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Appl
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14
,
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.
2
,
J
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e
20
25
,
p
p
.
291
~
2
9
9
I
SS
N:
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.
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.
pp
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-
299
291
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ttp
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//
ija
p
e.
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co
m/
State
-
a
ug
men
ted
a
da
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g
-
mo
de obs
erver fo
r estimatio
n
o
f
sta
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charg
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a
nd mea
surem
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lithium
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ies
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o
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s
a
n
d
Te
c
h
n
o
l
o
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y
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TU
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C
H
)
,
T
h
a
i
N
g
u
y
e
n
,
V
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t
n
a
m
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
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y:
R
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Ma
y
1
6
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2
0
2
3
R
ev
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2
6
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4
Acc
ep
ted
No
v
2
8
,
2
0
2
4
Esti
m
a
ti
n
g
t
h
e
sta
te
o
f
c
h
a
rg
e
(S
o
C)
in
li
t
h
i
u
m
-
io
n
b
a
tt
e
r
ies
(Li
B)
e
n
c
o
u
n
ters
c
h
a
ll
e
n
g
e
s
d
u
e
t
o
m
o
d
e
l
u
n
c
e
rtain
ti
e
s
a
n
d
se
n
so
r
m
e
a
su
re
m
e
n
t
e
rro
rs.
To
so
l
v
e
t
h
is
issu
e
,
th
is
stu
d
y
i
n
tro
d
u
c
e
s
a
n
e
stim
a
to
r
b
a
se
d
o
n
a
n
in
n
o
v
a
ti
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e
a
d
a
p
ti
v
e
a
u
g
m
e
n
ted
slid
in
g
m
o
d
e
a
p
p
r
o
a
c
h
.
Th
is
a
p
p
ro
a
c
h
in
c
o
rp
o
ra
tes
m
e
a
su
re
m
e
n
t
fa
u
lt
s a
s
a
d
d
it
i
o
n
a
l
sta
te
v
a
riab
les
t
o
m
i
n
imiz
e
th
e
imp
a
c
ts
o
f
u
n
c
e
rtain
ti
e
s
e
ffe
c
ti
v
e
ly
.
F
u
rt
h
e
rm
o
re
,
b
a
se
d
o
n
t
h
e
sli
d
in
g
m
o
d
e
fra
m
e
wo
rk
,
th
e
d
e
sig
n
o
f
t
h
is
e
stim
a
to
r
a
d
d
re
ss
e
s
re
sista
n
c
e
to
m
o
d
e
l
u
n
c
e
rtain
ti
e
s.
H
o
we
v
e
r,
slid
in
g
e
stim
a
to
rs
c
o
m
m
o
n
ly
fa
c
e
th
e
c
h
a
tt
e
rin
g
issu
e
.
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c
o
u
n
tera
c
t
th
is,
th
e
p
a
p
e
r
su
g
g
e
sts e
m
p
lo
y
in
g
a
d
a
p
ti
v
e
d
y
n
a
m
ics
to
d
e
term
in
e
th
e
e
stim
a
to
r'
s
g
a
in
.
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i
s
a
d
a
p
t
iv
e
a
p
p
ro
a
c
h
a
ll
o
w
s
th
e
g
a
in
c
a
lcu
latio
n
to
m
in
imiz
e
e
stim
a
ti
o
n
e
rro
rs
a
c
ro
ss
a
ll
ti
m
e
ste
p
s
,
e
ffe
c
ti
v
e
ly
re
d
u
c
in
g
c
h
a
tt
e
rin
g
a
n
d
e
n
h
a
n
c
in
g
e
stim
a
ti
o
n
a
c
c
u
ra
c
y
.
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e
p
e
rfo
rm
a
n
c
e
o
f
th
e
p
ro
p
o
se
d
m
e
th
o
d
is
v
a
li
d
a
te
d
th
r
o
u
g
h
sim
u
lat
io
n
s
u
sin
g
two
p
ra
c
ti
c
a
l
d
a
ta
se
ts.
Re
su
lt
s
d
e
m
o
n
stra
te
su
p
e
rio
r
a
c
c
u
ra
c
y
c
o
m
p
a
re
d
to
c
o
n
v
e
n
ti
o
n
a
l
slid
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g
m
e
th
o
d
s,
wi
th
im
p
ro
v
e
m
e
n
ts i
n
S
o
C
a
n
d
term
in
a
l
v
o
lt
a
g
e
e
stim
a
ti
o
n
.
K
ey
w
o
r
d
s
:
L
ith
iu
m
-
io
n
b
atter
ies
R
en
ewa
b
le
en
er
g
y
s
y
s
tem
s
Sli
d
in
g
m
o
d
e
o
b
s
er
v
er
State
esti
m
atio
n
State
o
f
ch
ar
g
e
T
h
is i
s
a
n
o
p
e
n
a
c
c
e
ss
a
rticle
u
n
d
e
r th
e
CC B
Y
-
SA
li
c
e
n
se
.
C
o
r
r
e
s
p
o
nd
ing
A
uth
o
r
:
C
h
i N
g
u
y
en
Van
Facu
lty
o
f
E
lectr
ical
an
d
E
lectr
o
n
ics E
n
g
in
ee
r
in
g
,
T
h
ai
Ng
u
y
en
Un
iv
er
s
ity
o
f
T
ec
h
n
o
lo
g
y
3
/2
r
o
a
d
,
T
h
ai
N
g
u
y
e
n
C
ity
,
T
h
ai
Ng
u
y
en
,
Vietn
am
E
m
ail:
n
g
ch
i@
tn
u
t.e
d
u
.
v
n
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
g
r
o
win
g
in
ter
est
in
r
e
n
e
wab
le
en
er
g
y
s
y
s
tem
s
h
as
le
d
to
a
s
u
r
g
e
in
r
esear
ch
a
r
o
u
n
d
e
n
er
g
y
s
to
r
ag
e
s
o
lu
tio
n
s
.
Am
o
n
g
th
e
s
e,
b
atter
ies
ar
e
c
r
u
cial
c
o
m
p
o
n
en
ts
th
at
ar
e
u
s
ed
in
alm
o
s
t
all
en
er
g
y
s
to
r
a
g
e
s
y
s
tem
s
.
T
h
e
em
er
g
en
ce
o
f
lith
iu
m
-
io
n
b
atter
ies
(
L
iB
)
h
as
r
ev
o
lu
tio
n
ized
en
er
g
y
s
to
r
a
g
e.
L
iB
s
o
f
f
er
s
ev
er
al
ad
v
an
tag
es,
in
clu
d
in
g
h
i
g
h
er
ch
ar
g
e
d
e
n
s
ity
,
co
m
p
ac
t
s
ize,
r
ed
u
ce
d
weig
h
t,
an
d
s
tab
le
o
u
tp
u
t
v
o
ltag
e
.
As
a
r
esu
lt,
th
eir
u
s
e
h
as
in
cr
ea
s
ed
in
v
ar
io
u
s
ap
p
licatio
n
s
,
in
clu
d
in
g
r
en
ewa
b
le
en
er
g
y
s
y
s
tem
s
(
R
E
S)
an
d
elec
tr
ic
v
eh
icles
(
E
Vs)
[
1
]
,
[
2
]
.
Ho
we
v
er
,
th
e
u
tili
za
tio
n
an
d
s
u
p
er
v
is
io
n
o
f
L
iB
s
p
r
esen
t
s
ig
n
if
ic
an
t
ch
allen
g
es,
th
e
p
r
im
ar
y
c
h
allen
g
es
in
clu
d
e
ac
cu
r
ately
esti
m
atin
g
p
a
r
am
eter
s
lik
e
s
tate
o
f
ch
ar
g
e
(
So
C
)
,
i
n
ter
n
al
r
esis
tan
ce
s
,
an
d
d
etec
tin
g
f
au
lts
d
u
r
i
n
g
cu
r
r
en
t a
n
d
te
r
m
in
al
v
o
ltag
e
m
ea
s
u
r
em
en
ts
[
3
]
-
[
5
]
.
R
esear
ch
er
s
h
av
e
p
r
o
p
o
s
ed
d
iv
er
s
e
m
eth
o
d
s
f
o
r
esti
m
atin
g
b
atter
y
p
ar
a
m
eter
s
an
d
d
etec
tin
g
m
ea
s
u
r
em
en
t
f
au
lts
,
ca
teg
o
r
iz
ed
as
s
ig
n
al
-
b
ased
,
m
o
d
el
-
b
a
s
ed
,
o
r
elec
tr
o
ch
em
ical
co
n
ce
p
ts
.
Am
o
n
g
th
ese,
m
o
d
el
-
b
ased
ap
p
r
o
ac
h
es
ar
e
wid
ely
ad
o
p
ted
f
o
r
th
eir
ef
f
e
ctiv
en
ess
in
b
o
th
p
ar
am
eter
e
s
tim
atio
n
an
d
f
au
lt
d
etec
tio
n
[
6
]
.
Ho
wev
er
,
t
h
e
s
u
cc
ess
f
u
l
im
p
lem
en
tatio
n
o
f
m
o
d
el
-
b
ased
m
et
h
o
d
s
h
in
g
e
s
o
n
s
elec
tin
g
an
ap
p
r
o
p
r
iate
m
o
d
el
f
o
r
L
iB
s
.
Var
io
u
s
m
o
d
elin
g
ap
p
r
o
ac
h
es
e
x
is
t,
with
elec
tr
ical
m
eth
o
d
s
b
ein
g
o
n
e
p
r
o
m
i
n
en
t
o
p
tio
n
.
I
n
th
is
ap
p
r
o
ac
h
,
a
ci
r
cu
it
m
o
d
el
is
f
o
r
m
u
lated
f
o
r
th
e
b
atter
y
,
f
r
o
m
wh
ich
a
s
tate
s
p
ac
e
m
o
d
el
is
d
er
iv
ed
.
Su
b
s
eq
u
en
tly
,
u
tili
zin
g
th
is
s
tate
s
p
ac
e
m
o
d
el,
r
es
ea
r
ch
er
s
d
ev
elo
p
tailo
r
ed
esti
m
ato
r
s
to
d
eter
m
in
e
Evaluation Warning : The document was created with Spire.PDF for Python.
I
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N
:
2
2
5
2
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8
7
9
2
I
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t J Ap
p
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E
n
g
,
Vo
l.
14
,
No
.
2
,
J
u
n
e
20
25
:
29
1
-
299
292
b
atter
y
p
a
r
am
eter
s
[
7
]
,
[
8
]
.
T
h
er
e
ar
e
v
ar
i
o
u
s
ty
p
es
o
f
esti
m
ato
r
s
,
with
Kalm
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f
ilter
s
c
o
n
s
titu
tin
g
th
e
f
ir
s
t
ca
teg
o
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T
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ilter
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o
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r
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atica
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ilter
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ile
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o
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am
ics
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alize
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Kalm
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ilter
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e
ex
ten
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e
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ilter
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u
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f
e
r
s
f
r
o
m
lin
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n
er
r
o
r
s
,
d
im
in
is
h
in
g
esti
m
atio
n
ac
cu
r
a
cy
.
T
o
m
itig
ate
th
is
,
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esear
ch
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s
tu
r
n
to
alter
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ativ
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lik
e
th
e
u
n
s
ce
n
ted
Kalm
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f
ilter
,
wh
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eq
u
ir
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m
o
r
e
co
m
p
u
tatio
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al
p
o
wer
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av
o
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s
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ea
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izatio
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Desp
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Kalm
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f
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p
ar
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to
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x
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d
ed
co
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ter
p
a
r
t.
E
s
tab
lis
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in
g
p
r
o
ce
s
s
an
d
m
ea
s
u
r
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e
n
t
n
o
is
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co
v
ar
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atr
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p
o
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a
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ig
n
if
ican
t
ch
allen
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e
in
Kalm
an
f
ilter
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esig
n
,
o
f
ten
ad
d
r
ess
ed
th
r
o
u
g
h
a
d
ap
tiv
e
ap
p
r
o
ac
h
es
[
9
]
,
[
1
0
]
.
R
esear
ch
er
s
em
p
lo
y
tech
n
iq
u
es
s
u
ch
as
f
u
zz
y
s
y
s
tem
s
o
r
n
eu
r
al
n
etwo
r
k
s
to
a
d
ap
tiv
ely
d
eter
m
in
e
co
v
ar
ian
ce
m
atr
ices,
en
h
a
n
cin
g
esti
m
atio
n
ac
cu
r
ac
y
.
No
n
et
h
eless
,
a
cr
u
cial
d
r
awb
ac
k
o
f
Kalm
an
f
ilter
s
lies
in
th
eir
d
ep
en
d
en
ce
o
n
ac
c
u
r
ate
b
atter
y
m
o
d
els.
E
r
r
o
r
s
in
m
o
d
el
id
e
n
tific
atio
n
e
n
g
en
d
er
u
n
ce
r
tain
ty
,
u
n
d
er
m
i
n
in
g
th
e
f
ilter
'
s
p
r
ec
is
i
o
n
[
1
1
]
-
[
1
3
]
.
T
o
ad
d
r
ess
m
o
d
el
u
n
ce
r
tain
tie
s
,
r
esear
ch
er
s
em
p
lo
y
r
o
b
u
s
t
esti
m
atio
n
tech
n
iq
u
es
f
o
r
esti
m
atin
g
th
e
b
atter
y
'
s
So
C
.
T
h
ese
m
eth
o
d
s
in
co
r
p
o
r
ate
a
r
an
g
e
o
f
u
n
ce
r
tain
ty
in
to
th
eir
m
o
d
els
an
d
a
d
ap
t
th
e
esti
m
ato
r
ac
co
r
d
in
g
l
y
[
1
4
]
.
Sli
d
in
g
esti
m
ato
r
s
ar
e
p
r
o
m
in
en
t
am
o
n
g
t
h
ese
r
o
b
u
s
t
tech
n
iq
u
es
[
1
5
]
.
Ho
wev
er
,
th
e
y
o
f
ten
en
co
u
n
ter
c
h
atter
in
g
is
s
u
es d
u
r
in
g
esti
m
atio
n
.
T
o
m
in
im
ize
th
is
,
s
o
m
e
r
esear
ch
er
s
em
p
lo
y
ad
ap
tiv
e
v
ar
iatio
n
s
th
at
ad
ju
s
t
b
atter
y
p
ar
am
eter
esti
m
atio
n
[
1
6
]
,
[
1
7
]
.
T
h
is
a
d
ap
tatio
n
ca
n
in
v
o
lv
e
m
ak
in
g
th
e
esti
m
ato
r
g
ai
n
ad
ap
tiv
e
th
r
o
u
g
h
tech
n
iq
u
es
lik
e
f
u
zz
y
s
y
s
tem
s
o
r
n
eu
r
al
n
etwo
r
k
s
[
1
8
]
,
[
1
9
]
,
o
r
b
y
in
tr
o
d
u
cin
g
s
p
ec
ialized
d
y
n
am
ics
to
m
in
im
ize
ch
att
er
in
g
.
An
o
th
er
r
o
b
u
s
t
esti
m
ato
r
,
th
e
H
-
i
n
f
in
ity
esti
m
at
o
r
,
tack
les
m
o
d
el
u
n
ce
r
tain
ty
b
y
ac
c
o
u
n
tin
g
f
o
r
it
in
its
d
esig
n
,
p
r
o
v
i
d
in
g
ac
cu
r
ate
esti
m
ates
ev
en
in
u
n
ce
r
tain
co
n
d
itio
n
s
.
No
n
eth
eless
,
th
ese
esti
m
ato
r
s
s
u
f
f
er
f
r
o
m
h
ea
v
y
co
m
p
u
tatio
n
al
r
eq
u
i
r
em
en
ts
an
d
co
m
p
lex
p
r
ac
tical
im
p
lem
en
tatio
n
s
[
2
0
]
,
[
2
1
]
.
I
n
r
ec
en
t
y
ea
r
s
,
alo
n
g
s
id
e
m
o
d
el
-
b
ased
ap
p
r
o
ac
h
es,
lear
n
in
g
-
b
ased
m
eth
o
d
s
h
a
v
e
g
ain
e
d
s
ig
n
if
ican
t
tr
ac
tio
n
f
o
r
esti
m
atin
g
b
atter
y
p
ar
am
ete
r
s
.
No
tab
ly
,
tech
n
iq
u
es
s
u
ch
as
m
ac
h
in
e
lear
n
i
n
g
,
d
ee
p
lear
n
i
n
g
,
an
d
r
ein
f
o
r
ce
m
e
n
t
lear
n
i
n
g
h
av
e
e
m
er
g
ed
as
p
r
o
m
i
n
en
t
ch
o
ices
in
th
is
d
o
m
ain
.
T
h
e
p
r
im
a
r
y
ad
v
an
tag
e
o
f
t
h
ese
m
eth
o
d
s
lies
in
th
eir
in
d
ep
en
d
en
ce
f
r
o
m
b
atter
y
m
o
d
elin
g
,
en
ab
lin
g
p
ar
am
eter
esti
m
atio
n
with
o
u
t
ex
p
licit
m
o
d
el
k
n
o
wled
g
e
.
Nev
e
r
th
e
less
,
a
m
ajo
r
c
h
allen
g
e
wi
th
th
ese
ap
p
r
o
ac
h
es
is
th
e
n
ec
ess
ity
f
o
r
a
co
m
p
r
eh
e
n
s
iv
e
an
d
d
ep
e
n
d
ab
l
e
d
ataset
f
o
r
lear
n
in
g
[
2
2
]
,
[
2
3
]
.
Ad
d
itio
n
ally
,
alter
n
ativ
e
m
eth
o
d
s
lik
e
s
ig
n
al
-
b
ased
ap
p
r
o
ac
h
es
u
tili
zin
g
u
ltra
s
o
n
ic
s
en
s
o
r
s
h
a
v
e
b
ee
n
p
r
o
p
o
s
ed
f
o
r
p
ar
am
eter
esti
m
atio
n
.
Ho
wev
e
r
,
th
es
e
m
eth
o
d
s
ar
e
h
in
d
er
ed
b
y
th
e
r
eq
u
ir
em
en
t
f
o
r
a
f
u
lly
e
q
u
ip
p
e
d
lab
o
r
ato
r
y
s
etu
p
.
Fu
r
th
er
m
o
r
e,
tech
n
i
q
u
es
s
u
ch
as
am
p
er
e
-
h
o
u
r
s
o
r
im
p
e
d
an
c
e
m
ea
s
u
r
em
en
ts
o
f
f
er
s
im
p
lici
ty
an
d
s
en
s
itiv
ity
to
lab
o
r
ato
r
y
co
n
d
itio
n
s
,
alb
eit
at
th
e
co
s
t o
f
lo
wer
ac
c
u
r
ac
y
[
2
4
]
.
Ad
d
r
ess
in
g
m
ea
s
u
r
em
en
t
f
a
u
lts
alo
n
g
s
id
e
b
atter
y
p
ar
am
et
er
esti
m
atio
n
is
cr
u
cial,
p
ar
ticu
lar
ly
in
h
ig
h
-
cu
r
r
en
t
a
p
p
licatio
n
s
.
C
u
r
r
en
tly
,
lim
ited
m
eth
o
d
s
ar
e
a
v
ailab
le
f
o
r
d
etec
tin
g
an
d
esti
m
atin
g
m
ea
s
u
r
em
en
t
er
r
o
r
s
in
b
atter
ies.
Fu
r
th
er
m
o
r
e,
th
e
u
n
ce
r
tain
ty
in
h
er
en
t
in
b
atter
y
m
o
d
els
ca
n
s
ig
n
if
ican
tl
y
im
p
ac
t
p
a
r
am
eter
esti
m
atio
n
ac
cu
r
ac
y
.
T
h
is
ar
ticle
p
r
o
p
o
s
es
an
e
x
ten
s
io
n
m
eth
o
d
f
o
r
s
lid
in
g
esti
m
ato
r
s
to
tack
le
th
ese
ch
allen
g
es.
T
h
is
ap
p
r
o
ac
h
t
r
ea
ts
m
ea
s
u
r
em
en
t
f
au
lts
as
an
ad
d
itio
n
al
s
tate
v
ar
iab
l
e,
esti
m
atin
g
th
em
alo
n
g
s
id
e
So
C
u
s
in
g
an
ad
ap
t
iv
e
s
lid
in
g
esti
m
ato
r
.
As
a
r
es
u
lt,
b
o
th
So
C
an
d
s
en
s
o
r
f
au
lt
s
ca
n
b
e
ac
cu
r
ately
an
d
ea
s
ily
esti
m
ated
.
T
h
e
esti
m
ato
r
em
p
l
o
y
s
a
s
p
ec
ially
d
es
ig
n
ed
d
y
n
am
ic
p
r
o
ce
s
s
to
a
d
a
p
tiv
ely
ex
tr
ac
t
f
ilter
g
ain
,
r
e
d
u
cin
g
ch
atter
in
g
d
u
r
in
g
esti
m
atio
n
.
T
h
e
r
em
ai
n
in
g
p
a
r
t
o
f
th
is
p
ap
er
is
s
tr
u
ctu
r
ed
as
f
o
llo
ws:
Sectio
n
2
m
en
tio
n
s
th
e
s
tate
s
p
ac
e
m
o
d
el
o
f
L
iB
.
Sectio
n
3
in
tr
o
d
u
ce
s
t
h
e
p
r
o
p
o
s
ed
s
tate
-
au
g
m
en
ted
ad
a
p
tiv
e
s
lid
in
g
-
m
o
d
e
o
b
s
er
v
er
f
o
r
esti
m
atio
n
o
f
s
o
c
an
d
m
ea
s
u
r
e
m
e
n
t
f
au
lt.
Sectio
n
4
s
h
o
ws
th
e
e
s
tim
atio
n
r
esu
lts
o
f
So
C
an
d
m
ea
s
u
r
em
en
t
f
au
lt u
s
in
g
p
r
ac
tical
d
ata.
Fin
ally
,
s
ec
tio
n
5
c
o
n
tain
s
s
o
m
e
co
n
clu
s
io
n
s
.
2.
ST
A
T
E
SP
ACE
M
O
DE
L
O
F
L
I
B
Sev
er
al
ap
p
r
o
ac
h
es
to
m
o
d
elin
g
L
iB
s
h
av
e
b
ee
n
p
r
o
p
o
s
ed
.
T
h
ese
in
clu
d
e
elec
tr
o
ch
em
ic
al
m
o
d
els,
eq
u
iv
alen
t
ci
r
cu
it
m
o
d
els,
a
n
d
e
x
p
er
im
en
tal
m
o
d
els.
A
m
o
n
g
th
ese,
th
e
eq
u
iv
alen
t
cir
cu
it
m
o
d
els
h
av
e
g
ar
n
er
e
d
s
ig
n
if
ican
t
atten
tio
n
f
r
o
m
en
g
in
ee
r
s
an
d
d
esig
n
er
s
d
u
e
to
th
eir
ab
ilit
y
to
s
tr
ik
e
a
b
alan
ce
b
etwe
en
p
r
ec
is
io
n
an
d
s
im
p
licity
,
m
ak
in
g
th
e
m
p
ar
tic
u
lar
ly
ap
p
ea
lin
g
f
o
r
d
esig
n
p
u
r
p
o
s
es.
T
o
d
escr
ib
e
m
o
r
e
ac
cu
r
ately
th
e
d
y
n
am
ics o
f
L
i
B
,
in
th
is
r
esear
ch
,
th
e
s
ec
o
n
d
o
r
d
er
o
f
L
iB
is
u
s
ed
[
2
5
]
,
[
2
6
]
.
As
d
ep
icted
in
Fig
u
r
e
1
,
t
h
is
p
ap
er
em
p
lo
y
s
a
s
ec
o
n
d
-
o
r
d
er
eq
u
iv
alen
t
cir
c
u
it
m
o
d
el
to
c
h
ar
ac
ter
ize
th
e
L
iB
.
T
h
e
cir
cu
it
m
o
d
el
e
n
co
m
p
ass
es
v
ar
io
u
s
co
m
p
o
n
e
n
ts
:
r
esis
to
r
0
r
ep
r
esen
tin
g
th
e
in
ter
n
al
r
esis
tan
ce
o
f
th
e
b
atter
y
,
two
r
esis
to
r
/cap
ac
ito
r
lo
o
p
s
1
,
1
,
an
d
2
,
2
to
em
u
lat
e
th
e
b
atter
y
'
s
tr
an
s
ien
t
b
eh
a
v
io
r
o
v
er
b
o
th
lo
n
g
a
n
d
s
h
o
r
t
ter
m
s
,
So
C
d
ep
en
d
en
t
v
o
ltag
e
s
o
u
r
ce
(
)
to
in
co
r
p
o
r
ate
t
h
e
n
o
n
lin
ea
r
r
elatio
n
s
h
ip
b
etwe
en
o
p
en
cir
cu
it
v
o
ltag
e
an
d
So
C
o
f
th
e
b
atter
y
,
r
esis
to
r
to
illu
s
tr
ate
s
e
lf
-
d
is
ch
ar
g
e,
an
d
ca
p
ac
ito
r
to
s
ig
n
if
y
th
e
to
tal
b
atter
y
ca
p
ac
ity
.
B
y
u
tili
zin
g
Kir
ch
h
o
f
f
'
s
laws,
th
e
ter
m
in
al
v
o
ltag
e
ca
n
b
e
ex
p
r
ess
ed
b
y
(
1
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
S
ta
te
-
a
u
g
men
ted
a
d
a
p
tive
s
lid
in
g
-
mo
d
e
o
b
s
erver fo
r
esti
ma
t
io
n
o
f sta
te
o
f c
h
a
r
g
e
…
(
Th
u
y
N
g
u
ye
n
V
in
h
)
293
=
(
)
−
1
−
2
−
0
(
1
)
I
n
wh
ich
,
is
th
e
So
C
o
f
L
iB
;
1
an
d
2
ar
e
th
e
v
o
ltag
es
ac
r
o
s
s
th
e
two
r
esis
to
r
/cap
ac
ito
r
lo
o
p
s
r
esp
ec
tiv
ely
.
T
h
e
d
y
n
am
ical
eq
u
atio
n
s
o
f
th
e
So
C
,
1
,
an
d
2
b
y
(
2
)
,
(
3
)
,
a
n
d
(
4
)
,
r
esp
ec
tiv
ely
.
=
−
−
(
2
)
1
=
−
1
1
1
+
1
(
3
)
2
=
−
2
2
2
+
2
(
4
)
B
y
co
n
s
id
er
in
g
=
0
an
d
u
s
in
g
(
1
)
an
d
(
2
)
,
th
e
d
y
n
am
ical
eq
u
atio
n
o
f
th
e
ter
m
in
al
v
o
ltag
e
is
f
o
r
m
u
late
d
as (
5
)
.
=
(
)
−
1
−
2
(
5
)
T
h
e
s
tate
v
ec
to
r
is
co
n
s
id
er
e
d
as
=
[
,
1
,
2
,
]
,
is
th
e
in
p
u
t
an
d
is
th
e
o
u
tp
u
t
o
f
t
h
e
b
atter
y
m
o
d
el.
T
h
e
s
tate
s
p
ac
e
m
o
d
el
o
f
th
e
b
atter
y
b
y
u
s
in
g
(
2
)
,
(
3
)
,
(
4
)
,
a
n
d
(
5
)
,
ca
n
b
e
w
r
itten
as (
6
)
.
{
=
(
,
)
+
=
+
,
,
=
[
0
0
0
1
]
(
6
)
T
h
e
ter
m
s
an
d
,
with
ze
r
o
m
ea
n
,
r
ep
r
esen
t
n
o
is
es
r
elate
d
to
p
r
o
ce
s
s
an
d
m
ea
s
u
r
em
e
n
t.
T
h
e
n
o
n
lin
ea
r
f
u
n
ctio
n
v
ec
to
r
(
,
)
ca
n
b
e
ex
p
r
es
s
ed
as (
7
)
.
(
,
)
=
[
−
−
−
1
1
1
+
1
−
2
2
2
+
2
(
)
+
1
1
1
+
2
2
2
−
(
1
+
2
1
2
)
]
(
7
)
T
h
e
(
7
)
d
escr
ib
es th
e
d
y
n
am
ic
s
o
f
L
iB
,
in
wh
ich
th
e
p
ar
am
eter
s
o
f
th
is
m
o
d
el
will b
e
id
en
ti
f
ied
f
r
o
m
ex
p
er
im
en
tal
d
ata
s
ets,
o
n
e
o
f
th
e
ef
f
ec
tiv
e
p
a
r
am
eter
id
en
tific
atio
n
m
eth
o
d
s
is
th
e
au
th
o
r
s
'
m
eth
o
d
in
th
e
d
o
cu
m
e
n
t
[
2
7
]
.
I
n
o
r
d
er
to
co
n
f
ir
m
th
e
ac
cu
r
ac
y
o
f
a
b
atter
y
m
o
d
el,
it
is
cr
u
cial
to
s
im
u
l
ate
it
in
a
s
o
f
twar
e
en
v
ir
o
n
m
en
t
an
d
co
m
p
ar
e
th
e
ter
m
in
al
v
o
ltag
e
with
th
e
v
o
ltag
e
m
ea
s
u
r
ed
d
u
r
in
g
p
r
a
ctica
l
test
s
.
I
f
th
e
s
im
u
lated
v
o
ltag
e
clo
s
ely
m
atch
es
th
e
m
ea
s
u
r
ed
v
o
ltag
e
with
in
a
p
r
ed
ef
in
ed
th
r
esh
o
ld
,
it
co
n
f
ir
m
s
th
e
s
u
cc
ess
f
u
l id
en
tific
atio
n
o
f
th
e
b
atter
y
.
Fig
u
r
e
1
.
T
h
e
s
ec
o
n
d
-
o
r
d
er
eq
u
iv
alen
t c
ir
cu
it m
o
d
el
o
f
L
iB
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
14
,
No
.
2
,
J
u
n
e
20
25
:
29
1
-
299
294
3.
ST
A
T
E
-
AUG
M
E
NT
E
D
AD
AP
T
I
V
E
SL
I
DING
-
M
O
DE
O
B
SE
RV
E
R
F
O
R
E
ST
I
M
AT
I
O
N
O
F
SO
C
AND
M
E
AS
URE
M
E
N
T
F
AUL
T
T
o
ac
cu
r
ately
esti
m
ate
th
e
s
ta
te
v
ar
iab
les,
s
u
ch
as
So
C
an
d
m
ea
s
u
r
em
en
t
s
en
s
o
r
f
au
lt,
it'
s
n
ec
ess
ar
y
to
r
ewr
ite
th
e
cu
r
r
en
t v
a
r
iab
les v
ec
to
r
as (
8
)
an
d
(
9
)
.
=
[
,
1
,
2
,
,
]
(
8
)
(
,
)
=
[
−
−
−
1
1
1
+
1
−
2
2
2
+
2
(
)
+
1
1
1
+
2
2
2
−
(
1
+
2
1
2
)
0
]
(
9
)
W
e
will
p
r
o
ce
ed
with
d
e
v
elo
p
in
g
th
e
o
b
s
er
v
e
r
b
y
in
tr
o
d
u
cin
g
th
e
s
p
atial
m
o
d
el
f
o
r
th
e
n
ewly
d
e
v
elo
p
ed
s
tate.
T
h
e
s
tate
d
y
n
am
ics
o
f
th
e
ad
ap
tiv
e
s
lid
in
g
m
o
d
e
esti
m
ato
r
ca
n
b
e
ex
p
r
ess
ed
in
(
1
0
)
.
{
̂
=
̂
+
+
Γ
(
)
+
̂
=
̂
(
1
0
)
I
n
(
1
0
)
,
t
h
e
p
o
l
e
-
p
l
a
c
e
m
e
n
t
m
e
t
h
o
d
i
s
u
s
e
d
t
o
d
e
t
e
r
m
i
n
e
t
h
e
f
u
n
c
t
i
o
n
v
e
c
t
o
r
Γ
,
w
h
i
l
e
v
e
c
t
o
r
r
e
p
r
e
s
e
n
t
s
t
h
e
s
w
it
c
h
i
n
g
g
a
i
n
s
o
f
t
h
e
o
b
s
e
r
v
er
,
w
h
i
c
h
is
d
e
r
i
v
e
d
t
h
r
o
u
g
h
s
p
e
c
i
f
i
c
d
y
n
a
m
ic
s
,
=
−
̂
is
t
h
e
S
o
C
es
t
i
m
at
i
o
n
e
r
r
o
r
,
=
[
1
0
0
0
0
]
.
T
h
e
d
y
n
a
m
i
c
s
o
f
t
h
e
e
s
ti
m
a
t
i
o
n
e
r
r
o
r
v
e
c
t
o
r
=
−
̂
i
s
c
a
l
c
u
l
at
e
d
a
s
(
1
1
)
.
=
̃
+
(
)
−
,
̃
=
(
−
Γ
)
(
1
1
)
Acc
o
r
d
in
g
t
o
th
e
L
y
ap
u
n
o
v
s
t
ab
ilit
y
th
eo
r
y
,
m
atr
ix
̃
m
u
s
t b
e
s
atis
f
ied
(
1
2
)
.
̃
+
(
̃
)
=
−
,
=
(
1
2
)
W
h
er
e
is
an
y
g
iv
en
p
o
s
itiv
e
d
ef
in
ite
s
y
m
m
etr
ic
m
atr
ix
an
d
is
u
n
iq
u
e
s
o
lu
tio
n
o
f
th
e
L
y
a
p
u
n
o
v
eq
u
atio
n
(
1
2
)
.
I
n
o
r
d
e
r
to
en
s
u
r
e
o
b
s
e
r
v
er
s
tab
ilit
y
,
a
L
y
ap
u
n
o
v
f
u
n
ctio
n
b
ased
o
n
th
e
e
r
r
o
r
is
n
ec
ess
ar
y
,
it
ca
n
b
e
f
o
r
m
u
lated
as (
1
3
)
.
(
)
=
1
2
(
+
(
)
2
)
(
1
3
)
W
e
u
s
e
to
d
e
n
o
te
a
n
ass
u
m
p
tio
n
f
o
r
t
h
e
g
ai
n
o
f
th
e
p
r
o
p
o
s
ed
o
b
s
er
v
er
,
wh
ich
is
r
ep
r
esen
ted
b
y
=
̂
−
,
is
a
co
n
s
tan
t
.
I
n
o
r
d
er
to
p
r
o
o
f
s
tab
ilit
y
o
f
esti
m
atio
n
er
r
o
r
s
,
it
is
e
s
s
en
tial
th
at
th
e
r
ate
o
f
ch
an
g
e
o
f
th
e
L
y
ap
u
n
o
v
f
u
n
cti
o
n
is
n
eg
ativ
e.
T
o
ac
h
ie
v
e
th
is
,
we
d
er
iv
e
th
e
L
y
ap
u
n
o
v
f
u
n
c
tio
n
as (
1
4
)
.
(
)
=
1
2
(
(
)
+
)
+
−
2
=
1
2
(
(
̃
+
(
̃
)
)
)
+
1
2
(
(
−
(
)
)
+
(
−
)
)
+
−
2
=
−
1
2
+
−
(
)
+
−
2
(
1
4
)
I
f
we
s
elec
t
as
2
|
|
,
an
d
th
e
is
ch
o
s
en
as
|
|
,
th
en
we
h
av
e
(
1
5
)
.
(
)
=
−
1
2
+
−
̂
|
|
=
−
1
2
+
(
−
|
|
)
(
1
5
)
If
is
p
o
s
itiv
ely
s
y
m
m
etr
ic,
−
1
2
will
b
e
n
eg
ativ
e.
Mo
r
eo
v
er
,
|
|
≤
i
s
les
s
th
an
ze
r
o
,
an
d
>
is
alwa
y
s
p
o
s
itiv
e,
en
s
u
r
in
g
(
−
|
|
)
is
n
eg
ativ
e.
C
o
n
s
eq
u
e
n
tly
,
t
h
e
ad
ap
tiv
e
o
b
s
er
v
e
r
g
ai
n
is
d
eter
m
in
ed
th
r
o
u
g
h
d
y
n
am
i
cs,
wh
ile
,
d
ir
ec
tly
in
f
l
u
en
cin
g
co
n
v
er
g
en
ce
tim
e,
is
co
m
p
u
ted
v
ia
t
h
e
o
p
tim
izatio
n
m
eth
o
d
s
.
is
o
b
tain
ed
u
s
in
g
(
1
6
)
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
S
ta
te
-
a
u
g
men
ted
a
d
a
p
tive
s
lid
in
g
-
mo
d
e
o
b
s
erver fo
r
esti
ma
t
io
n
o
f sta
te
o
f c
h
a
r
g
e
…
(
Th
u
y
N
g
u
ye
n
V
in
h
)
295
̂
=
|
|
=
̃
+
(
)
−
(
1
6
)
So
,
th
e
ad
ap
tiv
e
o
b
s
er
v
e
r
g
ain
is
ca
lcu
lated
b
y
(
1
7
)
.
=
{
̂
(
)
(
)
,
≠
0
0
,
=
0
(
1
7
)
4.
E
ST
I
M
AT
I
O
N
RE
S
UL
T
S
O
F
S
O
C
AN
D
M
E
A
SU
RE
M
E
N
T
F
A
UL
T
U
SI
N
G
P
R
A
CT
I
C
AL
DAT
A
I
n
o
r
d
er
to
d
eter
m
i
n
e
h
o
w
well
th
e
s
u
p
p
le
m
en
tar
y
esti
m
atio
n
tech
n
iq
u
e
wo
r
k
s
wh
e
n
ev
alu
atin
g
lith
iu
m
b
atter
y
f
au
lts
a
n
d
c
h
ar
g
e
lev
els,
a
n
im
p
lem
en
tati
o
n
s
y
s
tem
was
u
s
ed
.
T
h
is
s
y
s
tem
co
n
f
ig
u
r
atio
n
,
s
h
o
wn
in
Fig
u
r
e
2
,
i
n
v
o
lv
es
d
is
ch
ar
g
in
g
th
e
lith
iu
m
b
att
er
y
in
a
d
v
an
ce
with
a
p
r
o
g
r
am
m
ab
le
lo
ad
.
T
h
e
v
o
ltag
e
an
d
cu
r
r
en
t m
ea
s
u
r
em
en
ts
ar
e
th
en
u
tili
ze
d
f
o
r
s
im
u
l
atio
n
s
to
esti
m
ate
b
o
th
th
e
So
C
an
d
f
au
lts
.
Fig
u
r
e
2
.
T
h
e
co
n
f
ig
u
r
atio
n
o
f
th
e
im
p
lem
en
tatio
n
s
y
s
tem
f
o
r
p
ar
am
eter
s
id
e
n
tific
atio
n
So
C
an
d
m
ea
s
u
r
em
en
t f
au
lt e
s
tim
atio
n
Af
ter
co
n
d
u
ctin
g
a
s
et
o
f
ex
p
er
im
en
ts
,
th
e
d
y
n
am
ic
eq
u
atio
n
s
f
o
r
th
e
b
atter
y
m
o
d
el
ar
e
d
er
iv
ed
,
an
d
th
e
p
ar
am
eter
s
in
t
h
e
b
atter
y
s
tate
s
p
ac
e
m
o
d
el
ar
e
d
et
er
m
in
ed
.
I
n
th
is
s
tu
d
y
,
we
u
s
e
th
e
b
atter
y
ty
p
e
UL
1
8
6
5
0
,
4
.
2
V,
3
4
0
0
m
Ah
,
u
s
in
g
th
e
id
en
tific
atio
n
m
eth
o
d
o
f
th
e
au
th
o
r
s
in
[
2
7
]
,
th
e
p
ar
am
eter
s
(
7
)
ar
e
d
eter
m
in
ed
as (
1
8
)
.
=
1
.
0714
×
10
3
(
)
;
=
666
.
667
(
)
;
1
=
454
.
5455
(
)
;
1
=
20
(
)
2
=
0
.
75
(
)
;
2
=
133
(
)
(
)
≈
−
0
.
3
×
10
−
4
3
+
0
.
3
×
10
−
4
(
1
−
)
2
+
0
.
31
×
10
−
4
−
0
.
01
(
+
1
)
−
39
(
1
8
)
T
o
ev
alu
ate
t
h
e
ef
f
ec
tiv
e
n
ess
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
,
we
v
alid
ate
th
e
s
im
u
latio
n
s
u
s
in
g
two
s
ets
o
f
r
ea
l
-
wo
r
ld
d
ata.
T
h
ese
d
atasets
in
v
o
lv
e
alter
in
g
t
h
e
f
r
e
q
u
en
c
y
o
f
ter
m
in
al
cu
r
r
e
n
t
d
u
r
in
g
d
is
ch
a
r
g
e
to
e
v
alu
ate
th
e
ef
f
icac
y
o
f
th
e
esti
m
atio
n
m
eth
o
d
.
Fig
u
r
es
3
to
7
s
h
o
w
p
er
f
o
r
m
an
ce
r
esu
lts
f
o
r
th
e
f
ir
s
t
d
ata
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et,
wh
ile
Fig
u
r
es 8
to
1
1
s
h
o
w
r
esu
lts
f
o
r
th
e
s
ec
o
n
d
d
ata
s
et.
Fig
u
r
e
3
.
So
C
esti
m
atio
n
f
o
r
f
i
r
s
t d
ata
s
et
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
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8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
14
,
No
.
2
,
J
u
n
e
20
25
:
29
1
-
299
296
Fig
u
r
e
4
.
So
C
esti
m
atio
n
er
r
o
r
f
o
r
th
e
f
ir
s
t d
ata
s
et
Fig
u
r
e
5
.
T
e
r
m
in
al
v
o
ltag
e
esti
m
atio
n
f
o
r
th
e
f
ir
s
t
d
ata
s
et
F
i
g
u
r
e
6
.
V
o
l
t
a
g
e
e
s
ti
m
a
ti
o
n
e
r
r
o
r
f
o
r
t
h
e
f
i
r
s
t
d
a
t
a
s
e
t
Fig
u
r
e
7
.
Fau
lt e
s
tim
atio
n
f
o
r
t
h
e
f
ir
s
t d
ata
s
et
Fig
u
r
e
3
c
o
m
p
ar
es
th
e
p
er
f
o
r
m
an
ce
o
f
th
e
p
r
o
p
o
s
ed
m
eth
o
d
f
o
r
esti
m
atin
g
So
C
at
a
lo
we
r
f
r
eq
u
en
cy
with
th
at
o
f
a
co
n
v
en
tio
n
al
s
lid
in
g
m
o
d
e
ap
p
r
o
ac
h
.
T
h
e
a
d
a
p
tiv
e
s
lid
in
g
m
o
d
e
m
eth
o
d
ex
p
lain
ed
in
th
is
s
tu
d
y
s
h
o
ws
a
2
.
9
5
%
lo
wer
esti
m
atio
n
er
r
o
r
th
an
th
e
c
o
n
v
e
n
tio
n
al
m
eth
o
d
as
p
lo
tted
in
Fig
u
r
e
4
.
Mo
r
eo
v
er
,
th
e
p
r
o
p
o
s
ed
m
eth
o
d
p
r
esen
ts
m
in
im
al
ch
atter
in
g
wh
ile
th
e
co
n
v
en
tio
n
al
ap
p
r
o
ac
h
d
is
p
lay
s
s
o
m
e
ch
atter
in
g
in
its
p
er
f
o
r
m
an
ce
.
T
h
e
d
if
f
er
e
n
ce
b
etwe
en
th
e
two
m
eth
o
d
s
ca
n
b
e
attr
ib
u
ted
to
th
e
a
d
ap
tiv
e
ca
lcu
latio
n
o
f
th
e
esti
m
ato
r
's
g
ain
an
d
th
e
u
s
e
o
f
a
g
e
n
etic
alg
o
r
ith
m
to
en
h
an
ce
p
er
f
o
r
m
an
ce
in
th
e
p
r
o
p
o
s
ed
m
eth
o
d
.
T
h
e
u
n
iq
u
e
d
y
n
am
ics
em
p
lo
y
ed
f
o
r
ad
ap
tiv
el
y
ca
lcu
latin
g
th
e
esti
m
ato
r
'
s
g
ain
ar
e
d
esig
n
e
d
b
a
s
ed
o
n
m
in
im
izin
g
esti
m
atio
n
er
r
o
r
s
.
Fig
u
r
e
5
co
m
p
ar
es
th
e
p
r
o
p
o
s
ed
m
eth
o
d
'
s
p
er
f
o
r
m
an
ce
in
ter
m
in
al
v
o
ltag
e
esti
m
atio
n
with
th
at
o
f
th
e
co
n
v
en
tio
n
al
s
lid
in
g
m
et
h
o
d
.
Fig
u
r
e
6
s
h
o
ws
th
at
th
i
s
co
m
p
ar
is
o
n
r
ev
ea
ls
th
at
th
e
p
r
o
p
o
s
ed
m
eth
o
d
ac
h
iev
es
a
2
(
V)
lo
wer
v
o
lt
ag
e
esti
m
atio
n
er
r
o
r
th
an
th
e
co
n
v
e
n
tio
n
al
m
eth
o
d
.
H
o
wev
er
,
th
e
c
h
atter
in
g
p
h
en
o
m
en
o
n
p
e
r
s
is
ts
in
th
e
t
er
m
in
al
v
o
ltag
e
esti
m
atio
n
f
u
n
ctio
n
u
s
in
g
th
e
p
r
o
p
o
s
ed
m
e
th
o
d
.
Ad
d
itio
n
ally
,
th
e
p
r
o
p
o
s
ed
m
eth
o
d
co
n
s
id
e
r
s
m
ea
s
u
r
em
en
t
s
en
s
o
r
f
au
lts
as
an
ad
d
itio
n
al
s
tate
v
ar
iab
le
in
th
e
esti
m
ato
r
'
s
d
y
n
am
ics,
en
a
b
lin
g
it
to
esti
m
ate
f
au
lts
ac
cu
r
ately
.
Fig
u
r
e
7
illu
s
tr
ates
th
e
esti
m
atio
n
o
f
s
en
s
o
r
f
au
lts
.
T
h
e
co
n
v
en
tio
n
al
s
lid
in
g
m
eth
o
d
c
an
n
o
t
esti
m
ate
s
en
s
o
r
f
au
lts
,
wh
ich
ca
n
n
eg
ativ
ely
im
p
ac
t
th
e
ac
cu
r
ac
y
o
f
s
tate
v
ar
iab
le
esti
m
atio
n
.
T
h
is
lim
itatio
n
is
d
em
o
n
s
tr
ated
i
n
Fig
u
r
es
8
-
1
1
,
w
h
er
e
th
e
ab
s
en
ce
o
f
s
en
s
o
r
f
au
lt
esti
m
atio
n
in
th
e
co
n
v
en
tio
n
al
s
lid
in
g
m
eth
o
d
is
ev
id
en
t.
Fig
u
r
e
8
.
So
C
esti
m
atio
n
an
d
So
C
esti
m
atio
n
er
r
o
r
f
o
r
s
ec
o
n
d
d
ata
s
et
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t J Ap
p
l Po
wer
E
n
g
I
SS
N:
2252
-
8
7
9
2
S
ta
te
-
a
u
g
men
ted
a
d
a
p
tive
s
lid
in
g
-
mo
d
e
o
b
s
erver fo
r
esti
ma
t
io
n
o
f sta
te
o
f c
h
a
r
g
e
…
(
Th
u
y
N
g
u
ye
n
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in
h
)
297
Fig
u
r
e
9
.
Vo
ltag
e
esti
m
atio
n
e
r
r
o
r
f
o
r
s
ec
o
n
d
d
ata
s
et
Fig
u
r
e
1
0
.
T
er
m
in
al
v
o
ltag
e
e
s
tim
atio
n
f
o
r
s
ec
o
n
d
d
ata
s
et
Fig
u
r
e
1
1
.
Fau
lt e
s
tim
atio
n
f
o
r
s
ec
o
n
d
d
ata
s
et
5.
CO
NCLU
SI
O
N
T
h
is
p
ap
er
p
r
o
p
o
s
ed
an
a
u
g
m
en
ted
a
d
ap
tiv
e
s
lid
in
g
m
o
d
e
m
eth
o
d
to
ad
d
r
ess
m
o
d
el
u
n
ce
r
tain
ties
an
d
m
ea
s
u
r
em
e
n
t
s
en
s
o
r
er
r
o
r
s
.
T
h
e
m
et
h
o
d
tr
ea
ts
m
ea
s
u
r
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en
t
er
r
o
r
s
as
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cr
e
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en
t
al
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o
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e
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f
ec
tiv
ely
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m
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atin
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o
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n
ce
r
tain
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.
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h
e
in
h
er
en
t
ch
atter
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g
p
r
o
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lem
ass
o
ciate
d
with
s
lid
in
g
esti
m
ato
r
s
is
m
itig
ated
b
y
ad
ap
tiv
ely
d
esig
n
in
g
th
e
esti
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ato
r
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ain
.
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r
ap
p
r
o
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ce
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th
e
ch
atter
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g
ef
f
ec
t
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y
lev
er
ag
i
n
g
esti
m
atio
n
er
r
o
r
an
d
d
y
n
a
m
ically
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esig
n
ed
d
y
n
a
m
ics.
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h
is
m
eth
o
d
m
in
im
izes
esti
m
atio
n
er
r
o
r
ac
r
o
s
s
all
tim
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tep
s
b
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o
p
tim
izin
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t
h
e
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ain
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lc
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n
to
elim
in
ate
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h
atter
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in
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o
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esti
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atio
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an
d
en
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u
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.
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h
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o
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im
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with
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tical
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at
a
in
two
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ct
p
h
ases
,
o
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r
p
r
o
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o
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eth
o
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em
o
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ates
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u
p
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m
p
ar
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to
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e
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n
v
en
t
io
n
al
s
lid
in
g
m
et
h
o
d
,
ac
h
iev
in
g
a
b
etter
So
C
esti
m
atio
n
p
er
ce
n
tag
e.
ACK
NO
WL
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DG
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h
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r
esear
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p
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ted
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y
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h
ai
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u
y
en
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i
v
er
s
ity
o
f
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ec
h
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T
NUT
,
Vietn
am
.
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UNDING
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NF
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R
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T
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O
N
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h
is
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esear
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o
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e
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ic
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an
t
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r
o
m
an
y
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u
n
d
in
g
a
g
en
cy
in
th
e
p
u
b
lic,
co
m
m
er
ci
al,
o
r
n
o
t
-
f
o
r
-
p
r
o
f
it secto
r
s
.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SS
N
:
2
2
5
2
-
8
7
9
2
I
n
t J Ap
p
l Po
wer
E
n
g
,
Vo
l.
14
,
No
.
2
,
J
u
n
e
20
25
:
29
1
-
299
298
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
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M
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N
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h
is
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u
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C
o
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u
to
r
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o
les
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a
x
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o
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y
(
C
R
ed
iT)
to
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n
ize
in
d
iv
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d
u
al
au
th
o
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co
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u
tio
n
s
,
r
ed
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ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
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ate
co
llab
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n
.
Na
m
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o
f
Aut
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M
So
Va
Fo
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Vi
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h
i N
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C
:
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:
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f
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Au
th
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s
tate
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co
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in
t
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est.
DATA AV
AI
L
AB
I
L
I
T
Y
T
h
e
d
ata
th
at
s
u
p
p
o
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av
ailab
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f
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th
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esp
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in
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au
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r
[
C
NV]
,
u
p
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n
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ea
s
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ab
le
r
eq
u
est.
RE
F
E
R
E
NC
E
S
[
1
]
X
.
H
u
,
C
.
Z
o
u
,
C
.
Z
h
a
n
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.
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c
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s
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:
v
y
lh
h
2
0
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4
@
g
m
a
il
.
c
o
m
.
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