
r
r
e
n
t
an
d
am
b
ie
n
t
te
m
p
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e,
wh
ile
th
e
o
u
tp
u
t
v
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r
iab
le
was
s
et
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ter
n
al
tem
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er
atu
r
e
.
A
Gau
s
s
ian
p
r
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s
s
m
o
d
el
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th
en
f
it
ted
u
s
in
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eith
er
th
e
d
ef
au
lt
k
e
r
n
el
f
u
n
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o
p
tim
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n
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r
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s
s
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ted
th
r
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g
h
cr
o
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,
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d
th
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m
o
d
el'
s
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er
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o
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ated
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s
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iag
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lcu
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ally
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tr
ain
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d
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ted
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m
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lin
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s
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n
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th
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g
en
er
ate
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lin
k
b
l
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ck
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tu
r
e
f
o
r
in
teg
r
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to
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im
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en
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ir
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m
en
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L
M
an
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B
R
wer
e
d
ev
elo
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ed
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o
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win
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th
e
s
am
e
s
tep
s
u
s
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th
e
m
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el
f
itti
n
g
f
e
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r
es
o
f
th
e
n
eu
r
al
n
etwo
r
k
to
o
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x
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Fig
u
r
e
1
.
Dev
el
o
p
m
en
t
o
f
a
t
h
er
m
al
m
o
d
elin
g
s
tr
ateg
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s
in
g
th
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eth
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
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8
6
9
4
I
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t J Po
w
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lec
&
Dr
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t
,
Vo
l.
16
,
No
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4
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Dec
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er
20
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2699
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2
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u
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aso
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atter
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illi
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1
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s
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lin
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atter
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,
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u
r
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3
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r
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atter
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itio
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atter
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atter
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e
u
n
d
er
r
ea
lis
tic
d
r
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c
o
n
d
itio
n
s
.
Fig
u
r
e
2
. C
u
r
r
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n
t p
r
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iles
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e
T
R
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
A
d
va
n
ce
d
th
erma
l m
o
d
elin
g
o
f lith
iu
m
-
io
n
b
a
tter
ies:
fo
u
n
d
a
tio
n
s
fo
r
a
d
va
n
ce
d
…
(
A
b
d
elh
a
d
i E
lka
ke
)
2703
Fig
u
r
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3
.
C
o
m
p
a
r
is
o
n
o
f
v
ar
io
u
s
cu
r
r
en
t
p
r
o
f
iles
at
d
if
f
er
en
t
T
R
2
.
3
.
N
eura
l net
wo
r
k
m
et
ho
d
T
h
e
n
e
u
r
al
n
etwo
r
k
(
NN)
ap
p
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o
m
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el
t
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e
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ip
b
etwe
en
th
e
in
p
u
t
p
ar
am
eter
s
,
cu
r
r
en
t
(
I
)
an
d
am
b
ien
t
tem
p
e
r
atu
r
e
(
T
a
)
—
an
d
t
h
e
o
u
tp
u
t
w
h
ich
is
th
e
in
te
r
n
al
b
atter
y
te
m
p
er
atu
r
e
(
T
i)
.
T
h
e
n
etwo
r
k
t
y
p
ically
c
o
n
s
is
ts
o
f
m
u
ltip
le
lay
er
s
,
in
cl
u
d
in
g
o
n
e
o
r
m
o
r
e
h
i
d
d
en
lay
er
s
,
with
(
1
)
as
th
e
m
ath
em
atica
l r
ep
r
esen
tatio
n
f
o
r
a
s
in
g
le
h
i
d
d
en
la
y
er
.
=
∅
(
∑
2
∗
(
∑
1
∗
+
1
=
1
)
ℎ
=
1
+
2
)
(
1
)
W
h
er
e:
−
R
ep
r
esen
ts
th
e
in
p
u
ts
(
I
an
d
T
a)
.
−
1
an
d
2
ar
e
th
e
weig
h
ts
co
n
n
ec
tin
g
th
e
in
p
u
t
an
d
t
h
e
h
id
d
en
lay
er
,
an
d
th
e
h
i
d
d
en
lay
e
r
t
o
th
e
o
u
tp
u
t
,
r
esp
ec
tiv
ely
.
−
1
an
d
2
ar
e
b
ias ter
m
s
.
−
i
s
th
e
ac
tiv
atio
n
f
u
n
ctio
n
f
o
r
t
h
e
h
id
d
e
n
lay
er
.
−
∅
i
s
th
e
o
u
tp
u
t a
ctiv
atio
n
f
u
n
ctio
n
(
co
m
m
o
n
ly
lin
ea
r
f
o
r
r
eg
r
ess
io
n
task
s
)
.
−
ℎ
I
s
th
e
n
u
m
b
er
o
f
n
eu
r
o
n
s
in
t
h
e
h
id
d
e
n
lay
er
.
2
.
3
.
1
.
O
ptim
iza
t
io
n a
lg
o
ri
t
hm
s
T
wo
co
m
m
o
n
ly
u
s
ed
o
p
tim
iza
tio
n
alg
o
r
ith
m
s
in
n
eu
r
al
n
etwo
r
k
tr
ain
i
n
g
ar
e
:
−
L
ev
en
b
er
g
-
Ma
r
q
u
ar
d
t
(
LM
)
:
T
h
is
alg
o
r
ith
m
is
a
co
m
b
in
ati
o
n
o
f
g
r
ad
ien
t
d
escen
t
an
d
th
e
Gau
s
s
-
New
to
n
m
eth
o
d
.
I
t
o
p
tim
izes
th
e
n
etwo
r
k
p
ar
a
m
eter
s
to
m
in
im
ize
th
e
co
s
t
f
u
n
ctio
n
,
wh
ic
h
is
g
en
er
ally
th
e
m
ea
n
s
q
u
ar
ed
er
r
o
r
,
as in
(
2
)
.
E
(
)
=
1
2
⁄
(
∑
(
−
̂
)
2
=
1
)
(
2
)
W
h
er
e
an
d
̂
ar
e
th
e
m
ea
s
u
r
e
d
an
d
p
r
e
d
icted
tem
p
e
r
atu
r
es
,
r
esp
ec
tiv
ely
,
a
n
d
r
ep
r
esen
ts
th
e
m
o
d
el'
s
p
ar
am
eter
s
.
−
B
ay
esian
r
eg
u
lar
izatio
n
(
BR
)
:
T
h
is
m
eth
o
d
in
tr
o
d
u
ce
s
a
r
eg
u
lar
izatio
n
ter
m
in
to
th
e
c
o
s
t
f
u
n
ctio
n
to
b
alan
ce
ac
cu
r
ac
y
an
d
g
en
e
r
aliza
tio
n
.
T
h
e
m
o
d
if
ied
co
s
t f
u
n
c
tio
n
is
as (
3
)
.
E
(
)
=
2
⁄
(
∑
(
−
̂
)
2
=
1
)
+
2
⁄
‖
‖
2
(
3
)
W
h
er
e
α
an
d
β
c
o
n
tr
o
l th
e
tr
ad
e
-
o
f
f
b
etwe
en
f
itti
n
g
th
e
d
ata
an
d
m
o
d
el
co
m
p
lex
ity
.
2
.
4
.
P
G
M
m
et
ho
d
T
h
e
PGM
o
f
f
er
s
a
p
r
o
b
ab
ilis
tic
p
er
s
p
ec
tiv
e
to
th
e
m
o
d
elin
g
p
r
o
b
lem
.
I
t
ass
u
m
es
a
p
r
i
o
r
d
i
s
tr
ib
u
tio
n
o
v
er
f
u
n
ctio
n
s
th
at
r
elate
I
,
T
a
,
an
d
Ti
.
T
h
is
r
elatio
n
s
h
ip
ca
n
b
e
ex
p
r
ess
ed
as
(
4
)
.
Ti
~
GP
(
(
)
,
(
,
́
)
)
(
4
)
Her
e:
−
(
)
is
th
e
m
ea
n
f
u
n
ctio
n
,
o
f
ten
in
it
ialized
to
ze
r
o
f
o
r
s
im
p
licity
(
(
)
=
0
).
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
16
,
No
.
4
,
Dec
em
b
er
20
25
:
2699
-
2
7
1
0
2704
−
(
,
́
)
is
th
e
co
v
ar
ian
ce
(
o
r
k
er
n
el)
f
u
n
ctio
n
th
at
q
u
a
n
tifie
s
th
e
s
im
ilar
ity
b
etwe
en
an
y
two
d
ata
p
o
in
ts
an
d
́
A
co
m
m
o
n
l
y
u
s
ed
k
e
r
n
el
is
th
e
s
q
u
ar
ed
ex
p
o
n
e
n
tial:
K
(
,
́
)
=
2
(
‖
−
́
‖
2
2
2
)
(
5
)
W
h
er
e
=
[
I
,
T
a]
,
is
th
e
len
g
t
h
s
ca
le,
an
d
2
is
th
e
s
ig
n
al
v
ar
ian
ce
.
W
h
en
p
r
o
v
id
ed
with
tr
a
in
in
g
d
ata
{
,
}
,
th
e
m
o
d
el
co
m
p
u
tes th
e
p
o
s
t
er
io
r
d
is
tr
ib
u
tio
n
o
f
Ti
f
o
r
n
e
w
in
p
u
ts
∗
,
as in
(
6
)
.
(
⋮
,
∗
,
∗
)
=
(
∗
,
∁
∗
)
(
6)
W
h
er
e:
∗
i
s
th
e
p
o
s
ter
io
r
m
ea
n
;
∁
∗
i
s
th
e
p
o
s
ter
io
r
co
v
ar
ian
ce
m
a
tr
ix
.
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
e
th
er
m
al
m
o
d
elin
g
f
r
a
m
ewo
r
k
was
d
ev
elo
p
e
d
u
s
in
g
MA
T
L
AB
/
Simu
lin
k
Fig
u
r
e
4
,
lev
er
ag
in
g
its
g
r
ap
h
ical
p
r
o
g
r
am
m
in
g
en
v
ir
o
n
m
en
t
t
o
in
teg
r
ate
an
d
co
m
p
ar
e
th
r
ee
ad
v
a
n
ce
d
m
o
d
elin
g
ap
p
r
o
ac
h
es.
T
h
e
m
o
d
el
p
r
o
ce
s
s
es
in
p
u
t
p
ar
am
e
ter
s
,
in
clu
d
in
g
cu
r
r
e
n
t
(
I
)
an
d
am
b
ien
t
tem
p
er
atu
r
e
(
T
a)
,
to
p
r
ed
ict
th
e
in
ter
n
al
b
atter
y
tem
p
er
atu
r
e
(
T
i)
.
T
h
ese
p
r
ed
ictio
n
s
ar
e
ac
h
ie
v
ed
th
r
o
u
g
h
t
h
r
ee
d
is
tin
ct
m
eth
o
d
o
lo
g
ies:
NN
-
L
M,
NN
-
B
R
,
an
d
th
e
PGM.
E
ac
h
m
e
th
o
d
is
im
p
lem
en
ted
with
in
d
ed
icate
d
Simu
lin
k
b
lo
ck
s
,
e
n
ab
lin
g
a
s
ea
m
less
co
m
p
ar
is
o
n
o
f
th
eir
p
er
f
o
r
m
an
ce
.
3
.
1
.
Va
lid
a
t
i
o
n wit
h NN
-
LM
I
n
itially
,
T
ab
le
1
,
th
e
m
o
d
el
was
test
ed
w
ith
1
0
HN,
y
ield
in
g
an
MSE
o
f
ap
p
r
o
x
im
ately
0
.
0
4
0
6
f
o
r
tr
ain
in
g
a
n
d
v
alid
atio
n
,
with
a
co
r
r
elatio
n
co
e
f
f
icien
t
(
R
)
v
alu
e
o
f
0
.
9
9
9
9
1
,
in
d
icatin
g
ex
ce
llen
t
co
r
r
elatio
n
.
As
th
e
n
u
m
b
er
o
f
h
id
d
e
n
n
e
u
r
o
n
s
was
in
cr
ea
s
ed
to
3
0
,
t
h
e
MSE
s
ig
n
if
ican
tly
d
ec
r
ea
s
ed
to
0
.
0
0
8
5
1
f
o
r
tr
ain
in
g
,
with
a
co
r
r
esp
o
n
d
in
g
R
v
alu
e
o
f
0
.
9
9
9
9
8
.
T
h
e
b
e
s
t
r
esu
lts
wer
e
o
b
tain
ed
with
5
0
h
id
d
e
n
n
eu
r
o
n
s
,
wh
er
e
th
e
t
r
ain
in
g
MSE
r
ea
c
h
ed
a
m
in
im
u
m
o
f
0
.
0
0
6
7
3
a
n
d
an
R
v
alu
e
o
f
0
.
9
9
9
9
9
,
d
em
o
n
s
tr
atin
g
n
ea
r
-
p
er
f
ec
t c
o
r
r
elatio
n
.
Fig
u
r
e
4
.
MA
T
L
AB
/Si
m
u
lin
k
th
er
m
al
m
o
d
el
T
ab
le
1
.
NN
-
LM
p
e
r
f
o
r
m
an
ce
m
etr
ics
-
MSE
an
d
r
eg
r
ess
io
n
(
R
)
f
o
r
d
if
f
e
r
en
t h
i
d
d
en
la
y
er
c
o
n
f
ig
u
r
atio
n
s
I
n
d
i
c
a
t
o
r
s
Le
v
e
n
b
e
r
g
-
M
a
r
q
u
a
r
d
t
a
l
g
o
r
i
t
h
m
p
e
r
f
o
r
man
c
e
H
i
d
d
e
n
1
0
H
i
d
d
e
n
3
0
H
i
d
d
e
n
5
0
M
S
E
R
M
S
E
R
M
S
E
R
Tr
a
i
n
i
n
g
0
.
0
4
0
6
0
.
9
9
9
9
1
0
.
0
0
8
5
1
0
.
9
9
9
9
8
0
.
0
0
6
7
3
0
.
9
9
9
9
9
V
a
l
i
d
a
t
i
o
n
0
.
0
4
0
.
9
9
9
9
1
0
.
0
0
8
7
9
0
.
9
9
9
9
8
0
.
0
0
6
7
2
0
.
9
9
9
9
9
Te
st
i
n
g
0
.
0
4
0
4
0
.
9
9
9
9
1
0
.
0
0
8
9
4
0
.
9
9
9
9
8
0
.
0
0
6
9
8
0
.
9
9
9
9
9
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
A
d
va
n
ce
d
th
erma
l m
o
d
elin
g
o
f lith
iu
m
-
io
n
b
a
tter
ies:
fo
u
n
d
a
tio
n
s
fo
r
a
d
va
n
ce
d
…
(
A
b
d
elh
a
d
i E
lka
ke
)
2705
T
o
co
n
f
i
r
m
th
e
o
p
tim
ality
o
f
th
e
m
o
d
el,
a
d
d
itio
n
al
test
in
g
was
co
n
d
u
cted
with
7
0
h
id
d
e
n
n
eu
r
o
n
s
.
Ho
wev
er
,
th
e
MSE
i
n
cr
ea
s
ed
s
lig
h
tly
co
m
p
ar
ed
to
th
e
c
o
n
f
ig
u
r
atio
n
with
5
0
h
id
d
e
n
n
eu
r
o
n
s
,
in
d
icatin
g
o
v
er
f
itti
n
g
o
r
d
im
in
is
h
in
g
r
et
u
r
n
s
with
a
lar
g
e
r
n
etwo
r
k
s
ize.
B
ased
o
n
th
ese
r
esu
lts
,
th
e
NN
m
o
d
el
with
5
0
h
id
d
en
n
eu
r
o
n
s
was
s
elec
ted
as
it
ac
h
iev
ed
th
e
lo
west
MSE
wh
ile
m
ain
tain
in
g
ex
ce
llen
t
g
en
er
aliza
tio
n
.
Fig
u
r
e
5
illu
s
tr
ates
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
n
eu
r
al
n
etwo
r
k
(
NN)
tr
ain
ed
with
th
e
L
e
v
en
b
e
r
g
-
Ma
r
q
u
ar
d
t
(
L
M
)
alg
o
r
ith
m
in
p
r
e
d
ictin
g
th
e
in
ter
n
al
tem
p
er
atu
r
e
(
T
i)
o
f
th
e
b
atter
y
ac
r
o
s
s
d
if
f
er
e
n
t
am
b
i
en
t
co
n
d
itio
n
s
:
T
R
.
T
h
ese
r
esu
lts
p
r
o
v
id
e
v
alu
a
b
l
e
in
s
ig
h
ts
in
to
th
e
m
o
d
el'
s
ac
cu
r
ac
y
a
n
d
r
eliab
ilit
y
,
as
ev
id
en
ce
d
b
y
th
e
s
tr
o
n
g
co
r
r
elatio
n
b
etwe
en
p
r
e
d
icted
an
d
m
ea
s
u
r
ed
tem
p
er
at
u
r
es.
T
h
ese
r
esu
lts
h
ig
h
lig
h
t
th
e
s
tr
en
g
th
o
f
th
e
NN
-
L
M
m
o
d
el
in
ac
cu
r
ately
r
ep
r
esen
tin
g
th
e
th
er
m
al
b
eh
av
i
o
r
o
f
th
e
b
atter
y
.
T
h
e
co
n
s
is
ten
tl
y
h
ig
h
p
er
f
o
r
m
an
ce
v
alid
ates
th
e
ar
ch
itectu
r
e
an
d
o
p
tim
izatio
n
m
eth
o
d
,
estab
lis
h
in
g
th
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ap
p
r
o
ac
h
as
a
r
elia
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le
to
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f
o
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th
er
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a
l
m
o
d
elin
g
i
n
b
atter
y
m
an
ag
e
m
en
t sy
s
tem
s
.
3
.
2
.
Va
lid
a
t
i
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n wit
h NN
-
BR
T
h
e
r
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ab
le
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th
e
n
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r
al
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r
k
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ay
esian
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eg
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lar
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NN
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B
R
m
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el
h
i
g
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lig
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t
its
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ce
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tio
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al
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ilit
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t
o
ac
cu
r
a
tely
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r
ed
ict
b
atter
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th
er
m
al
b
eh
av
io
r
.
W
ith
1
0
h
id
d
en
n
eu
r
o
n
s
,
th
e
m
o
d
el
ac
h
iev
es
an
MSE
o
f
0
.
0
2
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7
a
n
d
a
n
R
R
R
v
alu
e
o
f
0
.
9
9
9
9
5
,
in
d
icatin
g
s
tr
o
n
g
p
r
e
d
ictiv
e
a
cc
u
r
ac
y
.
I
n
c
r
ea
s
in
g
th
e
h
id
d
e
n
n
e
u
r
o
n
s
to
3
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ig
n
i
f
ican
tly
r
ed
u
ce
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th
e
MSE
to
0
.
0
0
7
1
3
,
with
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n
R
R
R
v
alu
e
o
f
0
.
9
9
9
9
8
,
s
h
o
win
g
en
h
an
ce
d
p
er
f
o
r
m
a
n
ce
.
T
h
e
b
est
r
esu
lts
ar
e
o
b
tain
e
d
with
5
0
h
i
d
d
en
n
eu
r
o
n
s
,
wh
er
e
t
h
e
m
o
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el
ac
h
iev
es
its
lo
west M
SE
o
f
0
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0
0
7
0
8
a
n
d
a
n
R
R
R
v
alu
e
o
f
0
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9
9
9
9
8
,
d
em
o
n
s
tr
atin
g
n
ea
r
-
p
er
f
e
ct
co
r
r
ela
tio
n
.
T
h
ese
f
in
d
in
g
s
co
n
f
ir
m
th
at
5
0
h
id
d
e
n
n
eu
r
o
n
s
s
tr
ik
e
th
e
o
p
tim
al
b
alan
ce
b
etwe
en
ac
cu
r
ac
y
an
d
g
en
er
al
izatio
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,
s
h
o
wca
s
in
g
th
e
r
o
b
u
s
tn
ess
an
d
r
eliab
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y
o
f
th
e
B
ay
esian
r
eg
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lar
izatio
n
m
eth
o
d
f
o
r
b
atter
y
th
er
m
al
m
o
d
elin
g
.
Fig
u
r
e
5
.
NN
-
L
M
m
o
d
el
v
alid
atio
n
f
o
r
d
if
f
er
e
n
t te
m
p
er
at
u
r
e
s
TR
T
ab
le
2
.
NN
-
BR
p
er
f
o
r
m
an
ce
m
etr
ics
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MSE
an
d
r
e
g
r
ess
io
n
(
R
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f
o
r
d
if
f
er
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id
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e
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f
ig
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s
I
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d
i
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r
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a
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i
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i
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Tr
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9
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9
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5
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9
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9
9
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st
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5
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.
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9
9
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0
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0
0
7
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8
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.
9
9
9
9
8
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
16
,
No
.
4
,
Dec
em
b
er
20
25
:
2699
-
2
7
1
0
2706
Fig
u
r
e
6
o
b
tain
e
d
with
th
e
N
N
B
ay
esian
r
eg
u
lar
izatio
n
(
B
R
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m
o
d
el
illu
s
tr
ate
its
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tr
o
n
g
p
r
ed
ictiv
e
p
er
f
o
r
m
an
ce
ac
r
o
s
s
v
ar
io
u
s
a
m
b
ien
t
tem
p
er
at
u
r
es,
in
clu
d
i
n
g
-
20
°C
,
-
10
°C
,
0
°C
,
1
0
°
C
,
an
d
2
5
°C
.
T
h
e
p
ar
ity
p
lo
ts
f
o
r
ea
ch
tem
p
er
at
u
r
e
s
h
o
w
a
clea
r
alig
n
m
en
t
o
f
d
ata
p
o
in
ts
alo
n
g
th
e
d
iag
o
n
al
lin
e,
in
d
icatin
g
a
clo
s
e
m
atch
b
etwe
en
t
h
e
p
r
ed
i
cted
an
d
ac
tu
al
b
atter
y
tem
p
e
r
atu
r
es.
T
h
is
alig
n
m
en
t
d
em
o
n
s
tr
ates
th
e
m
o
d
el'
s
ab
ilit
y
to
ca
p
tu
r
e
th
e
u
n
d
e
r
ly
in
g
th
er
m
al
b
e
h
av
io
r
o
f
th
e
b
atter
y
ac
cu
r
ately
.
T
h
ese
v
is
u
a
l
r
esu
lts
p
r
o
v
id
e
a
clea
r
an
d
in
tu
itiv
e
r
e
p
r
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tat
io
n
o
f
th
e
ac
c
u
r
ac
y
a
n
d
r
elia
b
ilit
y
o
f
th
e
B
R
m
o
d
el,
alo
n
g
s
id
e
its
co
m
p
ar
is
o
n
with
th
e
L
M
ap
p
r
o
ac
h
.
W
h
ile
b
o
th
m
eth
o
d
s
d
em
o
n
s
tr
ate
s
tr
o
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g
p
r
ed
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ca
p
a
b
ilit
ies.
Fig
u
r
e
6
.
NN
-
B
R
m
o
d
el
v
alid
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n
f
o
r
d
if
f
er
e
n
t te
m
p
er
at
u
r
e
s
TR
3
.
3
.
V
a
lid
a
t
i
o
n wit
h
G
P
M
T
h
e
GPM
Fig
u
r
e
7
d
eliv
e
r
s
ex
ce
p
tio
n
al
ac
cu
r
ac
y
in
p
r
ed
ict
in
g
th
e
in
ter
n
al
tem
p
er
atu
r
e
(
T
i)
o
f
th
e
b
atter
y
u
n
d
er
v
ar
y
i
n
g
a
m
b
ien
t
co
n
d
itio
n
s
,
in
clu
d
i
n
g
-
20
°C
,
-
10
°C
,
0
°C
,
1
0
°C
,
an
d
2
5
°C
.
T
h
e
p
ar
ity
p
lo
ts
s
h
o
w
an
alm
o
s
t
p
er
f
ec
t
m
atch
b
etwe
en
th
e
p
r
ed
icted
an
d
ac
tu
al
v
alu
es,
with
th
e
d
ata
p
o
in
ts
clo
s
ely
f
o
llo
win
g
th
e
d
iag
o
n
al
lin
e,
h
ig
h
lig
h
tin
g
th
e
m
o
d
el'
s
ab
ilit
y
to
ca
p
tu
r
e
th
e
in
tr
icate
th
er
m
al
d
y
n
a
m
ics
o
f
th
e
b
atter
y
.
Ach
iev
in
g
an
R
MSE
o
f
0
.
0
3
4
%,
GPM
s
tan
d
s
o
u
t
as
th
e
m
o
s
t
ac
cu
r
ate
m
eth
o
d
am
o
n
g
th
o
s
e
test
ed
,
p
r
o
v
id
in
g
u
n
p
ar
alleled
p
r
ec
is
io
n
.
Alth
o
u
g
h
GPM
o
f
f
er
s
s
u
p
er
i
o
r
ac
c
u
r
ac
y
an
d
ac
h
ie
v
es
lo
wer
R
MSE
th
an
NN
-
L
M,
it
co
m
es
with
h
ig
h
er
co
m
p
u
tatio
n
al
co
s
t
d
u
e
to
its
p
r
o
b
ab
ilis
tic
f
r
am
ew
o
r
k
an
d
r
elian
ce
o
n
co
v
ar
ia
n
ce
f
u
n
ctio
n
s
.
T
h
is
m
ak
es
GPM
id
ea
l
f
o
r
ap
p
licat
io
n
s
wh
er
e
p
r
ec
is
io
n
o
u
tweig
h
s
ef
f
icien
cy
,
s
u
ch
as
cr
itical
b
atter
y
p
e
r
f
o
r
m
an
ce
s
im
u
latio
n
s
.
Ov
er
all,
GPM
s
e
ts
th
e
b
en
ch
m
ar
k
f
o
r
ac
cu
r
ac
y
,
p
ar
ticu
lar
ly
in
a
p
p
licatio
n
s
wh
er
e
p
r
ec
is
io
n
is
non
-
n
eg
o
tiab
le.
Yet,
its
h
ig
h
er
co
m
p
lex
ity
h
ig
h
lig
h
ts
th
e
im
p
o
r
tan
ce
o
f
b
alan
cin
g
ac
cu
r
ac
y
r
eq
u
ir
em
e
n
ts
with
co
m
p
u
tatio
n
al
r
eso
u
r
ce
s
.
3
.
4
.
Appl
ica
t
io
n o
f
t
he
t
herm
a
l mo
del t
o
ba
t
t
er
y
c
a
pa
cit
y
predict
io
n
B
atter
y
ca
p
ac
ity
,
a
f
u
n
d
am
e
n
tal
p
ar
am
eter
f
o
r
ass
ess
in
g
en
er
g
y
s
to
r
ag
e
s
y
s
tem
s
,
is
co
m
m
o
n
l
y
ca
lcu
lated
u
s
in
g
t
h
e
C
o
u
lo
m
b
co
u
n
tin
g
f
o
r
m
u
la.
T
h
is
m
eth
o
d
in
teg
r
ates
th
e
cu
r
r
en
t
d
r
aw
n
f
r
o
m
o
r
s
u
p
p
lie
d
to
th
e
b
atter
y
o
v
er
tim
e,
p
r
o
v
i
d
in
g
a
m
ea
s
u
r
e
o
f
t
h
e
av
ailab
l
e
ca
p
ac
ity
.
Ma
th
em
atica
lly
,
it
is
ex
p
r
ess
ed
as
(
7
)
.
=
∫
(
)
(
7
)
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
I
SS
N:
2088
-
8
6
9
4
A
d
va
n
ce
d
th
erma
l m
o
d
elin
g
o
f lith
iu
m
-
io
n
b
a
tter
ies:
fo
u
n
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a
tio
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fo
r
a
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va
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…
(
A
b
d
elh
a
d
i E
lka
ke
)
2707
W
h
er
e
I
(
t)
is
th
e
i
n
s
tan
tan
eo
u
s
cu
r
r
e
n
t.
Ho
wev
e
r
,
ca
p
ac
it
y
is
n
o
t
s
o
lely
a
f
u
n
ctio
n
o
f
th
e
c
u
r
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en
t;
it
is
in
f
lu
en
ce
d
b
y
s
ev
er
al
ex
ter
n
al
an
d
in
ter
n
al
f
ac
to
r
s
,
in
cl
u
d
in
g
am
b
ien
t
tem
p
er
at
u
r
e,
wh
ich
im
p
ac
ts
th
e
b
atter
y
'
s
elec
tr
o
ch
em
ical
ac
tiv
ity
an
d
en
e
r
g
y
s
to
r
a
g
e
ef
f
icien
cy
.
I
n
th
is
s
tu
d
y
,
th
e
C
o
u
lo
m
b
co
u
n
tin
g
f
o
r
m
u
la
was
ap
p
lied
to
co
m
p
u
te
th
e
b
atter
y
ca
p
ac
ity
at
v
ar
io
u
s
am
b
ien
t
tem
p
er
atu
r
es:
-
20
°C
,
-
10
°C
,
0
°C
,
1
0
°
C
,
a
n
d
2
5
°C
.
T
h
e
r
esu
lts
,
illu
s
tr
ated
in
Fig
u
r
e
8
,
d
em
o
n
s
tr
ate
a
clea
r
d
ep
en
d
e
n
cy
o
f
ca
p
ac
ity
o
n
tem
p
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atu
r
e.
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e
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atu
r
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e
ca
p
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ec
r
ea
s
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ican
tly
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e
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o
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ilit
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io
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th
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ter
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ely
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is
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ch
i
n
g
its
p
ea
k
at
2
5
°C
.
T
h
is
an
aly
s
is
u
n
d
er
s
co
r
es
th
e
s
tr
o
n
g
in
f
lu
en
ce
o
f
am
b
ie
n
t
tem
p
er
atu
r
e
o
n
b
atter
y
p
er
f
o
r
m
a
n
c
e,
h
ig
h
lig
h
tin
g
th
e
n
ee
d
f
o
r
ac
cu
r
ate
t
h
er
m
al
m
o
d
elin
g
to
p
r
e
d
ict
ca
p
ac
ity
u
n
d
er
d
iv
er
s
e
o
p
e
r
atin
g
co
n
d
itio
n
s
Fig
u
r
e
7
.
GPM
m
o
d
el
v
alid
ati
o
n
f
o
r
d
if
f
e
r
en
t te
m
p
e
r
atu
r
es
T
R
Fig
u
r
e
8
.
C
ap
ac
ity
in
f
u
n
ctio
n
o
f
tem
p
er
at
u
r
es
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
0
8
8
-
8
6
9
4
I
n
t J Po
w
E
lec
&
Dr
i Sy
s
t
,
Vo
l.
16
,
No
.
4
,
Dec
em
b
er
20
25
:
2699
-
2
7
1
0
2708
Fu
r
th
er
m
o
r
e
,
in
ter
io
r
tem
p
er
atu
r
e,
wh
ich
f
lu
ct
u
ates
d
y
n
a
m
ically
wh
en
in
u
s
e,
h
as
an
im
p
ac
t
o
n
b
atter
y
ca
p
ac
ity
in
ad
d
itio
n
to
ex
ter
n
al
tem
p
er
atu
r
e.
T
h
e
b
att
er
y
'
s
in
ter
n
al
tem
p
er
atu
r
e
f
lu
ct
u
ates a
s
a
r
esu
lt o
f
ch
em
ical
p
r
o
ce
s
s
es,
h
ea
t
p
r
o
d
u
ctio
n
d
u
r
i
n
g
cy
cles
o
f
ch
a
r
g
e
an
d
d
is
ch
ar
g
e,
an
d
r
esis
tan
ce
-
r
elate
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e
n
er
g
y
lo
s
s
es.
T
h
ese
v
ar
iab
les
f
u
r
th
er
af
f
ec
t
th
e
b
atter
y
'
s
ca
p
ac
ity
b
y
ch
an
g
i
n
g
th
e
elec
tr
o
ch
em
i
ca
l
k
in
etics
an
d
th
e
av
ailab
ilit
y
o
f
ac
tiv
e
m
ater
ial.
T
h
is
ar
ticle
'
s
th
er
m
al
m
o
d
el
o
f
f
er
s
th
e
f
r
am
ewo
r
k
r
eq
u
ir
e
d
to
in
clu
d
e
in
ter
n
al
tem
p
er
atu
r
e
in
ca
p
ac
ity
p
r
ed
ictio
n
m
o
d
els,
allo
win
g
f
o
r
a
th
o
r
o
u
g
h
ex
a
m
in
atio
n
o
f
b
atter
y
b
eh
a
v
io
r
in
p
r
ac
tical
s
ettin
g
s
,
in
th
e
f
u
tu
r
e
wo
r
k
ca
p
ac
ity
will
b
e
p
r
e
d
icted
u
s
in
g
c
u
r
r
en
t,
am
b
ien
t
tem
p
er
atu
r
e
a
n
d
b
atter
y
in
ter
n
al
tem
p
er
atu
r
e
th
at
is
o
b
tain
ed
with
th
e
th
e
r
m
al
m
o
d
el.
4.
CO
NCLU
SI
O
N
T
h
is
s
tu
d
y
ad
d
r
ess
es
im
p
o
r
ta
n
t
is
s
u
es
with
b
atter
y
m
an
ag
em
en
t
s
y
s
tem
s
b
y
in
tr
o
d
u
ci
n
g
a
n
o
v
el
th
er
m
al
m
o
d
elin
g
f
r
am
ewo
r
k
cr
ea
ted
esp
ec
ially
f
o
r
lith
iu
m
-
io
n
b
atter
ies.
T
h
e
s
u
g
g
ested
f
r
am
ewo
r
k
u
s
es
ad
v
an
ce
d
tech
n
iq
u
es,
in
clu
d
in
g
NN
-
L
M,
NN
-
B
R
,
an
d
GPM,
to
ac
cu
r
ately
f
o
r
ec
ast
in
ter
n
al
b
atter
y
tem
p
er
atu
r
e
w
h
ile
ac
co
u
n
tin
g
f
o
r
t
h
e
im
p
ac
ts
o
f
b
o
th
cu
r
r
e
n
t
an
d
a
m
b
ien
t
tem
p
er
atu
r
e
.
T
h
e
GPM
ac
h
iev
ed
an
o
u
ts
tan
d
in
g
R
MSE
o
f
0
.
0
3
4
%,
co
n
f
ir
m
in
g
its
p
o
s
itio
n
as
th
e
m
o
s
t
ac
c
u
r
ate
m
eth
o
d
.
E
x
ten
s
iv
e
v
alid
atio
n
ac
r
o
s
s
a
r
an
g
e
o
f
o
p
er
atio
n
al
co
n
d
itio
n
s
,
f
r
o
m
-
20
°C
to
2
5
°C
,
h
as
s
h
o
wn
th
e
s
tab
le
p
er
f
o
r
m
an
ce
o
f
th
ese
m
o
d
els.
On
th
e
o
th
er
h
a
n
d
,
NN
-
L
M
p
r
o
v
ed
to
b
e
a
c
o
m
p
u
tatio
n
ally
e
f
f
ec
tiv
e
s
u
b
s
titu
te,
m
ak
in
g
it
ap
p
r
o
p
r
iate
f
o
r
r
ea
l
-
tim
e
d
e
p
l
o
y
m
en
t.
A
co
m
p
r
eh
en
s
iv
e
u
n
d
er
s
tan
d
in
g
o
f
b
atter
y
b
e
h
av
io
r
is
f
o
s
ter
ed
b
y
th
e
co
m
b
in
atio
n
o
f
th
er
m
al
m
o
d
elin
g
a
n
d
e
f
f
icien
t
b
atte
r
y
m
an
a
g
em
en
t,
w
h
ich
im
p
r
o
v
es
s
af
ety
,
d
e
p
en
d
a
b
ilit
y
,
a
n
d
ef
f
icien
c
y
.
T
h
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
h
av
e
i
m
p
o
r
tan
t
im
p
licatio
n
s
f
o
r
f
u
tu
r
e
s
tu
d
ies
o
n
s
o
p
h
is
ticated
ca
p
ac
ity
p
r
e
d
ictio
n
m
o
d
els
th
at
in
co
r
p
o
r
ate
d
er
at
in
g
an
d
th
er
m
al
d
y
n
a
m
ics.
T
h
u
s
,
o
u
r
wo
r
k
h
as
th
e
p
o
ten
t
ial
to
s
ig
n
if
ican
tly
in
f
lu
en
ce
th
e
d
ev
el
o
p
m
en
t
o
f
n
ex
t
-
g
en
e
r
atio
n
b
atter
y
m
a
n
ag
em
en
t
s
y
s
tem
s
,
esp
ec
iall
y
in
cr
u
cial
f
ield
s
wh
er
e
ef
f
icien
t
co
n
tr
o
l
o
f
t
h
er
m
al
d
y
n
am
ics
an
d
ca
p
ac
ity
is
ess
en
tial,
s
u
ch
as
elec
tr
ic
v
e
h
i
cles
an
d
r
e
n
ewa
b
le
en
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y
s
to
r
a
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e.
F
UNDING
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h
is
r
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id
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p
ec
if
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y
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ip
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f
ac
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Ab
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wah
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Haja
jji
✓
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C
:
C
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e
p
t
u
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ec
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a
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f
u
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in
g
,
b
e
n
ef
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,
o
r
p
er
s
o
n
al
r
elatio
n
s
h
ip
s
th
at
co
u
ld
h
a
v
e
in
f
lu
e
n
ce
d
th
e
wo
r
k
r
ep
o
r
ted
in
t
h
is
p
ap
er
.
DATA AV
AI
L
AB
I
L
I
T
Y
T
h
e
d
ata
s
u
p
p
o
r
tin
g
t
h
e
f
in
d
in
g
s
o
f
th
is
s
tu
d
y
ar
e
av
ailab
le
f
r
o
m
h
tt
p
s
://d
ata.
m
en
d
eley
.
c
o
m
/d
atasets
/
wy
k
h
t8
y
7
tg
/1
.
Evaluation Warning : The document was created with Spire.PDF for Python.