In
te
r
n
ation
a
l Jou
rn
al
o
f Po
we
r
Elec
tron
ic
s an
d
D
r
ive S
y
stem
(IJ
PED
S
)
V
o
l.
11, N
o.
1, Mar
ch 20
20,
p
p.
333~
3
4
1
IS
S
N
: 2088-
86
94,
D
O
I
:
10.11
59
1
/ij
ped
s
.
v11
.
i
1.pp
3
33-
34
1
333
Jou
rn
a
l
h
o
me
pa
ge
:
ht
tp:
//i
j
p
eds.i
a
esco
re
.com
Accu
rate b
attery mod
el pa
r
ameter
identification using heuristic
optimization
M
o
hd A
f
ifi
J
u
so
h,
M
u
h
a
m
ad
Z
a
l
a
n
i D
a
ud
F
a
c
u
lt
y of Ocean
En
g
i
n
eerin
g Tech
n
o
l
o
g
y
an
d
In
f
orm
a
ti
cs, Uni
v
e
r
siti
Malays
i
a
T
erengganu,
Malaysia
Art
i
cl
e In
fo
ABSTRACT
A
r
tic
le hist
o
r
y
:
Re
ce
i
v
e
d
Ju
l
1
7,
201
9
Re
vise
d S
e
p 27,
201
9
Ac
ce
p
t
ed
No
v
2
9
,
2
019
Th
is
p
aper
p
rese
nt
s
an
accur
a
te
L
ithiu
m
-io
n
b
attery
m
odel
repre
sentation
in
M
a
tl
ab
/Si
m
u
lin
k
.
T
he
T
rem
b
l
a
y's
bat
t
ery
m
odel
w
a
s
u
s
ed
a
s
a
BES
m
ode
l
pl
atf
o
rm
,
wh
ere
th
e
det
e
rmi
n
atio
n
o
f
t
h
e
m
od
el
p
ara
m
et
ers
w
a
s
o
bt
ained
bas
e
d
on
h
eu
ristic
o
ptim
izatio
n
app
r
oach
.
Th
is
a
p
p
ro
ach
i
s
simp
le
b
ut
m
o
r
e
accur
a
t
e
c
o
m
p
a
red
to
t
he
c
on
ven
tio
na
l
met
h
o
d
.
In
t
h
e
c
lass
ical
m
e
t
hod,
it
r
e
q
u
i
r
e
s
t
h
e
u
s
e
r
t
o
m
a
n
u
a
l
l
y
s
e
l
e
c
t
t
h
e
b
a
t
t
e
r
y
m
o
d
e
l
p
a
r
a
m
e
t
e
rs
from
relev
a
nt
p
oi
nts
on
t
h
e
m
anuf
acturer
d
i
s
ch
arge
c
urv
e
s.
H
owev
er,
t
h
i
s
w
a
y
o
f
b
a
tte
r
y
pa
ra
me
t
e
rs
e
xtra
c
t
io
n
n
o
rma
lly
e
xp
ose
d
t
o
th
e
h
u
ma
n
e
r
r
or
a
nd
wo
ul
d
eas
il
y
res
u
l
t
i
n
an
i
n
accurat
e
s
el
ecti
on
o
f
b
at
tery
p
aram
eters
f
o
r
th
e
BES
s
i
mu
la
t
i
o
n
s
tu
di
es
.
Th
erefo
r
e,
a
n
e
a
s
y
a
n
d
accu
rate
a
ppr
o
a
c
h
usi
n
g
heu
r
is
tic
o
p
tim
i
zat
io
n
f
o
r
det
e
rm
inin
g
battery
m
o
d
el
p
aram
et
ers
w
a
s
introduced.
The
simulat
i
on
s
t
udi
es
u
tilized
t
h
r
ee
di
f
f
erent
o
p
t
imizati
o
n
a
l
go
rith
m
s
f
or
c
o
m
pa
riso
n
p
u
r
p
ose
s
,
i.
e
.
1
)
P
a
rtic
le
S
wa
rm
O
pt
i
mization
(P
S
O
),
2
)
G
r
avi
t
ati
o
n
a
l
S
earch
A
l
g
o
r
it
h
m
(
GSA),
an
d
3
)
G
enet
ic
Al
gori
t
h
m
(GA
)
.
T
h
e
p
e
rf
o
r
m
a
nce
of
B
E
S
m
od
el
d
i
s
charg
e
accura
cy
w
i
t
h
res
p
ect
t
o
th
e
tes
t
d
a
t
a
f
r
o
m
t
hree
di
ff
erent
al
go
rit
h
ms
w
as
c
o
m
p
a
red
an
d
th
e
resul
t
s
sh
ow
ed
t
hat
the
GA
a
p
p
ro
ach
g
iv
es
t
h
e
b
est
res
u
lts
i
n
terms
o
f
accura
cy
a
nd
executi
on
time.
F
inally,
the
val
i
d
a
te
d
r
e
su
lt
s
o
f
G
A
-
op
ti
miz
e
d
batt
ery
m
odel
sh
ow
ed t
he
accu
racy
of
98%
comp
a
red t
o
t
he conv
ent
i
on
al
a
ppro
a
c
h.
K
eyw
ord
s
:
Ba
tt
e
r
y pa
ram
e
te
r
Energy
s
tor
a
ge
He
u
r
i
s
ti
c
op
timi
z
a
t
i
o
n
Li
t
h
i
u
m
-
io
n ba
tter
y
Th
is
is a
n
o
p
en acces
s a
r
ti
cle u
n
d
e
r t
h
e
CC
B
Y
-S
A
li
cens
e
.
Corres
pon
d
i
n
g
Au
th
or:
Mu
ham
a
d Za
l
a
ni D
au
d,
F
a
cult
y
o
f
O
cea
n En
gi
nee
r
i
n
g
Tec
hnol
o
gy a
nd Inf
o
rma
t
i
c
s,
Uni
v
ersi
ti
M
al
ays
i
a Te
reng
ga
nu,
Me
nga
ba
n
g
T
e
l
i
p
ot
,
21
0
30 K
u
a
l
a N
e
rus,
T
er
eng
g
an
u Ma
l
a
ysia
.
Em
ail:
zala
n
i
@
um
t.ed
u.
my
1.
I
N
TR
OD
U
C
TI
O
N
Ba
ttery
e
nerg
y
stora
g
e
(BES
)
sys
t
em
i
s
a
n
i
m
porta
nt
e
le
me
nt
i
n
t
h
e
re
ne
w
a
bl
e
e
n
er
gy
(
R
E)
s
ystem
and
e
l
e
c
t
ric
ve
hic
l
es
(
EV
)
ap
pl
ica
t
io
ns
[
1,
2
].
I
n
so
l
a
r
ph
o
t
ov
o
l
ta
ic
(
P
V
)
sys
t
e
m
a
pp
l
i
c
a
t
i
o
n,
t
he
i
n
t
egr
a
tio
n
of
B
ES
w
i
t
h
th
e
P
V
s
yst
e
m
is
one
p
ro
ve
n
me
t
h
o
d
i
n
mi
t
i
ga
tin
g
th
e
ou
tput
p
o
w
er
fl
u
c
t
u
a
t
ion
s
o
f
P
V
s
ou
rc
e
s
[3].
C
ur
rent
l
y
,
ther
e
ar
e
var
i
o
u
s
t
ypes
o
f
b
a
tter
i
e
s
c
om
me
rcia
l
l
y
a
v
a
i
l
a
b
l
e
f
o
r
B
E
S
s
u
c
h
a
s
L
e
a
d
-
A
c
i
d
(
L
A
)
,
Li
t
h
i
u
m
-
io
n
(Li-i
on),
N
i
cke
l
M
e
t
al
H
y
d
ride
(
N
i
MH
),
N
ickel
Cadm
i
um
(
N
i
Cd)
,
S
od
ium
S
u
lp
hur
(
N
a
S
)
a
n
d
ma
ny
more
[
4,
5
].
L
i-i
o
n
ba
t
t
e
r
ies
ha
ve
o
utsta
n
din
g
a
p
p
l
i
c
a
ti
o
n
s
e
s
pe
c
i
al
ly
i
n
the
ope
rat
i
o
n
o
f
p
l
ug-
in
h
y
b
r
i
d
elec
tr
ic
v
e
h
i
c
le
s
(P
H
E
V
s
)
a
nd
p
o
w
e
r
gr
i
d
a
pp
l
i
cat
i
o
n
s
.
Th
is
i
s
du
e
to
i
t
s
c
h
a
ra
ct
erist
i
c
s
of
h
ig
h
en
e
r
gy
den
s
i
t
y,
h
i
g
h
c
h
arge
a
n
d
d
isc
h
arge
a
b
ili
ty,
l
o
w
sel
f
-
d
i
s
c
h
a
r
ge
lo
ss,
l
ong
est
cy
cl
e
l
i
f
e
,
hig
h
e
st
e
f
fi
c
i
en
cy
,
a
n
d
no m
e
m
o
ry e
ffe
c
ts c
ompa
red
t
o
t
he
a
ll
othe
r ba
tter
y
tec
hno
l
o
g
i
e
s
[4
,
6
].
Rec
e
n
t
l
y,
a
s
i
m
ula
t
i
on
st
udy
i
s
a
freq
u
e
n
t
l
y
u
sed
tec
h
n
i
qu
e
to
d
e
si
gn
a
nd
d
ev
e
l
op
a
h
i
g
h
e
f
fici
e
nc
y
and
r
o
b
u
st
c
o
n
tr
ol
s
trate
g
y
of
t
he
B
ES
s
ystem
,
p
a
r
t
i
c
u
lar
l
y
in
e
l
e
c
t
ric
ve
h
i
c
l
e
s
a
nd
pow
er
s
ystem
app
l
ica
t
i
o
ns.
The
s
i
mula
t
i
o
n
t
e
c
hn
i
q
u
e
can
r
e
duce
t
h
e
c
o
st
o
f
c
om
m
e
rc
i
a
l
i
z
a
tio
n
o
f
n
e
w
t
e
c
hn
o
l
og
y
a
s
i
t
ca
n
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2088-
8694
I
nt
J
P
ow
Elec
& Dr
i
S
y
st V
ol.
11,
N
o.
1
, Ma
r
202
0
:
333
–
34
1
33
4
avo
i
d
the
un
ne
c
e
ssary
p
roc
e
d
ure
s
i
n
t
e
s
t
i
ng
so
a
s
a
v
o
i
di
n
g
t
he
p
u
rc
h
a
se
o
f
ex
pe
nsi
v
e
m
easuri
ng
ins
t
ru
m
e
nts.
S
i
m
u
l
a
t
i
o
n
s
t
u
die
s
o
f
BES
co
ntr
o
l
sys
t
em
h
a
v
e
bee
n
e
xte
n
si
vel
y
ca
rrie
d
o
u
t
i
n
the
pa
st
[
7-1
3
].
I
n
thi
s
r
egar
d,
sever
a
l
ba
tter
y
m
ode
l
s
w
e
r
e
pro
pose
d
t
o
fu
rthe
r
eva
l
ua
te
a
n
d
d
e
ve
lo
p
t
h
e
BES
c
o
n
t
ro
l
syste
m
.
A
n
a
ccur
a
te
bat
t
ery
m
o
d
e
l
i
s
n
e
e
de
d
as
i
t
ha
s
d
i
rec
t
i
nfl
u
e
nce
t
o
t
he
s
ta
t
e
-
of-cha
rge
w
h
ich
ca
n
affec
t
t
he
r
ob
us
tne
ss
of
t
h
e
BE
S
c
o
n
t
r
o
l
sy
ste
m
[
12-
14].
I
n
[
1
5
]
,
a
b
r
i
e
f
ove
rview
o
f
s
e
v
era
l
b
a
t
tery
m
ode
l
s
f
or
v
ari
ous
a
pp
lic
a
tio
ns
a
re
p
re
se
n
t
ed.
The
bat
t
ery
m
o
del
s
a
re
c
la
ssifi
e
d
i
nt
o
se
ver
a
l
c
a
t
e
gor
ie
s:
s
imp
l
e
m
o
del,
T
he
ve
nin-
base
d
mod
e
l
,
i
m
p
eda
n
ce-
base
d
mode
l,
r
u
n
tim
e
-
base
d
mode
l,
c
om
b
i
ne
d
ele
c
t
r
i
c
a
l
c
irc
u
i
t
-
b
a
s
e
d
m
o
d
e
l
,
a
n
d
g
e
neric-
bas
e
d
m
o
de
ls.
A
ge
n
e
r
i
c
bat
t
ery
m
ode
l
is
a
cc
ura
t
e
a
n
d
ap
pro
p
ria
t
e
fo
r
all
ty
pe
s
o
f
b
att
er
y
e
n
er
g
y
s
t
o
r
a
ges.
I
n
[16
]
,
a
n
i
mpr
ove
d
an
d
ea
sy
t
o
use
ge
ne
ric
ba
t
t
er
y
mode
l
i
s
p
r
e
se
nte
d
f
or
e
l
e
ctri
c
ve
h
i
c
le
a
pp
l
i
c
a
t
i
o
ns.
H
o
w
e
ver
,
t
he
p
a
r
am
ete
r
s
of
the
ba
t
t
e
r
y
m
o
del
nee
d
t
o
be
m
a
nual
l
y
o
bta
i
ne
d
fr
om
b
at
t
e
ry
m
a
n
ufac
tu
re
r
discha
rge
c
u
rve.
T
his
r
e
sult
s
in
po
or
m
ode
l
p
e
rforma
n
ce
w
he
n
imp
l
em
en
te
d
i
n
t
he
s
im
ulat
i
on
s
o
ft
w
ar
e.
T
he
a
c
c
ura
c
y
of
t
he
b
a
tter
y
parameters
e
xtraction
has
dir
e
ct
e
f
f
ect
s
on
t
h
e
p
e
rfo
rman
ce
o
f
t
h
e
ba
t
t
ery
m
o
del.
T
o
a
c
c
u
rate
ly
e
st
im
a
t
e
the
mode
l
para
me
t
e
rs,
one
e
ffect
ive
w
a
y
is
b
y
pe
rform
i
n
g
p
ara
m
e
t
e
r
extra
c
ti
o
n
f
rom
manu
fac
t
ur
er
d
isc
h
a
r
g
e
curve
s
u
s
i
ng
o
p
tim
iza
t
io
n
a
p
proac
h
.
A
Q
u
ant
u
m
-
beha
ve
d
P
a
r
t
ic
l
e
Sw
a
r
m
O
p
tim
i
z
at
i
on
(
Q
PS
O)
a
nd
Pa
rticle
S
w
arm
O
p
t
i
m
i
zat
i
on
(
P
S
O
)
ar
e
used
t
o
ob
ta
in
i
n
g
t
h
e
Li-i
on
ba
tt
e
ry
p
a
r
amet
e
r
s
f
r
o
m
t
h
e
manu
fa
ct
u
r
er
di
sc
harge
c
u
rv
e
for
t
h
e
ele
c
t
ric
ve
h
i
c
l
e
ap
pl
ica
tio
n
ha
ve
b
ee
n
pr
esen
t
e
d
i
n
[
17]
a
n
d
[
18],
re
spe
c
ti
ve
ly.
Whe
r
ea
s,
i
n
[
1
9
]
,
a
pa
ralle
l
Jaya
a
lg
orit
h
m
i
s
app
l
ied
t
o
e
stim
ate
t
h
e
Li-i
on
bat
t
er
y
para
me
ters
a
nd
t
h
e
si
m
u
lat
i
on
resul
t
s
sh
ow
ed
g
o
o
d
p
er
form
anc
e
o
f
the
deve
lope
d
a
l
g
ori
t
hm
.
The
s
p
e
c
i
f
ic
o
p
t
imi
z
a
tio
n
alg
o
ri
t
h
ms
u
se
d
in
[
1
7
-1
9]
h
ow
e
v
e
r
g
i
v
es
c
hal
l
e
n
g
e
s
t
o
t
he
u
ser
w
i
t
h
lim
it
e
d
a
c
ces
s
to
t
he
o
p
timiz
a
tio
n
code
s.
A
n
e
a
sy
t
o
use
gu
ide
line
for
suc
h
p
ar
am
etric
op
t
i
miz
a
t
i
o
n
stra
te
gy
sh
o
u
ld
b
e
d
e
vel
o
ped
c
ons
i
d
er
in
g
w
i
de
ly
a
va
i
l
a
b
le
o
pt
imiza
tio
n
appr
oac
h
. T
his
pa
per
pre
s
e
n
ts par
a
m
e
t
ers estim
ati
o
n s
t
rate
g
y
o
f t
h
e
BES mode
l
us
i
n
g w
i
de
ly
u
sed heur
ist
i
c
o
p
t
i
miza
tio
n a
p
proac
h
es suc
h
as P
a
r
ti
c
l
e
S
w
ar
m O
p
ti
m
i
za
t
i
on
(P
S
O
) and G
e
net
i
c
Al
go
rit
h
m
(GA)
.
I
n
a
d
d
iti
on
,
Grav
i
t
a
t
i
on
al
S
ear
ch
A
l
g
o
r
i
t
h
m
(
GS
A)
i
s
also
u
sed
f
o
r
co
mp
ari
s
on
p
u
r
po
se
a
nd
di
versi
f
y
t
h
e
resu
lt
s
o
f
o
pt
i
m
i
zati
o
n.
T
he
g
e
n
e
r
ic
b
a
tter
y
m
ode
l
[16]
o
f
L
i
-
i
o
n
t
y
p
e
is
c
ons
ider
ed
i
n
w
h
ich
i
t
s
para
me
ters
a
re
e
xtrac
t
e
d
fro
m
the
ma
nufa
c
t
ur
er
d
i
s
c
h
arg
e
c
urves
.
F
i
na
lly,
ba
se
d
o
n
t
h
e
p
r
o
pose
d
h
e
u
r
i
sti
c
op
tim
iza
t
i
o
n a
p
pr
oache
s
, the
c
om
par
i
s
on o
f
Li-i
on ba
tter
y
m
odel
di
s
ch
a
r
ge
p
erf
o
rman
c
e
i
s
p
re
sent
e
d
.
2.
RESEARCH
M
ETH
O
D
The
pre
s
e
n
t
w
o
rk
i
s
c
a
rr
i
e
d
ou
t
fr
om
t
he
d
eve
l
o
p
m
e
n
t
o
f
acc
urat
e
Li
-ion
b
at
t
e
ry
m
o
d
el
.
Th
e
n
,
th
e
para
me
ters
o
f
t
h
e
de
ve
lo
pe
d
L
i
-
i
on
m
ode
l
a
r
e
op
t
i
m
i
zed
u
s
i
n
g
h
e
ur
ist
i
c
o
p
t
i
m
i
z
a
t
i
on
m
e
tho
d
s
c
ons
i
d
er
ing
the
P
S
O
,
G
S
A
,
a
nd
G
A
re
specti
v
e
l
y.
T
h
e
n,
t
he
o
p
t
im
al
L
i-i
on
ba
t
tery
m
ode
l
i
s
v
a
l
i
d
at
e
d
b
y
com
p
ari
ng
th
e
cha
r
ac
t
e
ris
tic
c
urve
s o
f
t
h
e
o
p
tima
l
L
i-i
on ba
tter
y
m
ode
l de
ve
l
o
p
e
d
, w
i
t
h t
h
e
tes
t
data
fr
om
t
he
m
anufa
c
t
urer
.
2.1.
Dev
e
lo
pment
o
f
l
i-io
n
ba
tte
ry
mo
d
el
The
L
i
-io
n
b
a
tter
y
m
ode
l
is
i
mple
me
nte
d
acc
ordi
n
g
t
o
t
h
e
Tre
m
bl
a
y
’
s
g
ener
i
c
b
atter
y
m
ode
l
prese
n
t
e
d
i
n
[
1
6
]
.
T
his
mode
l
is
h
i
gh
e
f
fi
c
ie
ncy
a
nd
ca
n
gi
ve
g
o
o
d
p
erf
o
rm
ance
i
n
st
u
d
i
e
s
relate
d
t
o
e
le
ctri
c
v
e
hi
cl
e
s
and
r
e
n
e
w
abl
e
e
n
e
rgy
t
e
c
hno
log
i
e
s
.
Th
e
mod
e
l
can
b
e
re
pre
s
e
n
t
e
d by
usi
ng e
q
u
a
tio
ns
t
o
de
scr
i
be
the
elec
tr
ochem
i
ca
l
beh
a
v
i
or
o
f
the
b
a
t
t
ery
in
t
e
r
m
s
o
f
sta
t
e
-
of-c
h
ar
ge
(
S
O
C),
term
ina
l
v
ol
t
a
ge
a
n
d
i
n
t
erna
l
resista
n
ce
.
The
form
ul
a
t
e
d
e
qua
t
i
on
s of t
he
dyna
mic
m
ode
l a
r
e
d
escribe
d
a
s
fol
l
ows:
(
1
)
1
00
(
2
)
,
∗
(
3
)
,
.
∗
(
4
)
wher
e
V
Bat
i
s
t
h
e
ba
tte
ry
v
olt
a
ge
,
R
int
i
s
t
h
e
b
a
t
t
e
r
y
i
n
t
e
r
n
a
l
r
e
s
i
s
t
a
n
c
e
,
I
Bat
i
s
the
bat
t
ery
cur
r
ent,
Q
i
s
t
h
e
ce
l
l
ca
paci
t
y
,
E
Bat
i
s
t
h
e
ba
tt
e
r
y
e
l
ectr
o
m
o
t
i
ve
f
or
ce,
E
Bat,
dis
c
and
E
B
a
t,charg
a
r
e
t
h
e
b
a
t
t
e
r
y
e
l
e
c
t
r
o
m
o
t
i
v
e
f
o
r
c
e
dur
in
g
c
h
arge
a
nd
disc
ha
rge,
E
0
i
s
t
h
e
b
a
tt
ery
op
e
n
-c
i
r
cu
it
v
olt
a
g
e
,
K
i
s
t
h
e
p
o
l
a
ri
sat
i
on
c
ons
tan
t
/p
ola
r
isa
tio
n
resistance.
The
term
it
c
a
n
b
e
ob
ta
ine
d
by
in
te
gra
tio
n
t
h
e
ba
t
t
e
r
y
c
u
rre
nt
,
i
.
e.
ʃ
I
Ba
t
d
t
,
w
h
i
c
h
i
s
t
h
e
a
c
t
u
a
l
bat
t
ery
curre
n
t
.
Where
a
s,
i
*
i
s
t
he
fi
l
t
e
r
ed
c
urr
e
nt.
T
h
e
e
xpo
ne
n
tia
l
zo
n
e
o
f
ba
t
t
er
y
d
i
sc
har
ge
c
ur
ve
s
a
r
e
repr
esente
d
by
A
,
wh
i
c
h
i
s
t
he
e
xp
on
en
ti
al
z
o
n
e
vol
t
a
g
e
,
a
n
d
B
r
epr
e
se
nt
s
the
ex
p
one
ntia
l
z
one
t
ime
c
o
nsta
n
t
i
n
v
e
r
s
e
.
F
o
r
t
h
e
b
a
t
t
e
r
y
m
o
d
e
l
,
t
h
e
r
e
a
r
e
s
e
v
e
r
a
l
s
p
e
c
i
fi
c
a
s
s
u
m
p
t
i
o
ns
a
nd
lim
ita
t
i
o
n
s
s
u
c
h
a
s
ther
e
i
s
n
o
se
lf-
di
sc
harge
,
t
he
nom
i
n
a
l
c
ap
ac
i
t
y
a
nd
i
n
te
rna
l
r
e
s
i
s
ta
nc
e
are
con
sta
n
t,
a
nd
there
a
r
e
no
e
nviro
n
m
enta
l
con
s
i
d
era
tio
ns.
From
t
he
d
e
v
elo
p
e
d
b
a
tter
y
m
ode
l,
B
ES
s
y
s
tem
m
o
de
l
ca
n
be
c
o
n
s
t
r
u
c
t
ed
b
y
se
r
i
es/
p
a
r
alle
l
c
o
mb
in
a
t
i
o
n
of
s
i
ngl
e
b
a
t
t
e
ry
c
e
l
l
p
a
ramet
e
rs.
Tabl
e
1
il
lu
st
ra
te
d
t
h
e
tra
n
sf
orm
a
tion
o
f
b
a
t
t
e
r
y
c
e
ll
Evaluation Warning : The document was created with Spire.PDF for Python.
Int J
P
o
w
E
l
e
c
&
D
ri S
yst
IS
S
N
:
2088-
86
94
Accur
a
te
b
a
tte
ry
m
odel
p
a
r
a
m
e
t
e
r ide
n
ti
fic
at
i
on u
s
i
n
g he
ur
istic
o
p
t
i
m
i
z
a
t
i
on
(Mo
hd A
f
if
i
Jus
o
h)
33
5
p
a
ramet
e
rs,
wh
ere
th
e
nu
mbe
r
o
f
ce
ll
s
in
s
e
r
i
e
s
(
n
s
)
and
par
a
ll
el
(
n
p
)
deter
m
i
n
es
t
he
t
o
t
a
l
o
u
t
pu
t
t
e
r
m
inal
vo
lta
ge a
n
d
ca
p
aci
t
y
or
to
t
a
l
si
ze
of a
BES
s
yste
m,
re
s
pecti
v
el
y.
Tab
l
e 1.
Bat
tery
p
ara
m
e
t
ers tr
ansform
a
ti
o
n
Pa
r
a
m
e
te
rs
(
unit
)
V
al
ue
E
nd
of
nom
ina
l
z
o
n
e
volt
a
g
e
(
V)
V
nom
×
n
s
E
nd
of
nom
ina
l
z
o
n
e
c
a
p
ac
ity
(
A
h
)
Q
no
m
× n
p
R
a
t
e
d
cap
ac
i
t
y
(
A
h
)
Q
ra
te
d
× n
p
Inte
rna
l
r
e
s
ist
a
n
c
e
(
Ω
)
I
in
t
× n
p
/ n
s
M
a
x
i
m
u
m
cap
acit
y
(
Ah
)
Q
ma
x
× n
p
Fully
c
h
a
rge
d
volta
g
e
(V)
V
full
× n
s
N
o
m
i
na
l
d
i
sc
ha
rg
e
c
u
r
r
e
n
t
(
A
)
I
no
m
,
disc
× n
p
E
nd
of
e
xpone
ntia
l
z
o
ne
volt
a
g
e
(
V)
V
exp
×
n
s
End
of
e
xpone
ntia
l z
one
c
a
p
a
c
i
t
y
(
A
h)
Q
ex
p
×
n
p
2.2.
B
a
tter
y
p
arame
t
er
s
extr
action
me
t
h
o
d
The
ba
tt
ery
pa
ram
e
te
rs
c
a
n
b
e
a
p
prox
ima
t
e
d
b
y
us
ing
the
m
a
nufa
c
t
u
rer’
s
data
by
fol
l
ow
i
ng
th
e
proce
dures
g
i
v
e
n
i
n
[1
6]
.
F
i
g
u
re
1
ill
us
trate
s
t
he
b
a
t
tery
p
ar
a
m
e
ters
e
xtra
cti
o
n
pr
o
c
ed
u
r
e
from
the
ty
pica
l
d
i
s
c
h
a
rg
e
cu
rves
f
ro
m
t
h
e
ma
n
u
f
act
u
r
er.
As
i
llu
s
t
r
a
t
e
d
i
n
t
h
e
fi
g
u
r
e
,
thr
ee
i
m
porta
nt
p
o
i
nts
na
me
ly
f
u
lly
cha
r
ge
d
v
o
l
t
a
ge
(
V
full
),
e
nd
of
e
x
p
o
n
e
n
t
i
a
l
zo
ne
(
V
ex
p
,
Q
exp
)
and
en
d
o
f
nom
i
n
a
l
z
one
(
V
nom
,
Q
nom
)
are
ma
nual
l
y
o
b
t
a
i
ne
d
from
t
he
fi
gur
e.
F
rom
the
s
e
p
o
i
n
t
s,
t
he
p
ar
am
e
ters
o
f
E
0
,
A
,
B,
a
nd
K
can
b
e
d
e
t
e
rmi
n
ed.
The
par
a
m
e
ter
s
a
ccur
acy
fro
m
thi
s
a
p
p
roa
c
h
i
s
de
pe
nds
on
t
h
e
a
c
c
u
r
acy
o
f
the
po
in
ts
m
a
r
ked
o
n
t
he
c
ur
ves.
In
p
ra
c
t
i
c
e
,
i
t
is
d
i
f
fi
c
ult
to
i
de
n
t
if
y
a
c
o
rrec
t
p
o
i
nt
o
n
t
h
e
c
u
rves
j
us
t
by
u
si
ng
v
i
s
ua
l
a
n
a
l
y
s
is.
T
h
i
s
i
s
b
e
c
a
use
the
raw
da
ta
o
f
the
ma
n
u
fac
t
ur
er
d
ischar
ge
c
urve
s
nor
ma
l
l
y
n
o
t
su
pp
l
i
e
d
t
o
the
user
.
Th
us,
an
i
n
t
e
llige
n
t
appr
oa
ch
i
s
a
promis
in
g
w
a
y
t
o
o
ve
rcom
e
th
is
i
ssue
.
B
y
u
s
i
ng
a
n
o
p
t
i
m
iz
a
t
i
on
a
p
p
r
oach,
a
goo
d
m
odel
des
i
g
n
c
a
n
b
e
a
c
hie
v
e
d
acc
ordi
n
g
t
o
a
p
p
l
i
c
a
t
i
o
n
nee
d
s
a
n
d
ca
n
a
void
hum
an
e
rror.
F
urth
erm
o
re,
m
o
r
e
t
im
e
ca
n be
s
ave
d
d
uri
n
g
t
h
e pa
ram
e
te
rs extra
cti
on pr
oc
ed
ure.
Figure
1.
B
a
tte
ry pa
r
am
eter
s ex
tra
c
tio
n
proc
e
dure
base
d
on
the
di
scha
rge
curve
of
p
a
n
a
soni
c
Li
-i
o
n
C
G
R 18
650AF b
a
t
t
e
r
y
[
20]
3.
OPTIMIZ
A
T
I
ON OF
B
A
T
TERY
PARAMET
E
R
S
I
n
t
he
o
p
t
imiza
tio
n
proc
es
s,
s
ix
o
pt
ima
l
p
a
r
am
eter
s
ne
ede
d
t
o
b
e
ob
ta
in
ed
w
h
i
ch
a
re
V
fu
ll
,
V
exp
,
Q
ex
p
,
V
nom
,
Q
no
m
a
n
d
R
in
t
.
The
ob
je
c
t
i
v
e
o
f
t
he
o
ptim
i
z
at
i
on
pr
o
b
l
e
m
is
t
o
m
i
n
i
mize
t
he
de
v
i
ati
on
o
f
t
he
d
e
v
el
o
p
ed
bat
t
ery
m
o
de
l
di
scha
rge
c
u
rv
e
s
w
it
h
t
h
e
r
e
al
b
a
t
tery
d
i
s
c
h
arge
c
u
rve
d
a
ta
o
b
t
ai
ne
d
fr
o
m
t
he
m
a
nufa
c
ture
r
data
shee
t.
I
n
thi
s
r
ega
r
ds,
t
h
e
o
b
je
ct
i
v
e
fu
nct
i
on
i
s
de
term
ine
d
ac
c
o
rdi
n
g
to
(
5),
w
h
ere
the
ve
ct
or
x
a
n
d
k
repr
esent
t
h
e
bat
t
er
y
pa
ram
e
te
rs
a
n
d
t
h
e
i
n
d
e
x
o
f
t
h
e
sam
p
le
d
d
at
a,
r
es
p
e
c
tiv
e
l
y
.
W
h
i
l
e
,
V
bat,
m
od
(k)
and
V
bat,m
a
nu(k)
repr
e
s
en
t
the
vo
l
t
a
g
e
da
ta o
f
the
d
e
ve
lo
pe
d
bat
t
e
r
y
m
ode
l
a
n
d
t
he v
olta
ge
d
a
t
a
o
f
r
e
a
l
Li-
i
on
bat
tery
from
t
he
m
an
ufac
t
u
r
e
r.
T
he
o
pt
i
m
iza
t
io
n
pro
b
lem
is
s
o
l
ve
d
by
t
h
re
e
d
i
ffer
en
t
a
l
g
o
ri
thm
s
w
h
i
ch
a
re
P
S
O
,
G
S
A
,
a
nd
G
A
for
c
o
mpa
r
is
o
n
purp
o
ses.
T
h
e
j
us
ti
fica
ti
on
for
se
le
c
t
i
n
g
the
s
e
t
h
re
e
al
g
o
rit
h
ms
i
s
due
t
o
t
h
ei
r
w
i
de
a
p
p
l
i
ca
bili
t
y
a
nd
r
e
a
d
i
l
y
t
o
be
i
mp
le
me
n
t
e
d
i
n
M
a
tl
a
b
.
T
h
e
s
e
a
lg
o
r
i
t
h
m
s
al
so
h
av
e
b
een
p
rov
e
n
to
del
i
v
er
g
o
od
op
tim
iza
t
i
o
n
a
ccur
acy,
par
tic
u
l
a
r
l
y
i
n
ba
tter
y
s
t
o
rage
a
pp
l
i
ca
ti
o
n
i
n
r
e
new
a
ble
e
n
erg
y
source
s [7,
12, 13,
21-
23].
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2088-
8694
I
nt
J
P
ow
Elec
& Dr
i
S
y
st V
ol.
11,
N
o.
1
, Ma
r
202
0
:
333
–
34
1
33
6
,
,
(
5
)
3.1.
Part
i
c
le sw
a
r
m
op
t
imizati
o
n (PS
O
)
The
P
S
O
alg
o
rit
h
m
ha
s
be
e
n
i
n
v
e
n
te
d
b
y
K
enne
dy
a
nd
Elbe
rt
i
n
1
9
95
[2
4]
.
The
ge
nera
l
pr
ocess
o
f
the
P
S
O
a
l
g
ori
t
hm
i
s
a
s
i
l
l
us
tra
t
e
d
i
n
F
i
gur
e
2(a)
.
P
S
O
a
lgor
i
t
hm
s
o
l
v
e
s
t
h
e
pr
ob
le
m
in
(
5)
b
y
h
a
v
i
ng
t
h
e
rand
om
p
o
p
u
l
a
t
i
o
n
o
f
p
ar
tic
le
s
o
l
ut
ion
s
(
bat
t
er
y
pa
ram
e
te
rs).
P
SO
a
l
gor
it
hm
o
p
t
imiz
es
t
he
p
r
o
b
l
e
m
by
it
e
r
a
t
i
v
e
l
y
m
o
vi
n
g
t
he
se
p
ar
ticle
s
ar
o
und
i
n
t
he
s
ear
ch-s
p
a
c
e
a
c
c
ord
i
ng
t
o
sim
p
l
e
m
at
hem
a
ti
ca
l
for
m
ula
as
descr
i
be
d i
n
(
6), (7), (
8), w
h
er
e
and
a
re
the previo
u
s a
n
d up
da
ted p
o
si
ti
on o
f
part
i
cle
j
;
and
are
the
pr
ev
io
us
a
n
d
u
pda
te
d
ve
loc
i
ty
o
f
p
a
rti
c
le
j
;
P
best,j
and
G
bes
t
a
re
t
he
b
es
t
p
o
si
tio
n
of
p
artic
le
j
a
nd
th
e
bes
t
p
osi
t
i
on
o
f
t
he
e
n
t
i
r
e
par
tic
le
s
olu
t
i
o
ns;
c
1
a
nd
c
2
a
re
c
og
n
i
t
i
ve
a
n
d
s
ocia
l
lear
nin
g
r
a
t
e
s
;
r
1
a
nd
r
2
a
r
e
t
h
e
rand
om
numb
e
r
betw
ee
n
0
t
o
1
;
ω
,
ω
min
,
a
nd
ω
ma
x
a
re
r
epresen
t
ed
t
he
t
ot
a
l
w
e
i
gh
t,
m
in
i
m
um
w
e
i
g
h
t
an
d
ma
ximum
w
e
igh
t;
it
i
a
nd
it
ma
x
a
re
num
ber
of
c
ur
ren
t
ite
rati
o
n
a
n
d
m
axim
um
itera
t
i
on
,
r
e
spec
t
ive
l
y.
F
or
a
rob
u
st
a
n
d
f
ast
co
nver
g
e
n
ce
P
S
O
a
lg
orit
hm
p
roce
ss,
par
a
m
e
ters
o
f
c
1
,
c
2
,
ω
mi
n
,
and
ω
ma
x
a
re
s
e
t
t
o
2,
2
,
0.
4
and
0.9 a
s
desc
r
ibe
d
in [
12].
(
6
)
,
(
7
)
(
8
)
F
i
gure
2. O
pti
m
i
z
at
io
n proc
e
dures
u
si
ng
P
S
O
,
G
S
A
a
nd G
A
3.2.
Gra
v
it
ationa
l
se
arch
al
gor
ith
m
(
GS
A)
G
S
A
is
a
n
op
t
i
miza
t
i
o
n
a
lg
or
i
t
hm
b
ase
d
o
n
N
e
w
t
on’s
fa
m
ous
l
aw
o
f
gra
v
i
t
y
a
n
d
m
ass
in
tera
ct
ion
s
[2
5].
The
simp
lified
p
r
o
c
e
s
s
o
f
G
S
A
a
l
g
o
ri
thm
is
i
l
l
ustra
t
e
d
i
n
F
i
gur
e
2(
b
)
,
w
h
ere
the
pr
ocess
is
s
tar
t
e
d
w
i
t
h
the
i
n
itia
lizi
n
g
t
h
e
ra
nd
om
a
gen
t
p
op
u
l
at
i
on.
I
n
G
S
A
,
t
he
u
pda
t
e
d
p
o
s
it
i
on
an
d
v
e
loc
ity
o
f
the
ag
e
n
t
is
c
a
l
c
u
l
a
t
e
d
u
s
i
n
g
(
9
)
a
n
d
(
1
0
)
,
w
h
e
r
e
r
i
i
s
the
random
numb
e
r
betw
ee
n
0
to
1
a
nd
i
s
a
n
acc
elera
t
i
o
n
of
t
he
age
n
t
a
t
t
he
c
u
rrent
ite
rati
o
n
,
respe
c
t
i
ve
ly.
The
a
c
c
e
lera
ti
o
n
of
t
he
a
ge
n
t
i
s
ob
tai
n
e
d
u
s
i
n
g
(
11),
w
h
e
r
e
a
n
d
,
a
re the
t
ota
l
f
o
r
c
e
tha
t
ac
t
s
o
n
age
n
t
an
d t
h
e
i
n
ert
i
al m
ass o
f the
age
n
t,
(
9
)
(
10)
Evaluation Warning : The document was created with Spire.PDF for Python.
Int J
P
o
w
E
l
e
c
&
D
ri S
yst
IS
S
N
:
2088-
86
94
Accur
a
te
b
a
tte
ry
m
odel
p
a
r
a
m
e
t
e
r ide
n
ti
fic
at
i
on u
s
i
n
g he
ur
istic
o
p
t
i
m
i
z
a
t
i
on
(Mo
hd A
f
if
i
Jus
o
h)
33
7
/
,
(
11)
3.3.
Gen
e
tic
algor
it
h
m
(
GA)
G
A
i
s
a
n
a
lg
orit
hm i
ns
p
i
r
e
d b
y
the
pr
o
cess o
f
n
a
t
ur
a
l
e
vo
lu
t
i
on
.
G
A
a
l
g
orit
hm
h
as bee
n
s
u
cc
ess
f
u
l
l
y
app
l
ied
t
o
a
w
ide
range
o
f
rea
l
-
w
orld
p
ro
ble
m
o
f
si
gn
ifi
c
a
n
t
c
om
ple
x
it
y.
S
t
a
rti
ng
w
i
t
h
a
r
a
ndoml
y
g
en
er
ated
po
p
u
l
a
tio
n
(c
hr
omosom
es),
G
A
a
l
gorithm
use
s
t
hre
e
m
ain
type
s
of
r
u
l
e
s
(
s
e
l
e
c
t
i
o
n
,
c
r
o
s
s
o
v
e
r
,
a
n
d
m
u
t
a
t
i
o
n
)
at
e
ac
h
s
t
e
p
t
o
p
r
o
d
u
ce
a
suc
cessor
po
p
u
l
a
ti
on
f
or
t
he
n
e
x
t
ge
n
era
t
i
o
n
as
i
llus
t
ra
t
e
d
i
n
F
i
gur
e
2(
c).
Dur
i
n
g
selec
t
i
o
n
rule
s,
t
he
p
a
r
en
t
chr
o
mos
o
m
e
t
ha
t
con
t
ri
b
u
tes
t
o
t
he
p
o
p
u
l
at
i
on
i
s
s
e
l
e
c
te
d
f
o
r
the
ne
xt
g
e
n
era
tio
n
proce
s
s.
T
he
s
elec
t
e
d
pare
nt
c
hrom
osom
es
a
r
e
r
e
-
com
b
ine
d
t
o
pr
o
duc
e
c
h
i
l
d
c
hrom
os
o
m
e
s
.
These
pr
ocesses
are
itera
ted u
n
t
il t
h
e sa
tis
fa
ct
o
r
y fi
t
n
e
ss leve
l
i
s
r
ea
ched.
3.4.
V
a
l
i
d
a
ti
on
o
f an
op
t
imal b
atte
ry m
od
el
The
o
p
t
i
ma
l
L
i
-i
o
n
b
a
t
tery
m
ode
l
in
t
he
s
im
u
l
at
ion
is
v
al
i
d
a
t
ed
b
ased
o
n
t
h
e
typ
i
ca
l
di
sc
h
a
rge
cha
r
ac
t
e
ris
tics
curve
of
P
anas
on
ic
L
i
-
io
n
CGR1
86
5
0
A
F
f
rom
the
m
a
n
ufac
t
u
re
r
fol
l
o
w
i
n
g
t
h
e
p
r
o
cedure
s
i
n
[1
6].
D
u
r
i
ng
v
a
li
d
a
t
i
o
n
,
the c
ons
ta
n
t
ba
t
t
e
ry
curr
e
nt a
re set
a
t
0.2
C
(
0.4
3
A
), 1C (2.
15 A
)
and 2
C
(
4.3 A
)
. The
resul
t
s ar
e
as show
n in
t
he
re
s
ults a
n
d
d
iscu
s
s
i
on
se
ct
i
on.
3.5.
Simu
lati
on
s
e
t
-up
for batt
ery mod
el p
ara
m
et
er
opt
i
m
i
z
a
ti
on
F
i
gure
3
i
l
l
us
t
r
ate
s
t
he
o
ver
a
l
l
s
imula
t
i
o
n
set-u
p
d
iagra
m
f
o
r
opt
i
m
i
z
atio
n
of
b
att
e
ry
p
ara
m
e
t
ers.
D
u
rin
g
t
he
o
p
t
i
m
izat
io
n o
f
t
he
ba
tte
ry pa
r
am
eter
s proc
ess, the
de
ve
l
o
pe
d b
a
tter
y
m
ode
l in
Mat
la
b
/
S
i
m
u
l
i
nk
is
lin
ke
d
to
t
he
P
SO
/G
SA
/G
A
a
l
g
o
ri
t
h
m
in
t
he
M
at
la
b/
M-file
a
s
p
rese
n
t
e
d
i
n
F
i
g
u
r
e
3
.
M
e
a
n
w
h
i
l
e
,
t
h
e
t
y
p
i
c
a
l
di
sc
harge
da
ta
f
rom
the
ma
nufac
t
u
re
r
da
t
a
i
s
sa
ve
d
in
M
a
t
l
a
b
/
MA
T-
fi
l
e.
B
efore
t
h
e
op
tim
i
z
at
ion
pro
c
e
s
s
i
s
st
a
r
te
d,
t
he
p
o
p
u
l
a
t
i
on
num
b
e
r,
d
im
ensi
o
n
num
ber
,
a
n
d
ite
rati
on
s
a
r
e
i
n
itia
l
l
y
se
t
t
o
2
5,
6
a
n
d
1
0
0
f
or
a
ll
alg
o
ri
t
h
ms,
respe
c
t
i
v
e
l
y.
T
he
o
p
t
i
m
iza
t
i
on
pr
ocess
by
P
S
O
,
G
S
A
and
G
A
algori
t
h
m
i
s
i
l
l
u
s
t
r
ate
d
i
n
F
i
gure
2(a)
-(c).
T
he
p
r
o
c
e
sses
ar
e
sta
r
ted
w
i
th
t
he
r
a
ndom
ly
s
e
t
o
f
th
e
i
n
itia
l
p
o
p
u
l
a
t
ion
for
e
ach
b
a
t
ter
y
c
ontr
o
l
para
me
ters.
The
ge
nera
t
e
d
r
a
nd
om
p
a
r
am
eter
s
a
r
e
eva
l
ua
t
e
d
b
y
u
s
in
g
a
fi
t
ness
func
t
i
o
n
i
n
(
5
).
T
he
p
roc
e
ss
i
s
repe
ate
d
l
y
e
xe
cute
d
u
n
t
il t
h
e
op
t
i
m
a
l
p
a
ra
me
t
e
rs of
ba
tter
y
a
re
d
et
ermi
n
e
d
.
F
i
gure
3.
S
i
m
ulat
i
o
n
se
t-u
p
of
the
bat
t
e
r
y pa
r
a
m
e
te
rs opt
i
m
i
z
a
t
ion
4.
RESULT
S
A
N
D
DISCU
SSIO
N
The
de
ve
lopm
ent
process
o
f
t
he
L
i-i
o
n
bat
t
e
ry
m
ode
l
is
s
t
a
rte
d
in
t
he
M
a
tla
b
/
S
i
m
u
li
nk.
T
he
n,
t
h
e
proce
ss
is
c
o
n
t
i
n
ue
d
w
i
th
t
he
b
a
tter
y
p
ara
m
e
t
e
r
s
o
p
tim
iza
tio
n.
F
i
na
l
l
y,
t
h
e
v
a
l
i
d
a
t
i
o
n
of
t
he
o
p
t
ima
l
b
atter
y
mode
l
us
in
g
t
y
p
i
c
a
l
d
isc
h
a
r
ge
c
ur
ve
s
o
f
a
r
e
a
l
bat
t
e
r
y
from
t
he
m
an
ufa
c
turer
is
c
arr
i
e
d
o
u
t
.
The
co
m
p
let
e
resul
t
s of
t
he
b
a
t
te
r
y
’s pa
r
ameter
s op
ti
m
i
zat
io
n a
r
e
prese
n
te
d
in t
he
f
ol
lo
w
i
n
g
s
ub-
se
c
t
i
o
n.
4.1.
Op
timiz
a
t
i
on
of
b
a
tter
y
mod
el p
arame
t
er
s
Ta
b
l
e
2
ill
us
trates
t
h
e
c
omp
a
rison
o
f
t
he
o
bta
i
ned
ba
tter
y
p
ara
me
t
e
rs
f
o
r
t
he
c
ases
o
f
m
a
nua
l
a
n
d
op
tim
iza
t
i
o
n
(P
SO
,
GS
A,
a
nd
G
A
)
appr
oache
s
.
Besi
de
s
tha
t
,
the
p
erf
o
rma
n
ce
a
n
d
el
a
p
se
d
t
i
me
o
f
op
tim
iza
t
i
o
n
a
ppr
oache
s
a
l
s
o
pre
s
en
te
d.
F
rom
Tab
l
e
2
,
t
h
e
G
A
a
p
pr
oac
h
c
on
ve
rge
d
f
a
s
ter
com
p
are
d
t
o
t
h
e
ot
her
a
p
proac
h
e
s
w
ith
t
he
e
la
pse
d
tim
e
of
1
68
0
s.
W
hi
le,
for
P
S
O
and
GS
A
the
elap
se
d
t
i
me
i
s
2
0
1
3
s
and
17
6
0
s
,
re
spect
ive
l
y.
I
t
i
s
a
l
s
o
obser
ve
d
tha
t
t
he
G
A
ap
proa
c
h
is
c
on
verge
d
a
t
the
28
th
n
um
ber
of
i
t
e
ra
t
i
o
n
s,
w
h
i
l
e
P
S
O
and G
S
A
are conv
e
r
ged
at t
he
i
t
e
rati
on o
f
38 a
nd
75 a
s
i
l
l
u
s
t
rat
e
d
in F
ig
ure
4,
re
s
pe
ct
ive
l
y.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2088-
8694
I
nt
J
P
ow
Elec
& Dr
i
S
y
st V
ol.
11,
N
o.
1
, Ma
r
202
0
:
333
–
34
1
33
8
Tab
l
e
2
.
Com
pa
riso
n of
b
a
t
tery
p
ara
m
e
t
e
r
s ba
se
d o
n
m
a
n
ua
l, P
S
O
,
G
S
A
a
nd G
A
appr
oac
h
e
s
Pa
r
a
m
e
t
e
rs
(unit
)
Pa
r
a
m
e
t
e
rs e
x
t
r
a
c
t
e
d
a
pproac
h
e
s
Ma
nua
l
P
S
O
GS
A
G
A
V
nom
(
V
)
3
.
3000
3.
2201
2.
8791
2.
9114
Q
no
m
(
A
h
)
1.
8100
2.
1164
2.
1657
2.
1738
E
0
(
V
)
3
.
6971
3.
5246
3.
6125
3.
7137
R
in
t
(
Ω)
0
.
0165
0.
0701
0.
1064
0.
1422
K
0.
0265
0.
0038
0.
0050
0.
0044
A
(
A
h
)
0.
4194
0.
6806
0.
6214
0.
5917
B
(
Ah
-1
)
4.
6152
1.
6488
1.
4669
1.
7049
Q
ra
te
d
(
A
h
)
2.
2500
Q
max
(
Ah)
2.
2500
V
fu
l
l
(
V)
4
.
2000
4.
1351
4.
1275
4.
1632
I
di
s
,
n
o
m
(
A
)
1.
0000
V
ex
p
(V)
3.
6400
3.
4287
3.
3421
3.
5421
Q
exp
(A
h)
0.
6500
1.
8195
2.
0451
1.
7597
E
l
a
p
s
e
d
ti
m
e
(
s)
-
2013.
6
1760.
1
1680.
1
OF
(
x
)
-
0.
1754
0.
2532
0.
1689
F
i
gure
4. The
pe
r
form
anc
e
o
f
the
heur
ist
i
c
o
p
t
i
miza
tio
n m
e
th
o
d
s
i
n te
rms of
f
itne
s
s
fu
nct
i
o
n
I
n
t
er
ms
o
f
acc
urac
y,
t
he
G
A
appr
oach is per
f
orm
i
ng the h
i
ghe
st
a
ccu
ra
cy
w
i
t
h
t
h
e
fin
al
v
al
u
e
o
f
th
e
fi
t
ness
fu
nc
ti
o
n
,
O
F
(
x
)
i
s
0
.168
9,
w
hi
le for P
S
O
a
nd
G
S
A
are
0.
17
5
4
a
n
d
0.25
3
2
,
re
spe
ctively.
T
heref
o
re,
f
o
r
furt
her
sim
u
lat
i
o
n
s
t
u
dy,
t
he
b
at
tery
p
a
r
am
e
t
er
s
ob
ta
ine
d
by
th
e
G
A
a
pproac
h
w
il
l
be
u
sed.
B
es
ide
s
t
ha
t,
F
i
gure
5
il
lus
t
r
a
tes
t
h
e
c
o
m
p
a
r
ison
b
etw
e
e
n
t
he
d
i
s
c
h
ar
ge
c
urve
f
rom
the
ba
tt
er
y
m
a
nufa
c
t
urer
a
nd
t
he
si
m
u
late
d
d
i
sc
harge
c
u
rves
g
ener
ate
d
by
P
S
O,
G
S
A
a
nd
G
A
a
pproac
h,
r
espe
ct
i
v
e
l
y
.
F
rom
t
h
e
fi
g
ure
,
it
i
s
pro
v
en
t
ha
t by
us
in
g t
h
e
opt
i
m
i
z
at
ion
m
e
th
od, the
ba
t
tery
m
ode
l
a
ccu
rac
y
sig
ni
fic
ant
l
y
i
n
c
re
ased
.
F
i
gure
5.
A
c
o
m
pariso
n be
t
w
e
e
n the
d
i
sc
har
g
e
c
u
rve
from
the
b
at
tery
m
a
n
ufac
ture
r
and sim
u
l
a
t
e
d d
i
sch
a
r
g
e
cur
v
es ge
n
era
t
e
d
by P
S
O,
G
S
A
, and
G
A
opt
imiz
a
tio
n
appr
oa
che
s
Evaluation Warning : The document was created with Spire.PDF for Python.
Int J
P
o
w
E
l
e
c
&
D
ri S
yst
IS
S
N
:
2088-
86
94
Accur
a
te
b
a
tte
ry
m
odel
p
a
r
a
m
e
t
e
r ide
n
ti
fic
at
i
on u
s
i
n
g he
ur
istic
o
p
t
i
m
i
z
a
t
i
on
(Mo
hd A
f
if
i
Jus
o
h)
33
9
4.2.
Validation
o
f BES
m
odel
The
de
ve
lo
pe
d
Li-
i
o
n
b
a
tter
y
m
o
d
e
l
u
ti
liz
in
g
o
p
t
i
m
al
b
a
t
te
r
y
p
a
r
a
m
e
ter
s
o
b
t
a
i
ne
d
fr
om
t
he
G
A
alg
o
ri
t
h
m
ha
ve
b
ee
n
rec
o
n
s
truc
t
e
d
to
v
a
l
i
d
a
t
e
its
d
isc
h
arge
c
ur
ve
s
pe
rfor
ma
nces
a
t
d
i
ffere
n
t
dis
c
ha
rg
e
curr
ents.
The
disc
harge
c
u
r
r
ent
ran
g
e
c
ons
ider
e
d
i
s
base
d
o
n
n
o
m
i
na
l
r
a
ting
a
t
1
C,
h
ig
her
(2C)
a
n
d
l
o
w
e
r
(0.2C).
The
re
sults w
it
h r
e
spe
c
t
t
o t
h
e ma
nuf
acture
r’s data a
r
e
as show
n in F
i
gur
e 6. Ba
s
e
d
o
n
th
e
res
u
lt
s, i
t
i
s
obs
erve
d t
h
a
t
t
he disc
h
arge
c
h
a
rac
t
eris
t
i
c
s
c
ur
ves of
d
e
v
e
l
ope
d
Li-i
o
n
m
ode
l ma
t
c
h ver
y
w
e
ll w
ith the
t
yp
ica
l
di
sc
harge
c
h
ar
a
c
ter
i
s
t
ic
c
ur
ve
s
of
P
ana
s
on
ic
L
i-i
on
CG
R1
8
6
5
0
A
F
wi
th
t
he
o
v
e
ral
l
ac
cu
ra
cy
o
f
u
p
t
o
98
%
.
I
t
clea
rl
y
sh
ow
s
t
h
at
t
he
a
cc
ur
acy
o
f
the
de
ve
lo
pe
d
m
o
de
l
de
p
e
nd
s
o
n
t
he
p
re
cis
i
on
of
t
he
e
xtra
c
t
ed
p
ar
a
m
e
t
ers
data
f
rom
th
e
t
ypic
a
l
di
s
char
g
e
c
urves.
F
i
gure
6.
V
alid
ati
o
n of
t
he d
is
cha
r
ge
c
har
act
er
i
s
t
i
cs be
t
w
een
t
h
e
de
v
e
l
o
p
e
d
Li-i
on ba
tte
ry m
odel i
n
m
a
tlab
/
s
i
m
u
lin
k
and r
eal
b
a
tte
ry
m
odel
(3.3
V
,
2.25
A
h
)
5.
CONCL
U
S
ION
An
e
a
s
y
t
o
u
se
a
n
d
a
cc
ur
ate
ba
tter
y
m
o
d
e
l
p
ar
am
eter
i
de
nt
ifica
t
i
o
n
s
t
r
a
t
eg
y
i
s
i
nt
r
odu
c
e
d
usin
g
a
heur
ist
i
c
op
ti
miz
a
t
i
on
a
p
pr
oach.
T
h
e
Tr
em
blay’s
L
i
-
i
o
n
bat
t
ery
mo
de
l
i
s
d
ev
e
l
op
ed
i
n
M
a
t
l
a
b
/
S
i
mu
li
nk
base
d
o
n
t
he
f
o
r
mula
te
d
eq
uat
i
o
n
s
,
in
w
hi
c
h
t
he
p
a
r
am
eter
s
are
obtai
ne
d
from
d
iffe
ren
t
o
pt
imi
z
a
t
io
n
appr
oa
ches
o
f P
S
O
,
G
SA
and
G
A
a
l
gor
ithm
s
.
F
r
om
t
he
op
t
i
m
iza
t
i
o
n
r
esu
l
t
s
of t
h
e
m
o
del
de
v
e
l
o
p
e
d ba
se
d on
P
a
naso
nic
L
i
-i
on
CG
R
18
65
0A
F
batter
y
t
e
s
t
da
ta,
the
G
A
a
lgor
ith
m
show
e
d
t
he
b
es
t
pe
rform
anc
e
w
it
h
t
h
e
fit
n
e
ss
f
u
n
c
ti
on
a
n
d
e
l
a
p
s
ed
t
i
m
e
of
0
.1
689
a
n
d
168
0
s,
r
e
s
p
e
ct
i
v
e
l
y
.
Th
e
ac
cu
ra
t
e
b
at
t
e
ry
m
od
e
l
o
b
t
a
i
ned
by
the
G
A
a
l
gori
t
h
m
w
a
s
fur
t
he
r
va
l
i
da
te
d
by
com
p
ar
ing
t
h
e
disc
har
ge
c
ur
ves
o
f
t
he
d
e
v
e
l
o
p
e
d
b
a
t
tery
m
od
e
l
w
ith
t
he
d
isc
h
arge
c
ur
ve
s
from
t
he
m
an
u
f
a
c
ture
r.
T
he
r
e
s
u
lts
s
h
o
w
ed
t
h
a
t
t
h
e
GA-b
a
s
ed
o
pti
m
al
b
att
e
ry
mode
l g
i
ve
s
a
n
a
ccur
acy o
f u
p
t
o
9
8
%.
T
he
r
e
fore,
the o
b
ta
i
n
ed b
a
t
te
r
y
p
a
r
am
eter
s
by usi
ng t
h
e
G
A
alg
o
ri
thm
ca
n be
u
se
d in
f
urt
h
er
s
i
m
ul
at
ion
stu
dy
rela
t
e
d
to t
he
c
o
n
t
rol
l
e
r
de
s
ig
n
of
t
he
l
ith
i
u
m
bat
t
e
r
ies.
ACKNOW
LEDG
E
MEN
T
S
The
a
u
thor
s
w
o
u
l
d
l
i
k
e
to
a
c
know
l
e
d
g
e
fina
ncia
l
sup
p
o
r
t
by
U
n
i
v
er
sit
i
M
a
l
a
y
sia
Te
re
ng
ga
nu
a
n
d
Mi
ni
st
ry
o
f Edu
c
at
io
n
,
M
al
a
y
si
a
un
d
e
r t
h
e Fu
nd
ament
a
l
R
e
se
a
r
c
h
G
r
ant S
c
he
me
(F
R
G
S
)
V
o
t N
o
.
5941
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a
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s
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a
g
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f
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g
r
i
d
-
A
r
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v
i
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w
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f
stationary
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s
torage
s
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des
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m
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t
orag
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s
t
e
m
s
f
o
r
e
l
ectric
v
e
hicle
appl
icat
ions:
Issues
a
nd
c
hal
l
en
g
e
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d
S
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sta
i
na
b
l
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K
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"
M
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tig
a
ti
ng
m
e
th
ods
o
f
p
o
w
e
r
f
l
u
c
tu
a
t
i
o
n
of
p
h
o
t
ovolt
a
ic
(PV
)
so
u
rces
- A
r
eview
,
"
Ren
e
wabl
e an
d
Su
s
t
ainab
le E
n
erg
y
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e
l
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a
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t
i
a
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d
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r
l
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,
"
E
n
e
r
g
y
s
t
o
r
a
g
e
f
o
r
P
V
p
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w
e
r
p
l
a
n
t
d
i
s
p
a
t
c
h
i
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"
En
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s
ystem
s
f
or
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enew
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e
ner
g
y
power
s
ector
i
n
t
egrat
i
on
a
nd
mitiga
t
i
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n
of
i
n
t
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mi
ttenc
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Renewa
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Evaluation Warning : The document was created with Spire.PDF for Python.
I
SSN: 2088-
8694
I
nt
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P
ow
Elec
& Dr
i
S
y
st V
ol.
11,
N
o.
1
, Ma
r
202
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333
–
34
1
34
0
[6]
W.
S
u
t
op
o
a
n
d
E.
A
.
Ka
dir,
"
De
sign
in
g
fra
m
e
w
o
r
k
fo
r
sta
n
da
rd
iz
a
tio
n
cas
e
st
ud
y:
L
i
t
h
i
u
m
-i
on
b
at
tery
m
o
d
u
l
e
i
n
electri
c
veh
i
cle
appl
icat
io
n
,
"
Intern
at
ion
a
l
Jou
r
n
a
l
of El
ectrical an
d Co
mp
uter
En
gi
neer
ing
,
v
o
l
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,
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201
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M.
A
.
J
u
s
oh
an
d
M.
Z
.
D
a
ud
,
"P
arti
cle
sw
a
r
m
op
timisatio
n-b
a
sed
op
tim
al
photo
v
o
l
t
a
ic
s
y
s
te
m
of
h
o
u
rly
o
u
t
p
u
t
power
d
i
s
patch
usi
n
g
L
ithiu
m-
ion
bat
t
eries,"
Jou
r
na
l of M
echa
n
ica
l
E
ngineerin
g a
n
d
Scien
c
e
s
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[8]
J
.
S
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H
u
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W
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S
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M
o
o
n
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H
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S
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S
h
i
n
,
K
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H
.
R
y
u
a
n
d
J
.
C
.
K
i
m
,
"
N
e
w
c
o
n
t
r
o
l
s
c
h
e
m
e
f
o
r
a
b
a
t
t
e
r
y
e
n
e
r
g
y
s
t
o
r
a
g
e
sy
ste
m
f
or
o
ut
pu
t
s
t
a
b
i
l
iz
a
tion
of
a
w
in
d
g
e
ne
r
a
to
r,"
Proc
e
e
ding
s o
f
the
IEEE Po
we
r En
gine
e
r
ing
So
c
i
e
t
y
T
r
an
smis
s
i
on
and D
i
stri
bu
ti
on
Con
f
eren
ce
, pp
. 1-
5
,
2
0
1
4
.
[9]
H.
Z
hao
,
Q
.
W
u
, C
.
W
ang
,
L
.
C
h
en
g
and
C
.
N.
R
a
sm
us
sen
,
"F
u
zzy
l
og
ic
b
a
s
e
d
c
o
o
rd
in
a
t
e
d
c
on
tr
ol o
f
ba
t
t
e
r
y
e
n
e
r
gy
sto
r
age
system
a
nd
di
spat
chab
le
d
istri
buted
g
en
eratio
n
f
o
r
mi
cr
ogrid,
"
J
o
u
r
n
a
l o
f
Mod
e
r
n
Po
we
r S
y
ste
m
s
an
d
C
l
e
a
n
Energy
,
vol.
3
, N
o.
3
,
p
p
.
4
2
2
-428,
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0
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5
.
[10]
F
.
L
u
o
,
K.
M
e
n
g
,
Z.
Y.
D
on
g,
Y.
Zh
eng,
Y.
Chen
a
nd
K.
P
.
W
on
g,
"Coo
rdi
n
at
e
d
o
perati
on
al plan
n
ing
f
o
r win
d
f
arm
wit
h
b
att
e
ry en
e
rgy
st
orage
sy
s
t
em
,"
IEE
E
Tran
sa
c
t
io
ns
on
Su
sta
i
na
b
l
e
Ene
r
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s
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t
r
ol
s
trateg
y
o
f
a
g
ri
d-co
nnect
ed
p
h
o
to
vo
lt
a
i
c
w
i
t
h
b
at
tery
e
nerg
y
s
t
o
r
age
sys
t
e
m
for
ho
urly
p
o
w
e
r
d
ispa
tc
h,"
Int
e
rn
ation
a
l
Jo
ur
n
a
l of Po
wer El
ectro
n
i
cs an
d Dr
iv
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M
oh
a
m
e
d
a
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H
a
n
na
n
,
"
An
i
mpro
v
e
d
c
o
ntro
l
m
eth
od
of
b
attery
e
n
e
rgy
sto
r
age
s
y
stem
f
or
hou
rly
d
i
sp
atch
of
p
hoto
v
o
l
ta
i
c
po
w
er s
ou
rces,"
Ene
r
gy
Co
nv
e
rsio
n
a
n
d
Ma
na
ge
me
n
t
,
v
o
l.
73,
p
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256
-27
0
,
201
3.
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M
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Z
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D
a
u
d
,
A
.
M
o
h
a
m
e
d
,
A
.
A
.
I
b
r
a
h
i
m
a
n
d
M
.
A
.
H
a
n
n
a
n
,
"
H
e
u
r
i
s
tic
o
p
timi
zatio
n
of
s
t
a
te-of-ch
arge
f
eed
b
a
c
k
cont
roller
para
m
e
ters
f
or
outp
u
t
p
o
w
e
r
dispatch
o
f
hy
brid
p
h
o
t
o
v
o
lt
a
i
c/bat
t
ery
en
erg
y
s
torag
e
s
yste
m
,
"
M
e
as
ur
ement
:
Jou
r
n
a
l of th
e In
tern
at
ion
a
l
M
e
a
s
u
r
em
ent
Co
n
f
eder
at
ion
,
v
o
l
.
49
, n
o.
1
,
pp.
1
5
-
25
,
20
14
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[14]
A
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Z
a
i
n
u
r
i
,
U
.
W
i
b
a
w
a,
M
.
R
u
s
l
i
,
R
. N
.
Has
anah and
R. A. Harah
a
p
,
"
VR
L
A
b
a
t
te
r
y
s
t
a
te
o
f
h
e
a
l
th
e
s
t
i
m
a
t
io
n
b
a
s
e
d
on
chargi
ng
t
im
e,
"
T
e
lekom
n
i
k
a
,
vol
.
1
7
,
no
.
3,
p
.
15
77
,
2
0
1
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[15]
S
.
M
.
M
.
M
ousavi
G
.
a
n
d
M
.
Nik
d
el,
"V
ari
ous
b
attery
m
od
els
f
o
r
va
r
i
o
u
s
s
i
mu
la
tion
s
tu
die
s
a
n
d
a
pp
lic
a
t
io
n
s
,"
Renewa
bl
e
an
d S
u
s
t
aina
bl
e En
e
r
g
y
Reviews
,
v
o
l.
3
2,
p
p.
4
7
7
-485,
2
0
14.
[16]
O.
T
rem
b
l
a
y
an
d
L
.
A
.
Des
s
aint,
"Ex
p
eri
m
ental
v
a
li
dati
on
o
f
a
b
at
tery
d
yn
a
m
i
c
m
o
d
el
f
o
r
E
V
a
ppl
icatio
ns,
"
Wo
rld
Elect
r
i
c Veh
i
cle
Jou
r
na
l
,
v
o
l
.
3
,
n
o
.
2,
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8
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[17]
Y.
Z
h
a
ng,
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,
B
.
A
.
L
.
De
L
a
Barra
a
nd
M
.
E
.
Haq
u
e,
"
O
p
ti
mi
za
tio
n
o
f
t
rem
b
l
a
y’s
b
a
tt
e
r
y
m
o
del
p
a
ra
m
e
t
e
rs
fo
r
p
l
ug-in
h
ybrid
e
l
e
c
t
ric
v
e
hic
l
e
applicat
io
n
s
,
"
2017 Aus
t
ra
l
a
sian
Universitie
s Power Engineer
ing
Conference
(AU
P
EC
)
, pp
.
1
-
6
, 20
1
7
.
[18]
Y
.
W
a
n
g
a
n
d
L
.
L
i
,
"
L
i
-
i
o
n
b
a
t
t
e
r
y
d
y
n
a
m
i
c
s
m
o
d
e
l
p
a
r
a
m
e
t
e
r
e
s
t
i
m
a
t
io
n
usin
g
d
a
tash
eets
a
n
d
p
a
rt
icl
e
s
warm
opt
imi
zati
o
n
,
"
In
ter
n
a
t
i
onal
J
o
urna
l of Ener
gy
R
e
sea
r
ch
,
vol.
40,
no
.
8
,
pp
.
1
0
5
0
-1
061
,
2
01
6.
[19]
L.
W
ang
,
Z
.
Zh
a
n
g
,
C
. Hu
ang an
d K. L. Tsu
i
,
"A
G
P
U
-accelerat
ed
P
a
rall
el
J
aya Alg
o
ri
thm f
o
r
e
ffi
cien
tly
es
tim
a
t
i
n
g
Li-
io
n b
a
tte
r
y
m
o
de
l pa
ra
m
e
te
rs,
"
Ap
pl
ie
d S
o
f
t
C
o
mp
ut
in
g J
o
urn
a
l
,
v
o
l
.
65
,
pp.
12-20
,
2
01
8.
[20]
"
L
it
h
i
um
-io
n
B
att
e
ri
es:
In
di
vi
dua
l
data
s
h
eet,
"
2
0
1
9
[O
nli
n
e].
Av
a
i
la
b
l
e
:
htt
p
://www
.hous
e
of
batt
er
ies.
com/
document
s/C
G
R186
50AF.pd
f
. [
Acce
ss
ed:
24-Fe
b
-2019].
[21]
M.
Nad
ou
r
,
A
.
Es
sad
k
i
,
T.
Nas
s
er
an
d
M
.
F
dail
i
,
"
R
obu
st
coo
r
d
i
n
ated
co
n
tro
l
u
s
i
n
g
back
st
eppi
ng
of fly
w
heel
energ
y
sto
r
age
sy
st
em
a
nd
D
F
IG
f
or
power
s
mo
o
t
h
i
ng
i
n
w
i
nd
po
wer
p
l
ant
s,"
Int
e
rnati
o
n
a
l
Jo
ur
nal
o
f
Po
wer
El
ectro
n
i
cs
and
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Syst
e
m
s
(
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JPE
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[22]
Hlal
A
,
Ram
acha
n
daram
u
rt
hy
a
V
.,
S
a
n
j
eev
ikum
ar
P
.,
P
ou
ryekta
A
re
f,
K
abo
l
i
Ham
i
d
Reza,
T
u
a
n
Ab
R
ash
i
d
bi
n
Tuan
A
bdullah,
"
NSG
A
-II
and
MOPS
O
bas
e
d
optim
i
zati
o
n
f
o
r
si
z
i
ng
o
f
hy
brid
P
V/win
d
/b
a
t
t
e
ry
e
nerg
y
sto
r
age
sys
t
e
m
,"
Inter
nat
io
nal Jo
ur
nal o
f
P
o
wer
El
e
c
t
r
o
n
i
c
s a
nd Drive S
y
stem
s (IJPED
S
)
,
vo
l. 10
, no
.
1
,
p
p
. 4
63
-47
8
,
2
0
1
9
.
[23]
J.
S
.
Norb
aky
a
h
and
A
.
R
.
S
a
lisa,
"Op
timizati
o
n
o
f
t
he
f
uel
eco
nomy
a
nd
e
mi
ssion
s
f
or
p
lug
in
h
ybri
d
e
lect
ri
c
rec
r
e
a
t
i
o
n
al
b
o
a
t
energ
y
m
an
age
m
ent
strat
e
gy
u
sin
g
g
en
eti
c
a
lg
o
ri
t
h
m
,
"
Int
e
rn
atio
n
a
l
Jo
ur
nal o
f
Po
wer
El
e
c
tro
n
i
c
s
and
Drive
Syst
e
m
s
(
I
JPE
D
S
)
,
vol.
10,
n
o
.
2
,
p
p
.
792
,
2
019
.
[24]
R.
C
.
Eberh
a
rt
a
nd
J
.
K
e
nned
y
,
"P
arti
cle
sw
arm
o
p
t
i
mi
zatio
n
i
n
neu
r
al
n
et
wo
rks,"
IE
EE In
ter
n
a
t
io
na
l Confer
ence
,
pp.
1
9
4
2
-
194
8,
19
9
5
.
[25]
E.
R
ashedi,
H.
N
e
zam
ab
adi
-
po
u
r
a
n
d
S
.
S
a
ryazd
i,
"
GSA:
A
G
ra
v
i
t
a
ti
ona
l
S
earch
A
lgor
it
h
m
,"
Inf
o
rma
tio
n Sc
ie
nc
e
s
,
v
o
l
.
17
9,
no
.
13
,
p
p. 2
23
2-2
2
4
8
,
2
00
9.
Evaluation Warning : The document was created with Spire.PDF for Python.
I
n
t
J
P
o
w
Elec
&
D
r
i
S
y
st
I
S
S
N
:
2088-
86
94
Acc
u
r
a
t
e
b
a
t
te
ry m
odel
p
a
r
a
m
e
ter i
d
e
n
t
i
f
i
c
a
t
i
on u
s
in
g he
ur
ist
i
c o
p
tim
i
z
ati
on (
M
o
hd
A
f
if
i
Jus
o
h)
34
1
BIOGRAPHI
E
S
OF
AUT
HORS
M
ohd
A
f
i
fi
J
usoh
was
b
o
rn
i
n
Pas
i
r
M
a
s,
K
el
antan,
i
n
19
89
.
He
r
eceived
th
e
b
a
c
h
e
lor’s
d
egree
in
E
l
e
c
t
rical
E
ngi
neerin
g
f
r
o
m
U
n
i
v
e
rsit
y
T
e
knol
ogi
M
ARA
(Ui
T
M
)
,
S
h
ah
A
l
a
m
,
M
alay
si
a
in
20
13.
H
e
work
ed
a
s
elect
rical
e
n
g
in
eer
a
t
electr
i
cal
s
wit
c
hgear
c
om
pa
n
y
d
u
r
in
g
th
e
y
e
a
r
s
of
2
0
1
3
a
n
d
20
15
.
In
2
0
1
8
,
h
e
c
o
m
p
le
te
d
his
M
.
Sc
.
d
e
gree
i
n
Phy
s
i
c
s
fro
m
t
he
U
ni
ve
rsit
i
Ma
la
ys
ia
Tereng
gan
u
(
U
M
T
)
,
Malays
ia.
H
e
i
s
cu
rrentl
y
p
ursu
in
g
P
h
D
degree
i
n
P
h
y
s
i
c
s
a
t
U
n
i
v
e
r
s
i
t
i
Ma
la
y
s
ia
T
e
r
e
n
g
g
a
n
u
(UMT)
foc
u
sing
i
n
wa
ve
e
n
e
rgy
ge
ne
ra
tio
n
sy
stem
.
His
curren
t
r
esearch
in
terests
in
clud
e
ren
e
wabl
e
en
erg
y
,
ocean
w
av
e
e
n
erg
y
c
onv
ersi
o
n
and
el
e
c
t
r
ical
a
nd
m
echan
ical
con
t
rol
s
y
st
em
M
uham
a
d
Zalani
D
aud
was
b
o
rn
i
n
Tump
at,
Kelan
t
an
M
al
aysia
i
n
1
9
78.
H
e
co
m
p
let
e
d
his
bach
elor’s
Deg
ree in
elect
rical
a
nd
elect
ron
i
c en
gin
eerin
g, Rit
s
u
m
e
i
k
an
Univ
e
rs
it
y,
Ky
o
t
o
,
J
a
pan
i
n
M
a
r
c
h
2
0
0
3
.
I
n
J
u
l
y
2
0
0
7
h
e
p
u
s
u
e
h
i
s
s
t
u
d
y
a
t
S
c
h
o
o
l
o
f
E
l
e
ctri
cal,
Co
m
p
u
t
er
a
nd
Tel
e
co
m
m
unicati
o
n
s
E
ngin
eerin
g
(S
E
C
TE),
U
n
i
versi
t
y
o
f
W
o
llo
n
g
on
g,
A
ustral
ia
a
nd
completed
hi
s
MS
c.
i
n
Fe
b
r
uary
2
01
0.
I
n
Decem
ber
th
e
sam
e
y
ear,
he
s
t
a
rte
d
his
P
h
D
stud
y
at
t
he
Universiti
Kebangsaan
M
alaysia
(UKM),
F
acul
t
y
of
E
ngi
ne
eri
n
g
an
d
Bui
l
t
E
n
v
i
ronm
ent
(
F
K
A
B
)
.
H
e
t
h
e
n
f
i
n
i
s
h
e
d
h
i
s
P
h
D
r
e
s
e
a
r
c
h
s
t
u
d
y
i
n
A
p
r
i
l
2
0
1
4
.
He
i
s
currently
a
s
eni
o
r
lectu
r
er
at
t
he
U
ni
versiti
M
a
lay
s
i
a
T
eren
ggan
u
(
U
M
T),
F
acu
lt
y
o
f
O
cean
E
n
g
in
eerin
g
Techn
o
lo
gy
a
nd
Inf
o
rm
at
ics
i
n
w
hi
ch
h
is
r
es
earch
i
nt
erests
a
re
i
n
energ
y
s
to
ra
ge
a
ppl
icat
io
n
f
o
r
ren
e
w
a
bl
e
energ
y
i
nteg
rati
o
n
and
sm
a
rt
m
eter d
evelo
p
m
e
n
t
fo
r
energ
y eff
i
c
ie
ncy
st
udies
.
Evaluation Warning : The document was created with Spire.PDF for Python.