I
nte
rna
t
io
na
l J
o
urna
l o
f
P
o
wer
E
lect
ro
nics
a
nd
Driv
e
S
y
s
t
em
(
I
J
P
E
DS)
Vo
l.
1
7
,
No
.
3
,
Sep
tem
b
er
20
2
6
,
p
p
.
1
6
0
1
~
1
6
0
9
I
SS
N:
2
0
8
8
-
8
6
9
4
,
DOI
: 1
0
.
1
1
5
9
1
/ijp
ed
s
.
v
1
7
.
i
3
.
p
p
1
6
0
1
-
1
6
0
9
1601
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
p
e
d
s
.
ia
esco
r
e.
co
m
O
ptimi
za
tion o
f
E
V batte
ry
charg
in
g
f
o
r t
emp
erature
contro
l
R.
J
.
Vij
a
y
a
Sa
ra
s
wa
t
hi
1
,
K
r
is
hn
a
k
um
a
r
V
eng
a
da
k
rish
na
n
2
,
Va
s
a
n P
ra
bh
u
Vee
ra
m
a
ni
3
,
S
.
K
a
m
a
l
a
kk
a
nn
a
n
4
1
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
a
n
d
El
e
c
t
r
o
n
i
c
s
E
n
g
i
n
e
e
r
i
n
g
,
P
a
n
i
m
a
l
a
r
E
n
g
i
n
e
e
r
i
n
g
C
o
l
l
e
g
e
,
C
h
e
n
n
a
i
,
I
n
d
i
a
2
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
a
n
d
El
e
c
t
r
o
n
i
c
s
E
n
g
i
n
e
e
r
i
n
g
,
S
t
.
J
o
s
e
p
h
's
C
o
l
l
e
g
e
o
f
E
n
g
i
n
e
e
r
i
n
g
,
C
h
e
n
n
a
i
,
I
n
d
i
a
3
S
u
b
j
e
c
t
M
a
t
t
e
r
E
x
p
e
r
t
,
L&
T
E
d
u
Te
c
h
,
C
h
e
n
n
a
i
,
I
n
d
i
a
4
D
e
p
a
r
t
me
n
t
o
f
El
e
c
t
r
i
c
a
l
a
n
d
El
e
c
t
r
o
n
i
c
s
E
n
g
i
n
e
e
r
i
n
g
,
S
.
A
.
E
n
g
i
n
e
e
r
i
n
g
C
o
l
l
e
g
e
,
C
h
e
n
n
a
i
,
I
n
d
i
a
Art
icle
I
nfo
AB
S
T
RAC
T
A
r
ticle
his
to
r
y:
R
ec
eiv
ed
Sep
6
,
2
0
2
5
R
ev
is
ed
J
u
l 6
,
2
0
2
6
Acc
ep
ted
J
u
l 2
1
,
2
0
2
6
El
e
c
tri
c
v
e
h
icle
s
(EVs)
o
ffe
r
a
s
u
sta
in
a
b
le
m
o
d
e
o
f
tran
sp
o
rtati
o
n
;
h
o
we
v
e
r,
e
x
c
e
ss
iv
e
b
a
tt
e
ry
tem
p
e
ra
tu
re
rise
d
u
rin
g
c
h
a
rg
i
n
g
d
e
g
ra
d
e
s
p
e
rfo
rm
a
n
c
e
,
li
m
it
s
li
fe
sp
a
n
,
a
n
d
a
ffe
c
ts
th
e
s
a
fe
o
p
e
ra
ti
o
n
o
f
p
o
we
r
c
o
n
v
e
rter
s
a
n
d
EV
d
riv
e
s
y
ste
m
s.
To
a
d
d
re
ss
th
is
p
r
o
b
lem
,
a
b
a
c
k
p
r
o
p
a
g
a
ti
o
n
n
e
u
ra
l
n
e
two
r
k
(BP
NN
)
b
a
se
d
tem
p
e
ra
tu
re
p
re
d
i
c
ti
o
n
m
o
d
e
l
is
in
teg
ra
te
d
with
f
o
u
r
n
a
tu
re
-
in
sp
ired
o
p
ti
m
iza
ti
o
n
tec
h
n
iq
u
e
s
(NIO
Ts)
:
wh
a
le
o
p
ti
m
iza
ti
o
n
a
lg
o
rit
h
m
(W
OA
),
m
o
th
flam
e
o
p
ti
m
iza
ti
o
n
(M
F
O)
,
m
o
d
ifi
e
d
p
a
rti
c
l
e
sw
a
rm
o
p
ti
m
iza
ti
o
n
(M
P
S
O),
a
n
d
g
re
y
wo
lf
o
p
ti
m
iza
ti
o
n
(G
WO)
,
to
o
p
ti
m
ize
m
u
lt
i
-
sta
g
e
c
h
a
rg
i
n
g
c
u
rre
n
t
p
r
o
f
il
e
s.
Am
o
n
g
t
h
e
e
v
a
lu
a
ted
m
e
th
o
d
s,
WOA
a
c
h
iev
e
s
th
e
b
e
st
p
e
rfo
rm
a
n
c
e
,
re
d
u
c
in
g
c
h
a
rg
in
g
ti
m
e
b
y
a
p
p
r
o
x
ima
tely
1
0
%
(1
1
4
0
0
s
to
1
0
3
0
0
s)
a
n
d
a
v
e
ra
g
e
tem
p
e
ra
tu
re
rise
b
y
n
e
a
rly
5
0
%
(3
.
9
°
C
to
1
.
9
°
C)
c
o
m
p
a
re
d
to
th
e
c
o
n
v
e
n
ti
o
n
a
l
c
o
n
sta
n
t
c
u
rre
n
t
–
c
o
n
sta
n
t
v
o
lt
a
g
e
(CC
-
CV)
stra
teg
y
.
Th
e
o
p
ti
m
ize
d
c
h
a
rg
in
g
c
u
rre
n
ts
d
irec
tl
y
su
p
p
o
rt
imp
ro
v
e
d
DC
-
DC
c
o
n
v
e
rter
o
p
e
ra
ti
o
n
a
n
d
sta
b
le
EV
d
riv
e
p
e
rfo
r
m
a
n
c
e
b
y
li
m
it
in
g
t
h
e
rm
a
l
stre
ss
a
n
d
c
u
r
r
e
n
t
tran
sie
n
ts.
Ov
e
ra
ll
,
a
c
c
u
ra
te
th
e
rm
a
l
-
a
wa
re
c
h
a
rg
in
g
e
n
h
a
n
c
e
s
c
h
a
rg
in
g
e
fficie
n
c
y
,
e
n
su
re
s
sa
fe
c
o
n
v
e
rte
r
o
p
e
ra
ti
o
n
,
a
n
d
c
o
n
tri
b
u
tes
to
re
l
iab
le
a
n
d
lo
n
g
-
li
fe
EV
b
a
tt
e
ry
a
n
d
d
ri
v
e
sy
ste
m
p
e
rfo
rm
a
n
c
e
.
K
ey
w
o
r
d
s
:
C
h
ar
g
e
s
to
r
ed
C
h
ar
g
in
g
ef
f
icien
cy
Dis
ch
ar
g
in
g
ca
p
ac
ity
T
em
p
er
atu
r
e
i
n
cr
ea
s
e
T
im
e
o
f
ch
a
r
g
in
g
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
:
R
.
J
.
Vijay
a
Sar
aswath
i
Dep
ar
tm
en
t o
f
E
lectr
ical
an
d
E
lectr
o
n
ics E
n
g
in
ee
r
i
n
g
,
Pan
i
m
alar
E
n
g
in
ee
r
in
g
C
o
lleg
e
C
h
en
n
ai,
I
n
d
ia
E
m
ail:
v
ijay
asar
aswath
i8
8
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
E
lectr
ic
v
eh
icles
(
E
Vs)
ar
e
em
er
g
in
g
as
a
d
o
m
in
a
n
t
s
o
lu
tio
n
f
o
r
clea
n
an
d
en
er
g
y
-
ef
f
icien
t
tr
an
s
p
o
r
tatio
n
,
with
lith
iu
m
-
io
n
b
atter
ies
f
o
r
m
in
g
th
e
b
ac
k
b
o
n
e
o
f
m
o
d
er
n
E
V
p
o
wer
elec
tr
o
n
ics,
co
n
v
er
te
r
s
,
an
d
elec
tr
ic
d
r
i
v
e
s
y
s
tem
s
.
B
at
ter
ies n
o
t o
n
ly
s
u
p
p
ly
p
r
o
p
u
ls
io
n
en
er
g
y
b
u
t a
ls
o
s
u
p
p
o
r
t a
u
x
iliar
y
lo
ad
s
ac
r
o
s
s
p
latf
o
r
m
s
r
an
g
in
g
f
r
o
m
two
-
wh
ee
ler
s
an
d
co
m
m
er
cial
f
le
ets
to
p
u
b
lic
tr
a
n
s
p
o
r
t
s
y
s
tem
s
.
Ho
wev
er
,
th
e
ch
ar
g
in
g
p
r
o
ce
s
s
r
em
ain
s
a
c
r
itical
b
o
ttlen
ec
k
,
as
t
h
er
m
al
r
is
e
d
u
r
in
g
ch
ar
g
in
g
ad
v
e
r
s
ely
af
f
ec
ts
co
n
v
er
ter
dut
y
cy
cles,
d
r
iv
e
r
eliab
ilit
y
,
an
d
lo
n
g
-
ter
m
b
atter
y
h
ea
lth
.
T
h
e
wid
ely
ad
o
p
ted
co
n
s
tan
t
cu
r
r
en
t
–
c
o
n
s
tan
t
v
o
ltag
e
(
C
C
-
C
V)
m
eth
o
d
[
1
]
,
th
o
u
g
h
s
im
p
le
a
n
d
r
o
b
u
s
t,
o
f
ten
r
esu
lts
in
h
ig
h
er
tem
p
er
at
u
r
e
r
is
e,
in
e
f
f
icien
t
cu
r
r
en
t r
e
g
u
latio
n
,
an
d
e
x
ten
d
ed
ch
ar
g
i
n
g
d
u
r
atio
n
,
th
er
eb
y
lim
itin
g
o
v
er
all
E
V
p
e
r
f
o
r
m
an
ce
.
T
o
o
v
e
r
co
m
e
t
h
ese
lim
itatio
n
s
,
s
ev
er
al
ad
v
a
n
ce
d
c
h
ar
g
in
g
s
tr
ateg
ies
h
av
e
b
ee
n
r
e
p
o
r
ted
in
th
e
liter
atu
r
e,
in
clu
d
i
n
g
PS
O
-
o
p
ti
m
ized
m
u
ltis
tep
ch
ar
g
in
g
[
2
]
,
ad
ap
tiv
e
p
u
ls
e
ch
ar
g
in
g
[
3
]
,
f
u
zz
y
-
l
o
g
ic
-
b
ase
d
co
n
tr
o
l
[
4
]
,
an
d
f
lex
ib
le
m
u
lti
-
s
tag
e
co
n
s
tan
t
cu
r
r
en
t
(
M
SC
C
)
m
eth
o
d
s
[
5
]
.
T
h
ese
a
p
p
r
o
ac
h
es
im
p
r
o
v
e
ch
ar
g
in
g
ef
f
icien
cy
an
d
th
er
m
al
b
eh
av
io
r
;
h
o
wev
e
r
,
th
ey
in
tr
o
d
u
ce
ch
allen
g
es
r
elate
d
to
o
p
tim
al
cu
r
r
en
t
s
elec
tio
n
,
co
m
p
u
tatio
n
al
b
u
r
d
en
,
a
n
d
i
n
teg
r
atio
n
with
r
e
al
-
tim
e
co
n
v
e
r
ter
a
n
d
d
r
iv
e
s
y
s
tem
s
.
Pre
d
ictiv
e
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.
1
7
,
No
.
3
,
Sep
tem
b
er
20
2
6
:
1601
-
1
6
0
9
1602
co
n
tr
o
l
tech
n
i
q
u
es
h
av
e
also
b
ee
n
ex
p
lo
r
ed
to
m
itig
ate
tem
p
er
atu
r
e
r
is
e
[
6
]
,
b
u
t
th
e
ir
im
p
lem
en
tatio
n
co
m
p
lex
ity
r
estricts
p
r
ac
tical
d
ep
lo
y
m
e
n
t.
I
n
co
n
tr
ast,
b
ac
k
p
r
o
p
ag
atio
n
n
e
u
r
al
n
etwo
r
k
s
(
B
PNN
s
)
h
av
e
d
em
o
n
s
t
r
ated
s
tr
o
n
g
ca
p
ab
ilit
y
in
m
o
d
elin
g
n
o
n
lin
ea
r
b
atter
y
th
er
m
al
d
y
n
am
ics
with
m
o
d
er
ate
co
m
p
u
tatio
n
al
ef
f
o
r
t
[
7
]
,
wh
ile
r
ec
en
t
s
tu
d
ies
h
ig
h
lig
h
t
th
e
b
en
ef
its
o
f
co
m
b
in
in
g
m
ac
h
i
n
e
lear
n
in
g
an
d
o
p
tim
izatio
n
f
o
r
im
p
r
o
v
e
d
E
V
b
atter
y
p
er
f
o
r
m
an
ce
[
8
]
.
Desp
ite
th
ese
ad
v
an
ce
s
,
a
c
lear
r
esear
ch
g
ap
ex
is
ts
in
th
e
f
o
r
m
o
f
s
y
s
tem
atic,
co
m
p
ar
ativ
e
in
v
esti
g
atio
n
s
o
f
n
atu
r
e
-
in
s
p
ir
ed
o
p
tim
izatio
n
tech
n
iq
u
es wi
th
d
ir
ec
t r
elev
an
ce
t
o
tem
p
er
at
u
r
e
-
awa
r
e
ch
a
r
g
in
g
an
d
co
n
v
er
ter
-
d
r
iv
e
s
y
s
tem
i
n
teg
r
atio
n
.
M
o
tiv
ated
b
y
th
is
g
ap
,
th
is
wo
r
k
p
r
o
p
o
s
es
a
u
n
if
ied
B
PNN
-
b
ased
p
r
ed
ictiv
e
c
h
ar
g
i
n
g
f
r
am
ewo
r
k
co
m
b
in
ed
with
m
u
ltip
le
n
a
tu
r
e
-
in
s
p
ir
ed
o
p
tim
izatio
n
tec
h
n
iq
u
es
(
NI
OT
s
)
,
in
clu
d
in
g
wh
ale
o
p
tim
izatio
n
alg
o
r
ith
m
(
W
OA)
,
m
o
th
f
lam
e
o
p
tim
izatio
n
(
MFO)
,
m
o
d
if
i
ed
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
MPSO
)
,
a
n
d
g
r
ey
wo
lf
o
p
tim
izatio
n
(
GW
O)
.
T
h
e
f
r
am
ewo
r
k
b
en
ch
m
ar
k
s
th
ese
m
eth
o
d
s
ag
ain
s
t
co
n
v
en
tio
n
al
C
C
-
C
V
ch
ar
g
in
g
to
i
d
en
tify
o
p
tim
al
ch
ar
g
in
g
c
u
r
r
en
ts
th
at
b
alan
ce
th
er
m
al
s
af
ety
,
ch
ar
g
in
g
e
f
f
icien
cy
,
a
n
d
o
p
er
atio
n
al
r
eliab
ilit
y
.
B
y
ex
p
licitly
lin
k
in
g
ac
cu
r
ate
s
tate
o
f
ch
ar
g
e
(
SOC
)
an
d
tem
p
er
atu
r
e
p
r
e
d
ictio
n
to
s
ta
b
le
co
n
v
er
ter
o
p
er
atio
n
an
d
ef
f
icien
t
E
V
d
r
iv
e
p
e
r
f
o
r
m
a
n
ce
,
th
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
co
n
t
r
ib
u
tes to
war
d
s
af
er
,
f
aster
,
an
d
m
o
r
e
s
u
s
tain
ab
le
elec
tr
ic
m
o
b
ilit
y
[
9
]
.
2.
M
E
T
H
O
DO
L
O
G
Y
I
M
P
L
E
M
E
N
T
E
D
T
h
e
o
u
tlin
e
o
f
t
h
e
s
u
g
g
ested
p
r
icin
g
m
eth
o
d
is
s
h
o
wn
in
Fig
u
r
e
1
.
Usi
n
g
d
ata
f
r
o
m
b
atter
y
ch
ar
g
in
g
,
a
B
PNN
is
tr
ain
ed
t
o
cr
ea
te
a
tem
p
er
atu
r
e
r
is
e
p
r
ed
ictio
n
m
o
d
el.
Usi
n
g
in
p
u
t
f
ac
t
o
r
s
lik
e
ch
ar
g
in
g
cu
r
r
en
t
(
I
)
an
d
SOC
,
th
e
m
o
d
el
p
r
ed
icts
an
in
cr
ea
s
e
in
b
atter
y
tem
p
e
r
a
tu
r
e.
T
h
e
B
PNN
-
b
ased
m
o
d
el
is
p
r
esen
ted
h
er
e
,
to
g
eth
er
with
in
f
o
r
m
atio
n
o
n
n
eu
r
al
n
etwo
r
k
ar
ch
itectu
r
e,
d
ata
g
ath
er
in
g
,
tr
ain
in
g
,
an
d
v
a
lid
atio
n
.
L
ater
p
ar
ts
p
r
esen
t a
co
m
p
ar
ativ
e
ex
a
m
in
atio
n
o
f
d
if
f
er
e
n
t N
I
OT
s
f
o
r
th
e
d
ef
in
ed
o
b
jectiv
e
f
u
n
ctio
n
.
Fig
u
r
e
1
.
An
o
u
tlin
e
o
f
th
e
p
r
o
p
o
s
ed
tech
n
iq
u
e
2
.
1
.
Desig
n a
nd
im
plem
ent
a
t
io
n o
f
t
he
B
P
NN
m
o
del
A
B
PNN
wa
s
em
p
lo
y
ed
to
estab
lis
h
th
e
r
elatio
n
s
h
ip
b
et
wee
n
b
atter
y
o
p
er
atin
g
co
n
d
itio
n
s
an
d
tem
p
er
atu
r
e
b
eh
av
io
r
d
u
r
in
g
c
h
ar
g
in
g
.
I
n
t
h
is
s
u
p
er
v
is
ed
lea
r
n
in
g
a
p
p
r
o
ac
h
,
th
e
n
etwo
r
k
l
ea
r
n
s
f
r
o
m
la
b
elled
in
p
u
t
–
o
u
tp
u
t d
ata
an
d
iter
ativ
e
ly
ad
ju
s
ts
its
in
ter
n
al
w
eig
h
ts
t
o
m
in
im
ize
p
r
ed
ictio
n
er
r
o
r
.
D
u
r
in
g
tr
ain
in
g
,
th
e
p
r
ed
icted
o
u
tp
u
t
is
co
m
p
a
r
ed
with
th
e
tar
g
et
v
alu
e,
an
d
th
e
r
esu
ltin
g
er
r
o
r
is
p
r
o
p
ag
ated
b
ac
k
war
d
t
h
r
o
u
g
h
th
e
n
etwo
r
k
to
u
p
d
ate
th
e
c
o
n
n
ec
tio
n
weig
h
ts
.
T
h
is
o
p
tim
izatio
n
p
r
o
ce
s
s
co
n
tin
u
es
o
v
e
r
m
u
lt
ip
le
tr
ain
in
g
cy
cles u
n
til th
e
p
r
e
d
ictio
n
ac
c
u
r
ac
y
r
ea
c
h
es a
s
atis
f
ac
to
r
y
lev
el
[
1
0
]
,
[
1
1
]
.
T
h
e
d
ev
elo
p
e
d
B
PNN
ar
ch
it
ec
tu
r
e
co
n
s
is
ts
o
f
an
in
p
u
t
l
ay
er
with
two
n
eu
r
o
n
s
,
a
h
id
d
en
lay
e
r
co
n
tain
in
g
s
ix
n
eu
r
o
n
s
,
an
d
a
s
in
g
le
o
u
tp
u
t
n
eu
r
o
n
.
C
h
ar
g
in
g
cu
r
r
e
n
t
(
I
)
an
d
b
atter
y
SOC
ar
e
s
elec
ted
as
th
e
in
p
u
t
v
a
r
iab
les,
wh
ile
b
atter
y
t
em
p
er
atu
r
e
r
is
e
s
er
v
es
as
th
e
o
u
tp
u
t v
ar
iab
le.
E
x
p
e
r
im
en
tal
d
ata
wer
e
co
llected
u
s
in
g
a
FENI
X
1
8
6
5
0
lith
iu
m
-
io
n
ce
ll,
th
e
s
p
ec
if
icatio
n
s
o
f
wh
ich
ar
e
p
r
esen
ted
in
T
a
b
le
1
.
Prio
r
t
o
ea
ch
c
h
ar
g
in
g
test
,
th
e
b
atter
y
was
d
is
ch
ar
g
ed
u
n
til
its
o
p
en
-
cir
cu
it
v
o
ltag
e
r
ea
c
h
ed
th
e
p
r
escr
ib
ed
lo
wer
o
p
er
atin
g
lim
it.
T
o
elim
in
ate
th
e
in
f
lu
en
ce
o
f
am
b
ien
t
tem
p
er
atu
r
e
f
lu
ctu
atio
n
s
,
all
ex
p
er
im
en
ts
wer
e
co
n
d
u
cte
d
with
in
an
is
o
th
er
m
al
ch
am
b
er
m
ai
n
tain
ed
at
25
°C
.
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
Op
timiz
a
tio
n
o
f E
V
b
a
tter
y
ch
a
r
g
in
g
fo
r
temp
era
tu
r
e
co
n
tr
o
l
(
R
.
J.
V
ija
ya
S
a
r
a
s
w
a
th
i
)
1603
Fiv
e
ch
ar
g
in
g
r
ates
r
an
g
in
g
f
r
o
m
0
.
6
C
to
1
.
0
C
,
with
in
cr
em
en
ts
o
f
0
.
1
C
,
wer
e
co
n
s
i
d
er
ed
f
o
r
d
ataset
g
en
er
atio
n
as
g
iv
e
n
in
T
ab
le
2
.
T
h
r
o
u
g
h
o
u
t
th
e
co
n
s
tan
t
-
cu
r
r
en
t
c
h
ar
g
in
g
s
tag
e,
t
h
e
b
atter
y
s
u
r
f
ac
e
tem
p
er
atu
r
e
was
r
ec
o
r
d
ed
at
two
-
m
in
u
te
in
ter
v
a
ls
.
A
to
tal
o
f
4
0
0
d
ata
s
am
p
les
wer
e
o
b
tain
ed
f
r
o
m
t
h
e
ex
p
er
im
en
ts
,
o
f
wh
ich
3
3
5
s
am
p
les
wer
e
u
s
ed
f
o
r
n
etwo
r
k
tr
ain
in
g
,
an
d
3
5
s
am
p
les
wer
e
r
eser
v
ed
f
o
r
v
alid
atio
n
as g
iv
en
in
T
ab
le
3
.
Sin
ce
th
e
ch
ar
g
in
g
d
u
r
atio
n
v
ar
ies with
ch
ar
g
in
g
cu
r
r
e
n
t,
th
e
co
llecte
d
d
atasets
r
ep
r
esen
t
d
if
f
er
en
t
ch
ar
g
in
g
p
r
o
f
iles
.
Mo
d
el
p
er
f
o
r
m
a
n
ce
w
as
ev
alu
ated
u
s
in
g
t
h
e
m
ea
n
s
q
u
ar
ed
er
r
o
r
(
MSE
)
cr
iter
io
n
.
T
h
e
c
o
m
p
ar
is
o
n
b
e
twee
n
m
ea
s
u
r
ed
an
d
p
r
ed
icte
d
tem
p
er
atu
r
e
v
alu
es
is
illu
s
t
r
ated
in
Fig
u
r
e
2
,
wh
er
e
th
e
m
ax
im
u
m
p
r
e
d
ictio
n
d
ev
iat
io
n
r
em
ain
ed
with
in
ap
p
r
o
x
im
ately
0
.
0
7
–
0
.
0
8
°C
,
in
d
icatin
g
s
atis
f
ac
to
r
y
m
o
d
ellin
g
ac
c
u
r
ac
y
.
T
ab
le
1.
Sp
ec
if
icatio
n
s
o
f
Fen
ix
-
AR
B
-
L
1
8
-
2
6
0
0
B
a
t
t
e
r
y
m
o
d
e
l
F
e
n
i
x
1
8
6
5
0
A
R
B
-
L
1
8
-
2
6
0
0
mA
h
C
a
p
a
c
i
t
y
2
6
0
0
mA
h
N
o
mi
n
a
l
v
o
l
t
a
g
e
3
.
6
V
C
u
t
-
o
f
f
v
o
l
t
a
g
e
2
.
6
V
C
h
a
r
g
i
n
g
c
u
r
r
e
n
t
1
A
(
M
a
x
i
m
u
m
2
A
)
D
i
me
n
si
o
n
s
6
9
×
1
8
.
6
mm
W
e
i
g
h
t
5
0
g
R
e
c
o
mm
e
n
d
e
d
c
h
a
r
g
i
n
g
t
e
mp
e
r
a
t
u
r
e
0
–
4
5
°
C
R
e
c
o
mm
e
n
d
e
d
d
i
sc
h
a
r
g
i
n
g
t
e
mp
e
r
a
t
u
r
e
-
20
–
6
0
°
C
T
ab
le
2
.
Nu
m
b
er
o
f
tr
ain
in
g
d
atasets
u
s
ed
f
o
r
th
e
B
PNN
m
o
d
el
T
ab
le
3
.
Nu
m
b
er
o
f
v
alid
atin
g
d
atasets
u
s
ed
f
o
r
th
e
B
PNN
m
o
d
el
C
-
r
a
t
e
N
u
mb
e
r
o
f
t
r
a
i
n
i
n
g
d
a
t
a
se
t
s
1
C
70
0
.
9
C
76
0
.
8
C
78
0
.
7
C
68
0
.
6
C
73
C
-
r
a
t
e
N
u
mb
e
r
o
f
v
a
l
i
d
a
t
i
o
n
d
a
t
a
s
e
t
s
1
C
7
0
.
9
C
7
0
.
8
C
7
0
.
7
C
7
0
.
6
C
7
Fig
u
r
e
2
.
R
esu
lts
o
f
th
e
B
PNN
m
o
d
el
3.
NATUR
E
-
I
N
SPIR
E
D
O
P
T
I
M
I
Z
AT
I
O
N
T
E
CH
N
I
Q
UE
S
(
NIOT)
T
h
e
NI
OT
s
h
av
e
e
m
er
g
ed
a
s
ef
f
ec
tiv
e
ap
p
r
o
ac
h
es
f
o
r
a
d
d
r
ess
in
g
co
m
p
lex
o
p
tim
izatio
n
task
s
b
ec
au
s
e
o
f
th
eir
ca
p
ab
ilit
y
t
o
ex
p
l
o
r
e
ex
te
n
s
iv
e
s
o
lu
tio
n
s
p
ac
es
wh
ile
ad
ap
tin
g
to
d
y
n
am
ic
o
p
er
atin
g
co
n
d
itio
n
s
.
I
n
th
e
p
r
esen
t
s
tu
d
y
,
t
h
ese
o
p
tim
izatio
n
tech
n
i
q
u
es
wer
e
u
tili
ze
d
to
id
e
n
tify
a
n
o
p
tim
al
ch
ar
g
in
g
cu
r
r
en
t
p
r
o
f
ile
f
o
r
lith
iu
m
-
i
o
n
b
atter
ies
with
th
e
d
u
al
o
b
jectiv
e
o
f
en
h
an
cin
g
ch
ar
g
in
g
ef
f
icien
cy
a
n
d
m
in
im
izin
g
b
atter
y
tem
p
er
at
u
r
e
r
is
e.
T
o
ac
co
m
p
lis
h
th
is
,
an
o
b
jectiv
e
f
u
n
ctio
n
was
d
ev
elo
p
e
d
b
y
in
co
r
p
o
r
atin
g
b
o
t
h
th
e
ch
a
n
g
e
in
s
tate
o
f
c
h
ar
g
e
(
Δ
SOC
)
an
d
th
e
ass
o
ciate
d
in
cr
ea
s
e
in
b
atter
y
tem
p
e
r
atu
r
e
(
Δ
T
)
.
A
weig
h
tin
g
p
a
r
am
ete
r
,
α
,
was
in
tr
o
d
u
ce
d
to
b
alan
ce
th
e
c
o
n
tr
ib
u
tio
n
o
f
t
h
ese
two
p
er
f
o
r
m
a
n
ce
m
ea
s
u
r
es
ac
co
r
d
in
g
to
t
h
e
o
p
tim
izatio
n
r
e
q
u
ir
em
e
n
ts
.
T
h
e
o
b
jectiv
e
f
u
n
ctio
n
ad
o
p
te
d
in
th
is
s
tu
d
y
is
r
ep
r
esen
ted
as
(
1
)
.
{
(
1
∑
(
1
−
−
−
)
=
1
)
+
(
1
−
)
1
∑
(
|
−
|
)
=
1
}
(
1
)
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.
1
7
,
No
.
3
,
Sep
tem
b
er
20
2
6
:
1601
-
1
6
0
9
1604
I
n
th
is
f
o
r
m
u
latio
n
,
α
r
ep
r
esen
ts
th
e
weig
h
tin
g
f
ac
to
r
ass
ig
n
ed
t
o
th
e
SOC
im
p
r
o
v
em
en
t
co
m
p
o
n
en
t
o
f
th
e
o
b
jectiv
e
f
u
n
ctio
n
.
T
h
e
f
ir
s
t
ter
m
q
u
an
tifie
s
th
e
m
ea
n
in
cr
ea
s
e
in
SOC
o
b
tain
ed
f
r
o
m
th
e
s
elec
ted
SO
C
m
ea
s
u
r
em
en
t p
o
in
ts
,
wh
e
r
ea
s
th
e
s
ec
o
n
d
ter
m
esti
m
ates
th
e
av
er
ag
e
v
ar
iatio
n
in
b
atter
y
te
m
p
er
atu
r
e
b
ased
o
n
th
e
r
ec
o
r
d
e
d
th
er
m
al
d
ata.
T
h
e
v
ar
iab
les
n
an
d
m
d
e
n
o
t
e
th
e
to
tal
n
u
m
b
er
o
f
SOC
m
ea
s
u
r
em
en
ts
an
d
tem
p
er
atu
r
e
o
b
s
er
v
atio
n
s
,
r
esp
ec
tiv
ely
,
in
clu
d
ed
i
n
th
e
o
p
ti
m
izatio
n
p
r
o
ce
d
u
r
e.
B
y
in
teg
r
atin
g
b
o
t
h
ch
ar
g
in
g
ef
f
icien
cy
an
d
t
h
er
m
al
ch
ar
ac
ter
is
tics
in
to
a
u
n
if
ied
o
b
jecti
v
e
f
u
n
ctio
n
,
th
e
p
r
o
p
o
s
ed
o
p
t
im
izatio
n
ap
p
r
o
ac
h
ac
h
iev
es
an
ef
f
ec
tiv
e
b
alan
ce
b
etwe
en
m
ax
im
izin
g
b
atter
y
ch
ar
g
in
g
p
er
f
o
r
m
an
c
e
an
d
li
m
itin
g
u
n
d
esira
b
le
tem
p
er
atu
r
e
elev
atio
n
.
3
.1
.
Wha
le
o
pti
m
iza
t
io
n a
l
g
o
rit
hm
T
h
e
W
OA
s
im
u
lates
th
e
h
u
n
tin
g
s
tr
ateg
y
o
f
h
u
m
p
b
ac
k
w
h
ales
b
y
in
teg
r
atin
g
p
r
e
y
en
c
ir
clem
en
t,
s
p
ir
al
u
p
d
atin
g
,
an
d
s
to
ch
asti
c
ex
p
lo
r
atio
n
,
th
e
r
eb
y
ac
h
ie
v
in
g
an
ef
f
ec
tiv
e
b
alan
ce
b
etwe
en
ex
p
lo
r
atio
n
an
d
ex
p
lo
itatio
n
d
u
r
in
g
o
p
tim
izati
o
n
[
1
2
]
-
[
1
5
]
.
W
h
ales m
o
v
e
ar
o
u
n
d
th
e
b
est s
o
lu
tio
n
u
s
in
g
a
d
ap
tiv
e
co
ef
f
i
cien
ts
,
s
h
r
in
k
th
eir
s
ea
r
ch
r
ad
i
u
s
d
u
r
i
n
g
ex
p
lo
itatio
n
,
o
r
f
o
llo
w
a
s
p
ir
al
p
ath
to
s
im
u
late
n
atu
r
al
h
elix
m
o
v
em
e
n
t.
A
5
0
%
p
r
o
b
a
b
ilit
y
d
ec
id
es
wh
eth
er
s
h
r
in
k
in
g
o
r
s
p
ir
al
ac
tio
n
s
ar
e
u
s
ed
.
Fo
r
ex
p
lo
r
atio
n
,
wh
ales
u
p
d
ate
th
eir
p
o
s
itio
n
s
r
elativ
e
to
r
an
d
o
m
ly
s
elec
ted
ag
en
ts
,
h
elp
in
g
t
h
em
escap
e
lo
ca
l
o
p
tim
a.
T
h
is
s
wi
tch
b
etwe
en
g
lo
b
al
s
ea
r
ch
an
d
lo
ca
l
r
ef
in
em
e
n
t e
n
ab
les W
OA
to
m
ain
tain
b
alan
ce
th
r
o
u
g
h
o
u
t o
p
tim
izatio
n
.
3
.
2
.
M
o
t
h
f
la
m
e
o
ptim
iza
t
io
n
T
h
e
MFO
alg
o
r
ith
m
in
itializes
m
o
th
s
as
ca
n
d
id
ate
s
o
lu
tio
n
s
an
d
ev
alu
ates
th
eir
f
itn
ess
to
d
eter
m
in
e
attr
ac
tio
n
s
tr
en
g
th
to
war
d
t
h
e
cu
r
r
en
t
b
est
s
o
lu
tio
n
(
f
lam
e)
[
1
6
]
–
[
1
9
]
.
Mo
th
s
th
en
u
p
d
ate
t
h
eir
p
o
s
itio
n
s
u
s
in
g
a
d
is
tan
ce
-
b
ased
attr
ac
tio
n
m
ec
h
an
is
m
with
r
a
n
d
o
m
n
ess
,
wh
ile
an
ad
d
itio
n
al
ex
p
l
o
r
atio
n
s
tep
e
n
s
u
r
es
d
iv
er
s
ity
an
d
p
r
ev
en
ts
p
r
em
at
u
r
e
c
o
n
v
er
g
en
ce
.
T
h
r
o
u
g
h
t
h
ese
r
ep
ea
ted
s
tep
s
,
MFO
ef
f
i
cien
tly
ex
p
l
o
r
es
th
e
s
ea
r
ch
s
p
ac
e
an
d
im
p
r
o
v
es th
e
q
u
ality
o
f
s
o
lu
tio
n
s
.
3
.
3
.
M
o
dified
pa
rt
icle
s
wa
rm
o
ptim
iz
a
t
io
n
T
h
e
MPSO
en
h
an
ce
s
class
ica
l
PS
O
b
y
ad
ap
tin
g
in
er
tia
weig
h
t,
co
n
tr
o
llin
g
p
ar
ticle
v
el
o
city
,
an
d
tu
n
in
g
p
ar
am
eter
s
d
y
n
am
icall
y
f
o
r
im
p
r
o
v
ed
c
o
n
v
er
g
en
ce
[
2
0
]
–
[
2
2
]
.
Par
ticles
u
p
d
ate
th
eir
p
o
s
itio
n
s
u
s
in
g
th
eir
p
er
s
o
n
al
b
est
an
d
g
lo
b
al
b
est
in
f
o
r
m
atio
n
,
w
h
ile
v
elo
c
ity
clam
p
in
g
en
s
u
r
es
s
tab
ilit
y
.
T
h
e
in
c
o
r
p
o
r
atio
n
o
f
ad
a
p
tiv
e
a
d
ju
s
tm
en
ts
an
d
lo
ca
l
s
ea
r
ch
h
elp
s
MPSO
m
a
in
tain
a
b
etter
e
x
p
lo
r
atio
n
–
ex
p
lo
itatio
n
b
ala
n
ce
,
r
ed
u
cin
g
s
tag
n
atio
n
a
n
d
im
p
r
o
v
in
g
o
p
tim
izatio
n
p
er
f
o
r
m
an
c
e.
3
.
4
.
M
o
dified
g
re
y
wo
lf
o
pti
m
iza
t
io
n
T
h
e
MG
W
O
alg
o
r
ith
m
s
tar
ts
b
y
r
an
k
in
g
wo
l
v
es
in
to
alp
h
a
,
b
eta,
d
elta,
a
n
d
o
m
e
g
a
ca
teg
o
r
ies
an
d
u
p
d
atin
g
p
o
s
itio
n
s
b
ased
o
n
th
eir
d
is
tan
ce
s
to
th
ese
lead
e
r
wo
lv
es
u
s
in
g
m
o
d
if
ied
co
e
f
f
icien
ts
[
2
3
]
–
[
2
5
]
.
W
o
lv
es
m
o
v
e
to
wa
r
d
t
h
e
n
e
ar
est
d
o
m
in
a
n
t
wo
lf
to
r
ef
in
e
s
ea
r
ch
d
ir
ec
tio
n
,
wh
ile
ad
d
e
d
lo
ca
l
s
e
ar
c
h
an
d
ad
ap
tiv
e
p
ar
am
eter
u
p
d
ates
en
h
an
ce
ex
p
l
o
r
atio
n
an
d
p
r
ev
e
n
t
en
tr
ap
m
en
t
in
lo
ca
l
o
p
tim
a
.
Mu
ltip
le
r
u
n
s
h
elp
d
eter
m
in
e
o
p
tim
ized
ch
ar
g
i
n
g
cu
r
r
e
n
ts
an
d
co
m
p
ar
e
r
esu
lts
with
tr
ad
itio
n
al
c
h
ar
g
in
g
a
p
p
r
o
ac
h
es
s
u
ch
as
C
C
-
C
V.
I
n
o
r
d
er
to
p
r
e
v
en
t
lo
ca
l
o
p
tim
a,
NI
OT
s
em
p
lo
y
r
an
d
o
m
p
ar
am
eter
s
,
wh
ich
r
esu
lts
in
s
o
lu
tio
n
u
n
p
r
e
d
ictab
ilit
y
.
Af
ter
5
0
r
u
n
s
o
f
1
0
0
iter
atio
n
s
,
th
e
a
v
er
ag
e
o
p
tim
ized
ch
ar
g
in
g
c
u
r
r
e
n
t
(
O
C
C
)
is
d
eter
m
in
ed
f
o
r
ea
ch
NI
OT
5
0
,
1
0
0
,
2
0
0
,
an
d
3
0
0
p
ar
ticle
co
u
n
ts
ar
e
u
s
ed
to
ca
lcu
late
f
in
al
OC
C
s
.
T
h
e
o
p
tim
izatio
n
o
u
tco
m
es a
r
e
also
b
e
n
ch
m
a
r
k
ed
u
s
in
g
th
e
t
r
ad
itio
n
al
C
C
-
C
V
m
eth
o
d
.
4.
CO
M
P
UT
AT
I
O
NAL P
AR
A
M
E
T
E
R
CO
NF
I
G
URA
T
I
O
N
AND
F
I
ND
I
NG
S
T
o
en
s
u
r
e
ef
f
ec
tiv
e
r
esu
lts
,
ea
ch
NI
OT
is
r
u
n
2
5
tim
es
with
1
0
0
iter
atio
n
s
,
an
d
th
e
a
v
er
a
g
e
OC
C
i
s
ca
lcu
lated
.
T
h
e
s
tu
d
y
also
co
m
p
ar
es
th
e
co
n
v
en
tio
n
al
C
C
-
C
V
m
eth
o
d
.
T
ab
le
4
s
h
o
ws
r
esu
lts
f
o
r
T
c
(
s
)
,
en
er
g
y
lo
s
s
(
J
)
,
a
n
d
C
S
(
Ah
)
.
T
ab
le
5
lis
ts
OC
C
s
f
o
r
ea
ch
c
ase.
MPSO
is
p
r
ef
er
r
ed
f
o
r
its
lo
west
T
c,
alig
n
in
g
with
th
e
s
tu
d
y
’
s
o
b
jectiv
e.
Af
ter
Py
th
o
n
-
b
ased
s
im
u
latio
n
,
r
ea
l
b
atter
y
test
s
ar
e
co
n
d
u
cted
,
a
n
d
ch
a
r
g
e
p
er
f
o
r
m
an
ce
m
etr
ics
(
C
PM)
a
r
e
ev
alu
ated
to
co
n
f
ir
m
OC
C
o
p
tim
ality
.
T
ab
le
4
.
Per
f
o
r
m
an
ce
p
ar
am
et
er
s
o
b
tain
ed
f
r
o
m
s
im
u
latio
n
Te
c
h
n
i
q
u
e
Ti
me
f
o
r
c
h
a
r
g
i
n
g
Tc
(
s)
C
h
a
r
g
i
n
g
s
t
o
r
a
g
e
C
S
(
A
h
)
Lo
ss
o
f
e
n
e
r
g
y
(
J)
W
O
A
9
,
9
5
0
3
.
4
0
5
3
5
6
6
.
7
9
M
F
O
9
,
7
2
0
3
.
3
2
0
2
8
6
0
.
2
4
M
P
S
O
9
,
8
0
0
3
.
3
6
9
2
9
6
0
.
0
3
G
W
O
9
,
9
0
9
3
.
3
9
2
3
0
8
8
.
4
3
0
.
6
C
C
C
-
CV
1
1
,
4
4
9
2
.
2
9
3
6
3
1
1
8
.
5
0
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
Op
timiz
a
tio
n
o
f E
V
b
a
tter
y
ch
a
r
g
in
g
fo
r
temp
era
tu
r
e
co
n
tr
o
l
(
R
.
J.
V
ija
ya
S
a
r
a
s
w
a
th
i
)
1605
T
ab
le
5
.
OC
C
o
b
tain
ed
u
s
in
g
d
if
f
er
en
t N
I
OT
s
Te
c
h
n
i
q
u
e
I1
I2
I3
I4
I5
C
u
t
-
o
f
f
(
V
)
W
O
A
1
.
2
3
2
0
.
8
0
2
0
.
3
1
2
2
0
.
2
0
0
5
0
.
1
2
0
2
3
.
6
M
F
O
1
.
1
8
0
0
.
7
3
2
0
.
3
7
2
5
0
.
2
5
7
0
0
.
1
3
8
5
3
.
6
M
P
S
O
1
.
1
6
5
0
.
7
2
0
0
.
3
8
0
9
0
.
2
6
2
8
0
.
1
1
0
2
3
.
6
G
W
O
1
.
1
9
3
0
.
7
3
6
0
.
3
7
0
6
0
.
2
8
2
9
0
.
1
3
5
2
3
.
6
0
.
6
C
C
C
-
CV
1
.
6
-
-
-
-
3
.
6
5.
E
XP
E
R
I
M
E
N
T
A
L
VE
R
I
F
I
CATI
O
N
T
o
en
a
b
le
p
r
ac
tical
v
alid
atio
n
,
a
r
ea
l
-
tim
e
m
o
n
ito
r
in
g
s
etu
p
as
s
h
o
wn
in
Fig
u
r
e
3
is
d
ev
el
o
p
ed
u
s
in
g
an
E
SP
3
2
-
b
ased
e
m
b
ed
d
ed
s
y
s
tem
.
A
lith
iu
m
-
io
n
1
8
6
5
0
b
at
ter
y
co
n
f
ig
u
r
atio
n
is
in
ter
f
ac
e
d
with
tem
p
er
atu
r
e
an
d
cu
r
r
en
t
s
en
s
o
r
s
to
m
ea
s
u
r
e
o
p
er
atin
g
co
n
d
itio
n
s
d
u
r
in
g
ch
a
r
g
in
g
.
Alth
o
u
g
h
th
e
p
r
o
p
o
s
ed
m
o
d
el
is
d
ev
elo
p
e
d
f
o
r
a
s
in
g
le
ce
ll
,
th
e
h
ar
d
war
e
s
etu
p
r
e
p
r
e
s
en
ts
a
m
u
lti
-
ce
ll
co
n
f
ig
u
r
a
tio
n
f
o
r
p
r
ac
tical
im
p
lem
en
tatio
n
.
T
h
e
E
SP
3
2
m
o
d
u
le
en
a
b
les
r
ea
l
-
tim
e
ac
q
u
is
itio
n
o
f
cu
r
r
en
t
an
d
v
o
ltag
e
d
ata,
wh
ich
ca
n
b
e
f
u
r
th
er
u
tili
ze
d
f
o
r
SOC
esti
m
atio
n
u
s
in
g
co
m
p
u
tatio
n
al
alg
o
r
ith
m
s
.
T
h
e
ex
p
er
im
en
tal
p
r
o
ce
d
u
r
e
co
m
m
en
ce
d
b
y
ap
p
ly
in
g
th
e
r
e
q
u
ir
ed
ch
ar
g
in
g
cu
r
r
en
t
lev
els
ac
co
r
d
in
g
to
th
e
ch
ar
g
in
g
cu
r
r
e
n
t
p
atter
n
s
lis
ted
in
T
ab
le
6
.
Su
b
s
eq
u
en
tly
,
th
e
b
atter
y
was
ch
ar
g
ed
,
a
n
d
th
e
co
r
r
esp
o
n
d
in
g
C
PMs
alo
n
g
w
ith
th
e
ch
ar
g
in
g
ch
ar
ac
ter
is
tics
wer
e
r
ec
o
r
d
ed
.
Fo
llo
win
g
a
r
esti
n
g
p
er
io
d
o
f
2
h
o
u
r
s
,
th
e
b
atter
y
was
d
is
ch
a
r
g
ed
at
a
co
n
s
tan
t
cu
r
r
e
n
t
r
at
e
o
f
0
.
2
C
u
n
til
th
e
o
p
en
-
cir
cu
it
v
o
ltag
e
(
OC
V)
r
ea
ch
ed
3
V.
T
h
e
d
is
ch
ar
g
e
ca
p
ac
ity
(
DC
)
was
th
en
m
ea
s
u
r
ed
,
an
d
th
e
c
h
ar
g
in
g
ef
f
icien
cy
(
C
E
)
was
d
eter
m
in
ed
b
ased
o
n
th
e
o
b
ta
in
ed
v
alu
es.
T
h
is
p
r
o
ce
d
u
r
e
was
r
ep
ea
ted
u
n
til
all
p
r
ed
ef
i
n
ed
ch
ar
g
in
g
cu
r
r
en
t
p
atter
n
s
h
ad
b
ee
n
ev
al
u
ated
.
T
h
e
ex
p
er
im
en
tal
f
i
n
d
in
g
s
p
r
esen
ted
in
T
a
b
le
6
i
n
clu
d
e
f
iv
e
c
h
ar
g
i
n
g
p
er
f
o
r
m
an
ce
m
etr
ics:
T
C
,
C
S,
DC
,
C
E
,
an
d
AT
I
.
T
ab
le
6
s
u
m
m
ar
izes
th
e
ex
p
er
im
en
tal
p
er
f
o
r
m
a
n
ce
m
etr
ics,
in
clu
d
in
g
to
tal
c
h
ar
g
i
n
g
t
im
e
(
T
C
)
,
ch
ar
g
in
g
ca
p
ac
ity
(
C
S),
d
is
ch
ar
g
e
h
o
ld
in
g
ca
p
ac
ity
(
D
HC
)
,
ch
ar
g
in
g
ef
f
icien
c
y
(
C
E
)
,
an
d
a
v
er
ag
e
tem
p
er
atu
r
e
in
cr
ea
s
e
(
AT
I
)
.
Fo
r
ea
ch
ch
a
r
g
in
g
tech
n
iq
u
e,
th
e
b
atter
y
is
ch
ar
g
ed
u
s
in
g
th
e
co
r
r
esp
o
n
d
in
g
cu
r
r
en
t
p
r
o
f
ile
an
d
s
u
b
s
eq
u
en
tly
s
u
b
jecte
d
to
a
co
n
tr
o
lled
d
is
ch
ar
g
e
p
r
o
ce
s
s
af
ter
a
d
esig
n
ated
r
est
p
er
io
d
.
T
h
e
d
is
ch
ar
g
e
h
o
ld
in
g
ca
p
ac
i
ty
an
d
c
h
ar
g
in
g
ef
f
icien
c
y
ar
e
th
en
ev
alu
ate
d
.
T
h
e
s
tr
o
n
g
ag
r
ee
m
en
t
b
etwe
en
s
im
u
latio
n
an
d
ex
p
e
r
im
en
tal
f
in
d
in
g
s
v
alid
ates
th
e
e
f
f
icac
y
o
f
th
e
s
u
g
g
ested
c
h
ar
g
in
g
p
r
o
ce
d
u
r
es,
an
d
th
is
co
n
s
is
ten
t p
r
o
ce
s
s
g
u
ar
an
tees
a
f
air
co
m
p
ar
is
o
n
.
Fig
u
r
e
3
.
T
h
e
s
etu
p
f
o
r
r
ea
l
-
ti
m
e
m
o
n
ito
r
i
n
g
T
ab
le
6
.
E
x
p
er
im
en
tal
r
esu
lts
Te
c
h
n
i
q
u
e
TC
(
s)
C
S
(
A
h
)
D
H
C
(
A
h
)
C
E
(
%)
A
TI
(
◦
C
)
W
O
A
1
0
,
3
2
8
3
.
3
8
9
2
3
.
3
5
6
3
9
9
.
0
2
9
2
1
.
9
0
2
8
M
F
O
1
0
,
8
8
5
3
.
2
9
0
0
3
.
2
5
0
0
9
8
.
7
8
4
1
2
.
1
2
2
2
M
P
S
O
1
0
,
6
5
0
3
.
2
9
8
6
3
.
1
8
9
9
9
6
.
7
0
4
6
2
.
2
8
7
0
G
W
O
1
0
,
7
5
0
3
.
3
9
2
4
3
.
3
1
3
8
9
7
.
6
8
3
0
2
.
2
0
6
3
CC
-
CV
1
1
,
4
4
9
3
.
4
4
5
3
3
.
3
9
7
8
9
8
.
6
2
7
0
3
.
9
2
5
1
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.
1
7
,
No
.
3
,
Sep
tem
b
er
20
2
6
:
1601
-
1
6
0
9
1606
Am
o
n
g
t
h
e
ev
al
u
ated
m
et
h
o
d
s
,
th
e
W
OA
-
b
ased
tech
n
iq
u
e
ex
h
ib
its
s
u
p
er
i
o
r
p
er
f
o
r
m
a
n
ce
with
a
ch
ar
g
in
g
tim
e
o
f
1
0
,
3
2
8
s
,
th
e
h
ig
h
est
C
E
o
f
9
9
.
0
3
%,
an
d
th
e
lo
west
tem
p
er
atu
r
e
r
is
e
o
f
1
.
9
0
°C
.
T
h
e
MFO
m
eth
o
d
s
h
o
ws
s
lig
h
tly
in
f
e
r
io
r
p
er
f
o
r
m
a
n
ce
,
with
a
lo
n
g
er
ch
ar
g
in
g
d
u
r
atio
n
(
1
0
,
8
8
5
s
)
,
h
ig
h
er
tem
p
er
atu
r
e
in
cr
ea
s
e
(
2
.
1
2
°C
)
,
an
d
r
ed
u
ce
d
ef
f
icien
cy
(
9
8
.
7
8
%).
T
h
e
M
PS
O
s
tr
ateg
y
ac
h
iev
es
f
aster
c
h
ar
g
in
g
(
1
0
,
6
5
0
s
)
b
u
t
s
u
f
f
er
s
f
r
o
m
lo
wer
e
f
f
icie
n
cy
(
9
6
.
7
0
%)
a
n
d
in
c
r
ea
s
ed
th
er
m
al
r
is
e
(
2
.
2
9
°C
)
,
in
d
icat
in
g
h
ig
h
e
r
b
atter
y
s
tr
ess
.
T
h
e
GW
O
-
b
ased
ap
p
r
o
ac
h
p
r
o
v
id
es
b
alan
ce
d
p
er
f
o
r
m
an
ce
with
m
o
d
er
ate
c
h
ar
g
i
n
g
tim
e
(
1
0
,
7
5
0
s
)
,
C
E
o
f
9
7
.
6
8
%,
an
d
AT
I
o
f
2
.
2
1
°C
,
b
u
t d
o
es n
o
t o
u
tp
e
r
f
o
r
m
W
OA
in
ter
m
s
o
f
ef
f
icien
cy
o
r
th
er
m
al
co
n
tr
o
l.
I
n
co
n
tr
ast,
th
e
co
n
v
en
tio
n
al
C
C
–
C
V
m
eth
o
d
r
ec
o
r
d
s
th
e
l
o
n
g
est
ch
ar
g
i
n
g
tim
e
(
1
1
,
4
4
9
s
)
an
d
th
e
h
ig
h
est
tem
p
er
atu
r
e
r
is
e
(
3
.
9
3
°C
)
,
h
ig
h
lig
h
tin
g
its
lim
itat
io
n
s
in
th
er
m
al
m
an
ag
em
e
n
t.
Ov
er
all,
wh
ile
all
NI
OT
-
b
ased
tech
n
iq
u
es
o
u
tp
e
r
f
o
r
m
C
C
–
C
V,
th
e
W
OA
ap
p
r
o
ac
h
o
f
f
e
r
s
th
e
b
est
tr
ad
e
-
o
f
f
b
etwe
en
ch
ar
g
in
g
s
p
ee
d
,
ef
f
icien
c
y
,
an
d
th
er
m
al
s
tab
ilit
y
,
m
ak
in
g
it
t
h
e
m
o
s
t
ef
f
ec
tiv
e
s
tr
ateg
y
f
o
r
b
atter
y
p
e
r
f
o
r
m
an
ce
en
h
an
ce
m
e
n
t.
Dir
ec
t
m
ea
s
u
r
em
en
t
o
f
en
er
g
y
lo
s
s
d
u
r
in
g
b
atter
y
ch
a
r
g
in
g
is
d
if
f
icu
lt;
h
en
ce
,
th
is
s
tu
d
y
u
s
es
ch
ar
g
in
g
T
I
as
th
e
e
v
alu
atio
n
m
etr
ic
f
o
r
l
o
s
s
o
f
en
er
g
y
.
As
s
h
o
wn
in
Fig
u
r
e
4
,
t
h
e
C
C
-
C
V
m
eth
o
d
d
is
p
lay
s
s
ig
n
if
ican
tly
h
ig
h
er
cu
m
u
lativ
e
T
I
,
in
d
icatin
g
g
r
ea
ter
en
e
r
g
y
lo
s
s
d
u
r
in
g
th
e
ch
a
r
g
in
g
p
r
o
c
ess
.
I
n
co
n
tr
ast,
th
e
p
r
o
p
o
s
ed
NI
OT
te
ch
n
iq
u
es
d
e
m
o
n
s
tr
ate
s
m
o
o
th
er
an
d
m
o
r
e
co
n
tr
o
lled
T
I
c
u
r
v
es
b
y
ef
f
ec
tiv
ely
b
alan
cin
g
T
C
an
d
L
o
s
s
o
f
E
n
e
r
g
y
.
T
h
is
h
i
g
h
lig
h
ts
th
e
im
p
r
o
v
ed
t
h
er
m
a
l
an
d
e
n
er
g
y
p
e
r
f
o
r
m
an
ce
ac
h
iev
ed
th
r
o
u
g
h
t
h
e
NI
OT
-
b
ased
ch
ar
g
in
g
s
tr
ateg
i
es.
Fig
u
r
e
4
.
T
I
f
o
r
th
e
ch
a
r
g
in
g
t
ec
h
n
iq
u
es
6.
AN
ASS
E
SS
M
E
NT
O
F
T
H
E
NIOT
s
US
E
D
T
h
is
s
tu
d
y
cr
itically
ev
alu
ate
s
th
e
f
o
u
r
C
PMs:
T
C
,
C
S,
C
E
,
an
d
AT
I
.
T
h
e
r
esu
lts
p
r
o
v
id
e
u
s
ef
u
l
g
u
id
an
ce
f
o
r
s
elec
tin
g
an
ap
p
r
o
p
r
iate
c
h
ar
g
in
g
m
eth
o
d
f
o
r
li
th
iu
m
-
io
n
b
atter
ies.
Sin
ce
ea
c
h
C
PM
is
b
ased
o
n
d
if
f
er
en
t
p
er
f
o
r
m
a
n
ce
c
r
iter
ia,
a
c
o
m
m
o
n
n
o
r
m
alize
d
ev
alu
a
tio
n
s
co
r
e
was
co
m
p
u
ted
b
y
a
s
s
ig
n
in
g
a
v
alu
e
o
f
1
to
th
e
b
est
-
p
er
f
o
r
m
in
g
r
esu
l
t
an
d
0
t
o
th
e
least
d
esira
b
le
r
esu
lt.
T
h
e
c
o
m
m
o
n
n
o
r
m
alize
d
ev
alu
atio
n
s
co
r
es
ar
e
p
r
esen
ted
in
T
ab
le
7
.
Fig
u
r
e
5
p
r
esen
ts
th
e
r
ad
ar
ch
ar
t
co
m
p
ar
is
o
n
o
f
th
e
n
o
r
m
ali
ze
d
ch
ar
g
in
g
p
e
r
f
o
r
m
an
ce
m
e
tr
ics
(
T
C
,
C
S,
C
E
,
an
d
AT
I
)
f
o
r
all
tech
n
iq
u
es.
T
h
e
W
OA
m
eth
o
d
e
x
h
ib
its
th
e
lar
g
est
en
cl
o
s
ed
ar
ea
,
in
d
icatin
g
s
u
p
er
io
r
o
v
er
all
p
er
f
o
r
m
a
n
ce
with
b
al
an
ce
d
ch
ar
g
in
g
s
p
ee
d
,
ef
f
icie
n
cy
,
an
d
th
er
m
al
c
o
n
tr
o
l.
GW
O
an
d
MFO
s
h
o
w
m
o
d
er
ate
p
er
f
o
r
m
a
n
ce
with
tr
ad
e
-
o
f
f
s
am
o
n
g
th
e
m
etr
ics,
w
h
ile
MPSO
d
em
o
n
s
tr
ates
wea
k
er
o
v
er
all
b
ala
n
ce
.
T
h
e
C
C
–
C
V
m
eth
o
d
attain
s
l
o
wer
n
o
r
m
alize
d
s
co
r
es,
h
ig
h
lig
h
tin
g
its
co
m
p
ar
ativ
ely
in
f
er
io
r
p
er
f
o
r
m
an
ce
ac
r
o
s
s
th
e
ev
alu
ated
C
PMs.
T
ab
le
7
.
T
a
b
le
6
'
s
n
o
r
m
alize
d
v
alu
es
Te
c
h
n
i
q
u
e
TC
(
s)
C
S
(
A
h
)
C
E
(
%)
A
TI
(
°
C)
To
t
a
l
r
a
t
i
n
g
W
O
A
1
.
0
0
0
0
0
.
6
3
8
7
1
.
0
0
0
0
1
.
0
0
0
0
3
.
6
3
8
7
M
F
O
0
.
4
9
6
9
0
.
0
0
0
0
0
.
9
0
1
7
0
.
1
0
8
4
1
.
5
0
7
M
P
S
O
0
.
2
8
7
3
0
.
0
8
4
0
0
.
0
6
9
8
0
.
1
9
0
0
0
.
6
3
1
1
G
W
O
0
.
3
7
6
4
1
.
0
0
0
0
0
.
4
6
1
5
0
.
1
5
0
0
1
.
9
8
7
9
CC
-
CV
0
.
0
0
0
0
0
.
8
8
9
2
0
.
0
0
0
0
0
.
0
0
0
0
0
.
8
8
9
2
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
Op
timiz
a
tio
n
o
f E
V
b
a
tter
y
ch
a
r
g
in
g
fo
r
temp
era
tu
r
e
co
n
tr
o
l
(
R
.
J.
V
ija
ya
S
a
r
a
s
w
a
th
i
)
1607
Fig
u
r
e
5
.
R
ad
ar
c
h
ar
t f
o
r
th
e
n
o
r
m
alize
d
v
alu
es
7.
CO
NCLU
SI
O
N
T
h
is
wo
r
k
s
u
cc
ess
f
u
lly
d
ev
e
lo
p
ed
a
n
d
v
alid
ated
a
th
er
m
al
-
awa
r
e
lith
iu
m
-
io
n
b
atter
y
ch
ar
g
in
g
s
tr
ateg
y
u
s
in
g
a
u
n
if
ie
d
b
ac
k
p
r
o
p
ag
atio
n
n
e
u
r
al
n
etwo
r
k
(
B
PNN)
an
d
n
atu
r
e
-
in
s
p
ir
ed
o
p
ti
m
izatio
n
tech
n
iq
u
e
(
NI
OT
)
f
r
am
ewo
r
k
.
B
y
ac
c
u
r
ately
p
r
e
d
ictin
g
b
atter
y
tem
p
er
a
tu
r
e
r
is
e
an
d
o
p
tim
izin
g
m
u
lti
-
s
tag
e
ch
ar
g
in
g
cu
r
r
en
t
p
r
o
f
iles
,
th
e
p
r
o
p
o
s
ed
ap
p
r
o
ac
h
im
p
r
o
v
es
c
h
ar
g
i
n
g
ef
f
icien
cy
wh
ile
m
ain
tain
in
g
th
er
m
al
s
af
ety
.
Qu
an
titativ
e
r
esu
lts
co
n
f
ir
m
s
ig
n
if
ican
t
p
er
f
o
r
m
an
ce
en
h
a
n
ce
m
en
t
o
v
er
t
h
e
co
n
v
en
tio
n
al
C
C
–
C
V
m
eth
o
d
.
T
h
e
wh
ale
o
p
tim
izatio
n
alg
o
r
ith
m
(
W
OA)
ac
h
iev
ed
ap
p
r
o
x
im
ately
a
1
0
%
r
e
d
u
ctio
n
in
ch
ar
g
in
g
tim
e
an
d
n
ea
r
ly
5
0
%
r
ed
u
ctio
n
in
av
er
a
g
e
tem
p
er
atu
r
e
r
is
e,
wh
ile
m
ain
tain
in
g
h
ig
h
c
h
ar
g
e
s
to
r
ag
e
a
n
d
ef
f
icien
cy
.
T
h
e
clo
s
e
ag
r
ee
m
en
t
b
etwe
en
s
im
u
latio
n
an
d
ex
p
er
im
e
n
tal
r
es
u
lts
d
em
o
n
s
tr
ates
th
e
r
o
b
u
s
tn
es
s
an
d
r
eliab
ilit
y
o
f
th
e
B
PNN
-
b
ased
th
er
m
al
p
r
ed
ictio
n
m
o
d
el
u
n
d
er
p
r
ac
tical
o
p
er
atin
g
co
n
d
itio
n
s
.
Alth
o
u
g
h
MFO,
MPSO,
an
d
GW
O
al
s
o
im
p
r
o
v
ed
ch
ar
g
in
g
p
er
f
o
r
m
an
ce
co
m
p
ar
ed
to
C
C
–
C
V,
W
OA
co
n
s
is
ten
tly
d
eliv
er
ed
th
e
b
est
b
alan
ce
b
etwe
en
s
p
ee
d
,
th
er
m
al
co
n
tr
o
l,
a
n
d
s
tab
ilit
y
.
Fro
m
a
p
o
wer
elec
tr
o
n
ics
an
d
d
r
iv
es
p
er
s
p
ec
tiv
e,
t
h
e
o
p
tim
ized
ch
ar
g
in
g
cu
r
r
en
ts
ef
f
ec
ti
v
ely
lim
it
th
er
m
al
s
tr
ess
an
d
cu
r
r
en
t
tr
an
s
ien
ts
,
en
s
u
r
in
g
s
af
e
DC
–
DC
co
n
v
er
ter
o
p
er
atio
n
an
d
r
eliab
le
E
V
d
r
iv
e
p
er
f
o
r
m
an
ce
.
R
ed
u
ce
d
tem
p
e
r
atu
r
e
r
is
e
also
co
n
tr
ib
u
tes
to
im
p
r
o
v
e
d
b
atter
y
life
s
p
an
a
n
d
en
h
an
ce
d
o
v
e
r
all
s
y
s
tem
r
eliab
ilit
y
.
Fu
tu
r
e
r
esear
ch
will
f
o
cu
s
o
n
h
ar
d
war
e
-
lev
el
v
alid
atio
n
,
in
teg
r
atio
n
o
f
th
e
p
r
o
p
o
s
ed
ch
ar
g
in
g
s
tr
ateg
y
with
m
o
to
r
d
r
iv
e
o
p
er
atin
g
cy
cles,
an
d
th
e
d
ev
elo
p
m
en
t
o
f
h
y
b
r
id
m
ac
h
in
e
lear
n
in
g
–
NI
OT
f
r
am
ewo
r
k
s
f
o
r
r
ea
l
-
tim
e
b
atte
r
y
m
an
a
g
em
en
t in
elec
tr
ic
v
eh
icles.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
e
au
th
o
r
s
co
n
f
ir
m
th
at
th
e
r
esear
ch
was c
ar
r
ied
o
u
t i
n
d
ep
e
n
d
en
tly
with
o
u
t f
in
an
cial
i
n
f
lu
en
ce
.
AUTHO
R
CO
NT
RI
B
UT
I
O
NS ST
A
T
E
M
E
N
T
T
h
is
jo
u
r
n
al
u
s
es
th
e
C
o
n
tr
ib
u
to
r
R
o
les
T
ax
o
n
o
m
y
(
C
R
ed
iT)
to
r
ec
o
g
n
ize
in
d
iv
id
u
al
au
th
o
r
co
n
tr
ib
u
tio
n
s
,
r
ed
u
ce
au
th
o
r
s
h
ip
d
is
p
u
tes,
an
d
f
ac
ilit
ate
co
llab
o
r
atio
n
.
Na
m
e
o
f
Aut
ho
r
C
M
So
Va
Fo
I
R
D
O
E
Vi
Su
P
Fu
R
.
J
.
Vijay
a
Sar
aswath
i
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Kr
is
h
n
ak
u
m
ar
V
en
g
ad
ak
r
is
h
n
a
n
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Vasan
Pra
b
h
u
Vee
r
am
an
i
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
S
.
Kam
alak
k
an
n
a
n
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
C
:
C
o
n
c
e
p
t
u
a
l
i
z
a
t
i
o
n
M
:
M
e
t
h
o
d
o
l
o
g
y
So
:
So
f
t
w
a
r
e
Va
:
Va
l
i
d
a
t
i
o
n
Fo
:
Fo
r
mal
a
n
a
l
y
s
i
s
I
:
I
n
v
e
s
t
i
g
a
t
i
o
n
R
:
R
e
so
u
r
c
e
s
D
:
D
a
t
a
C
u
r
a
t
i
o
n
O
:
W
r
i
t
i
n
g
-
O
r
i
g
i
n
a
l
D
r
a
f
t
E
:
W
r
i
t
i
n
g
-
R
e
v
i
e
w
&
E
d
i
t
i
n
g
Vi
:
Vi
su
a
l
i
z
a
t
i
o
n
Su
:
Su
p
e
r
v
i
s
i
o
n
P
:
P
r
o
j
e
c
t
a
d
mi
n
i
st
r
a
t
i
o
n
Fu
:
Fu
n
d
i
n
g
a
c
q
u
i
si
t
i
o
n
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.
1
7
,
No
.
3
,
Sep
tem
b
er
20
2
6
:
1601
-
1
6
0
9
1608
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
Au
th
o
r
s
s
tate
n
o
co
n
f
lict o
f
in
t
er
est.
DATA AV
AI
L
AB
I
L
I
T
Y
R
aw
d
ata
is
n
o
t p
u
b
licly
av
ail
ab
le
d
u
e
to
p
r
iv
ac
y
o
r
in
s
titu
tio
n
al
r
estrictio
n
s
.
RE
F
E
R
E
NC
E
S
[
1
]
G
.
J.
C
h
e
n
a
n
d
W
.
H
.
C
h
u
n
g
,
“
E
v
a
l
u
a
t
i
o
n
o
f
c
h
a
r
g
i
n
g
m
e
t
h
o
d
s
f
o
r
l
i
t
h
i
u
m
-
i
o
n
b
a
t
t
e
r
i
e
s
,”
El
e
c
t
r
o
n
i
c
s
(
S
w
i
t
z
e
rl
a
n
d
)
,
v
o
l
.
1
2
,
n
o
.
1
9
,
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
e
l
e
c
t
r
o
n
i
c
s
1
2
1
9
4
0
9
5
.
[
2
]
S
.
C
.
W
a
n
g
a
n
d
Y
.
H
.
L
i
u
,
“
A
P
S
O
-
b
a
s
e
d
f
u
z
z
y
-
c
o
n
t
r
o
l
l
e
d
s
e
a
r
c
h
i
n
g
f
o
r
t
h
e
o
p
t
i
ma
l
c
h
a
r
g
e
p
a
t
t
e
r
n
o
f
Li
-
i
o
n
b
a
t
t
e
r
i
e
s
,
”
I
EEE
T
ra
n
s
a
c
t
i
o
n
s
o
n
I
n
d
u
st
r
i
a
l
E
l
e
c
t
r
o
n
i
c
s
,
v
o
l
.
6
2
,
n
o
.
5
,
p
p
.
2
9
8
3
–
2
9
9
3
,
2
0
1
5
,
d
o
i
:
1
0
.
1
1
0
9
/
TI
E.
2
0
1
4
.
2
3
6
3
0
4
9
.
[
3
]
J.
L
i
u
a
n
d
X
.
W
a
n
g
,
“
I
n
v
e
st
i
g
a
t
i
n
g
e
f
f
e
c
t
s
o
f
p
u
l
se
c
h
a
r
g
i
n
g
o
n
p
e
r
f
o
r
ma
n
c
e
o
f
Li
-
i
o
n
b
a
t
t
e
r
i
e
s
a
t
l
o
w
t
e
mp
e
r
a
t
u
r
e
,
”
J
o
u
r
n
a
l
o
f
Po
w
e
r
S
o
u
r
c
e
s
,
v
o
l
.
5
7
4
,
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
j
p
o
w
so
u
r
.
2
0
2
3
.
2
3
3
1
7
7
.
[
4
]
G
.
K
á
r
o
l
y
i
,
A
.
I
.
P
ó
z
n
a
,
K
.
M
.
H
a
n
g
o
s,
a
n
d
A
.
M
a
g
y
a
r
,
“
A
n
o
p
t
i
m
i
z
e
d
f
u
z
z
y
c
o
n
t
r
o
l
l
e
d
c
h
a
r
g
i
n
g
s
y
st
e
m
f
o
r
l
i
t
h
i
u
m
-
i
o
n
b
a
t
t
e
r
i
e
s
u
si
n
g
a
g
e
n
e
t
i
c
a
l
g
o
r
i
t
h
m
,”
En
e
rg
i
e
s
,
v
o
l
.
1
5
,
n
o
.
2
,
2
0
2
2
,
d
o
i
:
1
0
.
3
3
9
0
/
e
n
1
5
0
2
0
4
8
1
.
[
5
]
J.
Ti
a
n
,
S
.
Li
,
X
.
Li
u
,
D
.
Y
a
n
g
,
P
.
W
a
n
g
,
a
n
d
G
.
C
h
a
n
g
,
“
L
i
t
h
i
u
m
-
i
o
n
b
a
t
t
e
r
y
c
h
a
r
g
i
n
g
o
p
t
i
mi
z
a
t
i
o
n
b
a
s
e
d
o
n
e
l
e
c
t
r
i
c
a
l
,
t
h
e
r
mal
a
n
d
a
g
i
n
g
me
c
h
a
n
i
sm
m
o
d
e
l
s
,
”
E
n
e
r
g
y
Re
p
o
r
t
s
,
v
o
l
.
8
,
p
p
.
1
3
7
2
3
–
1
3
7
3
4
,
N
o
v
.
2
0
2
2
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
g
y
r
.
2
0
2
2
.
1
0
.
0
5
9
.
[
6
]
S
.
Jari
d
a
n
d
M
.
D
a
s,
“
A
n
e
l
e
c
t
r
o
-
t
h
e
r
mal
m
o
d
e
l
b
a
se
d
f
a
st
o
p
t
i
ma
l
c
h
a
r
g
i
n
g
st
r
a
t
e
g
y
f
o
r
L
i
-
i
o
n
b
a
t
t
e
r
i
e
s,”
AI
M
S
En
e
r
g
y
,
v
o
l
.
9
,
n
o
.
5
,
p
p
.
9
1
5
–
9
3
3
,
2
0
2
1
,
d
o
i
:
1
0
.
3
9
3
4
/
e
n
e
r
g
y
.
2
0
2
1
0
4
3
.
[
7
]
R
.
J.
V
.
S
a
r
a
sw
a
t
h
i
,
V
.
K
r
i
s
h
n
a
k
u
mar,
V
.
V
.
P
r
a
b
h
u
,
a
n
d
P
.
A
r
u
n
a
,
“
H
y
b
r
i
d
e
n
e
r
g
y
ma
n
a
g
e
me
n
t
s
t
r
a
t
e
g
y
f
o
r
u
l
t
r
a
-
c
a
p
a
c
i
t
o
r
/
b
a
t
t
e
r
y
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
c
o
n
si
d
e
r
i
n
g
b
a
t
t
e
r
y
d
e
g
r
a
d
a
t
i
o
n
,
”
El
e
c
t
ri
c
a
l
E
n
g
i
n
e
e
ri
n
g
,
v
o
l
.
1
0
7
,
n
o
.
1
,
p
p
.
7
9
5
–
8
0
8
,
Ja
n
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
0
7
/
s0
0
2
0
2
-
0
2
4
-
0
2
5
3
3
-
2
.
[
8
]
D
.
M
a
r
i
n
k
o
v
i
ć
,
G
.
D
e
z
s
ő
,
a
n
d
S
.
M
i
l
o
j
e
v
i
ć
,
“
A
p
p
l
i
c
a
t
i
o
n
o
f
ma
c
h
i
n
e
l
e
a
r
n
i
n
g
d
u
r
i
n
g
ma
i
n
t
e
n
a
n
c
e
a
n
d
e
x
p
l
o
i
t
a
t
i
o
n
o
f
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s,”
A
d
v
a
n
c
e
d
E
n
g
i
n
e
e
ri
n
g
L
e
t
t
e
rs
,
v
o
l
.
3
,
n
o
.
3
,
p
p
.
1
3
2
–
1
4
0
,
2
0
2
4
,
d
o
i
:
1
0
.
4
6
7
9
3
/
a
d
e
l
e
t
t
e
r
s.
2
0
2
4
.
3
.
3
.
5
.
[
9
]
T.
S
k
r
ú
c
a
n
ý
,
S
.
M
i
l
o
j
e
v
i
ć
,
Š
.
S
e
man
o
v
á
,
T.
Č
e
c
h
o
v
i
č
,
T.
F
i
g
l
u
s
,
a
n
d
F
.
S
y
n
á
k
,
“
T
h
e
e
n
e
r
g
y
e
f
f
i
c
i
e
n
c
y
o
f
e
l
e
c
t
r
i
c
e
n
e
r
g
y
a
s
a
t
r
a
c
t
i
o
n
u
s
e
d
i
n
t
r
a
n
s
p
o
r
t
,”
T
r
a
n
sp
o
r
t
t
e
c
h
n
i
c
a
n
d
t
e
c
h
n
o
l
o
g
y
,
v
o
l
.
1
4
,
n
o
.
2
,
p
p
.
9
–
1
4
,
D
e
c
.
2
0
1
8
,
d
o
i
:
1
0
.
2
4
7
8
/
t
t
t
-
2
0
1
8
-
0
0
0
5
.
[
1
0
]
Y
.
G
a
o
,
W
.
Ji
,
a
n
d
X
.
Zh
a
o
,
“
S
O
C
e
s
t
i
ma
t
i
o
n
o
f
e
-
c
e
l
l
c
o
m
b
i
n
i
n
g
B
P
n
e
u
r
a
l
n
e
t
w
o
r
k
a
n
d
E
K
F
a
l
g
o
r
i
t
h
m,
”
Pr
o
c
e
sses
,
v
o
l
.
1
0
,
n
o
.
9
,
p
.
1
7
2
1
,
A
u
g
.
2
0
2
2
,
d
o
i
:
1
0
.
3
3
9
0
/
p
r
1
0
0
9
1
7
2
1
.
[
1
1
]
S
.
Li
,
S
.
L
i
,
H
.
Zh
a
o
,
a
n
d
Y
.
A
n
,
“
D
e
si
g
n
a
n
d
i
mp
l
e
m
e
n
t
a
t
i
o
n
o
f
s
t
a
t
e
-
of
-
c
h
a
r
g
e
e
s
t
i
m
a
t
i
o
n
b
a
s
e
d
o
n
b
a
c
k
-
p
r
o
p
a
g
a
t
i
o
n
n
e
u
r
a
l
n
e
t
w
o
r
k
f
o
r
sm
a
r
t
u
n
i
n
t
e
r
r
u
p
t
i
b
l
e
p
o
w
e
r
sy
st
e
m,”
I
n
t
e
rn
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
D
i
st
r
i
b
u
t
e
d
S
e
n
s
o
r
N
e
t
w
o
rks
,
v
o
l
.
1
5
,
n
o
.
1
2
,
p
.
1
5
5
0
1
4
7
7
1
9
8
9
4
5
2
,
D
e
c
.
2
0
1
9
,
d
o
i
:
1
0
.
1
1
7
7
/
1
5
5
0
1
4
7
7
1
9
8
9
4
5
2
6
.
[
1
2
]
S
.
M
i
r
j
a
l
i
l
i
a
n
d
A
.
Le
w
i
s
,
“
Th
e
w
h
a
l
e
o
p
t
i
mi
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m
,”
Ad
v
a
n
c
e
s i
n
En
g
i
n
e
e
ri
n
g
S
o
f
t
w
a
re
,
v
o
l
.
9
5
,
p
p
.
5
1
–
6
7
,
M
a
y
2
0
1
6
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
a
d
v
e
n
g
so
f
t
.
2
0
1
6
.
0
1
.
0
0
8
.
[
1
3
]
J.
Ji
a
n
g
,
Q
.
W
a
n
g
,
a
n
d
C
.
L
i
,
“
R
e
s
e
a
r
c
h
o
n
S
O
C
e
s
t
i
m
a
t
i
o
n
me
t
h
o
d
o
f
p
o
w
e
r
b
a
t
t
e
r
y
b
a
s
e
d
o
n
W
O
A
-
B
P
n
e
u
r
a
l
n
e
t
w
o
r
k
,
”
i
n
2
0
2
2
I
EEE
5
t
h
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
El
e
c
t
ro
n
i
c
I
n
f
o
rm
a
t
i
o
n
a
n
d
C
o
m
m
u
n
i
c
a
t
i
o
n
T
e
c
h
n
o
l
o
g
y
(
I
C
EI
C
T
)
,
A
u
g
.
2
0
2
2
,
p
p
.
5
5
7
–
5
6
0
,
d
o
i
:
1
0
.
1
1
0
9
/
I
C
EI
C
T5
5
7
3
6
.
2
0
2
2
.
9
9
0
8
9
6
3
.
[
1
4
]
D
.
C
a
o
,
Y
.
X
u
,
Z
.
Y
a
n
g
,
H
.
D
o
n
g
,
a
n
d
X
.
Li
,
“
A
n
e
n
h
a
n
c
e
d
w
h
a
l
e
o
p
t
i
mi
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m
w
i
t
h
i
mp
r
o
v
e
d
d
y
n
a
mi
c
o
p
p
o
s
i
t
e
l
e
a
r
n
i
n
g
a
n
d
a
d
a
p
t
i
v
e
i
n
e
r
t
i
a
w
e
i
g
h
t
st
r
a
t
e
g
y
,
”
C
o
m
p
l
e
x
&
I
n
t
e
l
l
i
g
e
n
t
S
y
st
e
m
s
,
v
o
l
.
9
,
n
o
.
1
,
p
p
.
7
6
7
–
7
9
5
,
F
e
b
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
0
7
/
s
4
0
7
4
7
-
0
22
-
0
0
8
2
7
-
1.
[
1
5
]
C
.
L
i
e
t
a
l
.
,
“
Ev
o
l
v
i
n
g
t
h
e
w
h
a
l
e
o
p
t
i
mi
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m:
t
h
e
d
e
v
e
l
o
p
me
n
t
a
n
d
a
n
a
l
y
si
s
o
f
M
I
S
W
O
A
,
”
Bi
o
m
i
m
e
t
i
c
s
,
v
o
l
.
9
,
n
o
.
1
0
,
p
.
6
3
9
,
O
c
t
.
2
0
2
4
,
d
o
i
:
1
0
.
3
3
9
0
/
b
i
o
m
i
met
i
c
s
9
1
0
0
6
3
9
.
[
1
6
]
S
.
M
i
r
j
a
l
i
l
i
,
“
M
o
t
h
-
f
l
a
m
e
o
p
t
i
m
i
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m:
A
n
o
v
e
l
n
a
t
u
r
e
-
i
n
s
p
i
r
e
d
h
e
u
r
i
s
t
i
c
p
a
r
a
d
i
g
m,
”
K
n
o
w
l
e
d
g
e
-
Ba
s
e
d
S
y
s
t
e
m
s
,
v
o
l
.
8
9
,
p
p
.
2
2
8
–
2
4
9
,
N
o
v
.
2
0
1
5
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
k
n
o
s
y
s.
2
0
1
5
.
0
7
.
0
0
6
.
[
1
7
]
Y
.
W
a
n
g
,
G
.
Zh
a
o
,
C
.
Zh
o
u
,
M
.
Li
,
a
n
d
Z.
C
h
e
n
,
“
L
i
t
h
i
u
m
-
i
o
n
b
a
t
t
e
r
y
o
p
t
i
mal
c
h
a
r
g
i
n
g
u
s
i
n
g
m
o
t
h
-
f
l
a
me
o
p
t
i
m
i
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m
a
n
d
f
r
a
c
t
i
o
n
a
l
-
o
r
d
e
r
m
o
d
e
l
,
”
I
EEE
T
r
a
n
s
a
c
t
i
o
n
s
o
n
T
r
a
n
s
p
o
rt
a
t
i
o
n
El
e
c
t
ri
f
i
c
a
t
i
o
n
,
v
o
l
.
9
,
n
o
.
4
,
p
p
.
4
9
8
1
–
4
9
8
9
,
D
e
c
.
2
0
2
3
,
d
o
i
:
1
0
.
1
1
0
9
/
TT
E.
2
0
2
2
.
3
1
9
2
1
7
4
.
[
1
8
]
S
.
K
.
S
a
h
o
o
e
t
a
l
.
,
“
M
o
t
h
f
l
a
me
o
p
t
i
mi
z
a
t
i
o
n
:
t
h
e
o
r
y
,
mo
d
i
f
i
c
a
t
i
o
n
s,
h
y
b
r
i
d
i
z
a
t
i
o
n
s
,
a
n
d
a
p
p
l
i
c
a
t
i
o
n
s
,
”
Arc
h
i
v
e
s
o
f
C
o
m
p
u
t
a
t
i
o
n
a
l
Me
t
h
o
d
s
i
n
E
n
g
i
n
e
e
ri
n
g
,
v
o
l
.
3
0
,
n
o
.
1
,
p
p
.
3
9
1
–
4
2
6
,
Ja
n
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
0
7
/
s
1
1
8
3
1
-
0
2
2
-
0
9
8
0
1
-
z.
[
1
9
]
M
.
A
.
El
s
e
i
f
y
,
S
.
K
a
me
l
,
a
n
d
L
.
N
a
sr
a
t
,
“
A
n
i
m
p
r
o
v
e
d
m
o
t
h
f
l
a
me
o
p
t
i
mi
z
a
t
i
o
n
f
o
r
o
p
t
i
ma
l
D
G
a
n
d
b
a
t
t
e
r
y
e
n
e
r
g
y
st
o
r
a
g
e
a
l
l
o
c
a
t
i
o
n
i
n
d
i
st
r
i
b
u
t
i
o
n
s
y
s
t
e
ms
,
”
C
l
u
s
t
e
r
C
o
m
p
u
t
i
n
g
,
v
o
l
.
2
7
,
n
o
.
1
0
,
p
p
.
1
4
7
6
7
–
1
4
8
1
0
,
D
e
c
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
0
7
/
s1
0
5
8
6
-
024
-
0
4
6
6
8
-
0.
[
2
0
]
D
.
Ti
a
n
a
n
d
Z.
S
h
i
,
“
M
P
S
O
:
M
o
d
i
f
i
e
d
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
m
i
z
a
t
i
o
n
a
n
d
i
t
s
a
p
p
l
i
c
a
t
i
o
n
s,
”
S
w
a
rm
a
n
d
Ev
o
l
u
t
i
o
n
a
ry
C
o
m
p
u
t
a
t
i
o
n
,
v
o
l
.
4
1
,
p
p
.
4
9
–
6
8
,
A
u
g
.
2
0
1
8
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
sw
e
v
o
.
2
0
1
8
.
0
1
.
0
1
1
.
[
2
1
]
K
.
W
a
t
a
n
a
b
e
a
n
d
X
.
X
u
,
“
N
o
n
l
i
n
e
a
r
c
r
o
ss
i
n
g
st
r
a
t
e
g
y
-
b
a
s
e
d
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
mi
z
a
t
i
o
n
s
w
i
t
h
t
i
me
-
v
a
r
y
i
n
g
a
c
c
e
l
e
r
a
t
i
o
n
c
o
e
f
f
i
c
i
e
n
t
s,
”
A
p
p
l
i
e
d
I
n
t
e
l
l
i
g
e
n
c
e
,
v
o
l
.
5
4
,
n
o
.
1
3
–
1
4
,
p
p
.
7
2
2
9
–
7
2
7
7
,
Ju
l
.
2
0
2
4
,
d
o
i
:
1
0
.
1
0
0
7
/
s1
0
4
8
9
-
0
2
4
-
0
5
5
0
2
-
1.
[
2
2
]
Y
.
O
.
M
.
S
e
k
y
e
r
e
,
F
.
B
.
Ef
f
a
h
,
a
n
d
P
.
Y
.
O
k
y
e
r
e
,
“
A
n
e
n
h
a
n
c
e
d
p
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
mi
z
a
t
i
o
n
a
l
g
o
r
i
t
h
m
v
i
a
a
d
a
p
t
i
v
e
d
y
n
a
mi
c
i
n
e
r
t
i
a
w
e
i
g
h
t
a
n
d
a
c
c
e
l
e
r
a
t
i
o
n
c
o
e
f
f
i
c
i
e
n
t
s
,
”
J
o
u
r
n
a
l
o
f
E
l
e
c
t
r
o
n
i
c
s
a
n
d
El
e
c
t
r
i
c
a
l
E
n
g
i
n
e
e
ri
n
g
,
v
o
l
.
3
,
n
o
.
1
,
p
p
.
5
3
–
6
7
,
Ja
n
.
2
0
2
4
,
d
o
i
:
1
0
.
3
7
2
5
6
/
j
e
e
e
.
3
1
2
0
2
4
3
8
6
8
.
[
2
3
]
N
.
M
i
t
t
a
l
,
U
.
S
i
n
g
h
,
a
n
d
B
.
S
.
S
o
h
i
,
“
M
o
d
i
f
i
e
d
g
r
e
y
w
o
l
f
o
p
t
i
mi
z
e
r
f
o
r
g
l
o
b
a
l
e
n
g
i
n
e
e
r
i
n
g
o
p
t
i
mi
z
a
t
i
o
n
,
”
Ap
p
l
i
e
d
C
o
m
p
u
t
a
t
i
o
n
a
l
I
n
t
e
l
l
i
g
e
n
c
e
a
n
d
S
o
f
t
C
o
m
p
u
t
i
n
g
,
v
o
l
.
2
0
1
6
,
p
p
.
1
–
1
6
,
2
0
1
6
,
d
o
i
:
1
0
.
1
1
5
5
/
2
0
1
6
/
7
9
5
0
3
4
8
.
[
2
4
]
S.
-
C
.
W
a
n
g
a
n
d
Z.
-
Y
.
Zh
a
n
g
,
“
R
e
se
a
r
c
h
o
n
o
p
t
i
m
u
m
c
h
a
r
g
i
n
g
c
u
r
r
e
n
t
p
r
o
f
i
l
e
w
i
t
h
m
u
l
t
i
-
s
t
a
g
e
c
o
n
s
t
a
n
t
c
u
r
r
e
n
t
b
a
s
e
d
o
n
b
i
o
-
i
n
s
p
i
r
e
d
o
p
t
i
mi
z
a
t
i
o
n
a
l
g
o
r
i
t
h
ms
f
o
r
l
i
t
h
i
u
m
-
i
o
n
b
a
t
t
e
r
i
e
s
,
”
E
n
e
r
g
i
e
s
,
v
o
l
.
1
6
,
n
o
.
2
2
,
p
.
7
6
4
1
,
N
o
v
.
2
0
2
3
,
d
o
i
:
1
0
.
3
3
9
0
/
e
n
1
6
2
2
7
6
4
1
.
[
2
5
]
H
.
S
.
R
a
ma
d
a
n
,
H
.
H
a
e
s
A
l
h
e
l
o
u
,
a
n
d
A
.
A
.
A
h
me
d
,
“
I
mp
a
r
t
i
a
l
n
e
a
r
‐
o
p
t
i
mal
c
o
n
t
r
o
l
a
n
d
s
i
z
i
n
g
f
o
r
b
a
t
t
e
r
y
h
y
b
r
i
d
e
n
e
r
g
y
s
y
st
e
m
b
a
l
a
n
c
e
v
i
a
g
r
e
y
w
o
l
f
o
p
t
i
mi
z
e
r
s:
l
e
a
d
a
c
i
d
a
n
d
l
i
t
h
i
u
m‐
i
o
n
t
e
c
h
n
o
l
o
g
i
e
s,”
I
ET
R
e
n
e
w
a
b
l
e
P
o
w
e
r
G
e
n
e
r
a
t
i
o
n
,
v
o
l
.
1
9
,
n
o
.
1
,
p
p
.
1
–
1
4
,
J
a
n
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
4
9
/
r
p
g
2
.
1
2
4
2
3
.
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
Op
timiz
a
tio
n
o
f E
V
b
a
tter
y
ch
a
r
g
in
g
fo
r
temp
era
tu
r
e
co
n
tr
o
l
(
R
.
J.
V
ija
ya
S
a
r
a
s
w
a
th
i
)
1609
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
R.
J
.
Vija
y
a
S
a
r
a
sw
a
th
i
re
c
e
iv
e
d
h
e
r
B.
Tec
h
.
i
n
e
lec
tro
n
ics
a
n
d
i
n
stru
m
e
n
tati
o
n
e
n
g
in
e
e
rin
g
fro
m
S
AST
RA
U
n
i
v
e
rsity
,
Tan
j
o
re
,
I
n
d
ia,
i
n
2
0
1
0
,
a
n
d
h
e
r
M
.
E.
in
p
o
we
r
e
lec
tro
n
ics
a
n
d
d
ri
v
e
s
fro
m
An
a
n
d
In
stit
u
te
o
f
Hig
h
e
r
Tec
h
n
o
l
o
g
y
(AIH
T),
Ch
e
n
n
a
i,
a
ffil
iate
d
with
An
n
a
Un
i
v
e
rsity
,
Ch
e
n
n
a
i
,
in
2
0
1
2
.
S
h
e
is
c
u
rre
n
tl
y
p
u
rsu
in
g
h
e
r
P
h
.
D.
a
t
A
n
n
a
Un
iv
e
rsity
,
C
h
e
n
n
a
i
.
At
p
re
se
n
t
,
sh
e
is
w
o
rk
i
n
g
a
s
a
n
a
ss
istan
t
p
ro
fe
ss
o
r
a
t
P
a
n
ima
lar
En
g
i
n
e
e
rin
g
C
o
ll
e
g
e
,
C
h
e
n
n
a
i,
Tam
il
Na
d
u
,
In
d
ia.
He
r
c
u
rre
n
t
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
e
lec
tri
c
v
e
h
icle
s,
re
n
e
wa
b
le
e
n
e
r
g
y
sy
ste
m
s,
a
n
d
e
m
b
e
d
d
e
d
sy
ste
m
s.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
v
ij
a
y
a
sa
ra
sw
a
th
i8
8
@g
m
a
il
.
c
o
m
.
K
r
ish
n
a
k
u
m
a
r
V
e
n
g
a
d
a
k
r
ish
n
a
n
re
c
e
iv
e
d
h
is
B.
E.
in
e
lec
tri
c
a
l
a
n
d
e
lec
tro
n
ic
s
e
n
g
in
e
e
rin
g
fr
o
m
IF
ET
E
n
g
i
n
e
e
rin
g
C
o
ll
e
g
e
,
Vil
lu
p
u
ra
m
,
In
d
ia,
i
n
2
0
0
7
,
h
is
M
.
Tec
h
.
fr
o
m
P
o
n
d
ich
e
rry
E
n
g
i
n
e
e
rin
g
Co
l
leg
e
,
P
o
n
d
ic
h
e
rry
,
In
d
ia,
i
n
2
0
1
0
,
a
n
d
h
is
P
h
.
D.
fro
m
An
n
a
Un
iv
e
rsity
,
Ch
e
n
n
a
i,
I
n
d
ia,
in
2
0
1
7
.
At
p
re
se
n
t,
h
e
is
wo
r
k
in
g
a
s
a
n
a
ss
o
c
iate
p
ro
fe
ss
o
r
a
t
S
t.
Jo
se
p
h
'
s
Co
l
leg
e
o
f
En
g
in
e
e
rin
g
,
Ch
e
n
n
a
i,
Tam
il
Na
d
u
,
In
d
ia.
Hi
s
c
u
rre
n
t
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
th
e
p
e
rfo
rm
a
n
c
e
imp
ro
v
e
m
e
n
t
o
f
p
e
rm
a
n
e
n
t
m
a
g
n
e
t
b
ru
s
h
les
s
DC
m
o
t
o
r
d
ri
v
e
s
a
n
d
th
e
p
e
rfo
rm
a
n
c
e
e
n
h
a
n
c
e
m
e
n
t
o
f
so
li
d
-
sta
te
c
o
n
v
e
rters
th
r
o
u
g
h
in
n
o
v
a
t
iv
e
p
u
lse
-
wid
t
h
m
o
d
u
lati
o
n
stra
teg
ies
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
v
.
k
ris
h
n
a
k
u
m
a
rsjc
e
@g
m
a
il
.
c
o
m
.
Va
sa
n
Pra
b
h
u
Ve
e
r
a
m
a
n
i
re
c
e
iv
e
d
h
is
B.
E.
d
e
g
re
e
in
e
lec
tri
c
a
l
a
n
d
e
lec
tro
n
ics
e
n
g
in
e
e
rin
g
fr
o
m
EG
S
P
E
n
g
in
e
e
rin
g
C
o
ll
e
g
e
,
Na
g
a
p
a
tt
i
n
a
m
,
T
a
m
il
Na
d
u
,
I
n
d
ia,
a
ffil
iate
d
with
An
n
a
U
n
iv
e
rsit
y
,
C
h
e
n
n
a
i
,
in
2
0
0
5
.
He
re
c
e
iv
e
d
h
is
M
.
E.
d
e
g
re
e
in
p
o
we
r
e
lec
tro
n
ics
a
n
d
d
ri
v
e
s
fro
m
S
S
N
Co
l
leg
e
o
f
En
g
i
n
e
e
rin
g
,
Ch
e
n
n
a
i,
Tam
il
Na
d
u
,
In
d
ia,
a
ffil
iate
d
wit
h
An
n
a
Un
iv
e
rsit
y
,
Ch
e
n
n
a
i,
i
n
2
0
0
8
,
a
n
d
h
is
P
h
.
D.
d
e
g
re
e
fro
m
An
n
a
Un
iv
e
rsit
y
,
Ch
e
n
n
a
i,
In
d
ia,
in
2
0
1
8
.
He
is
c
u
rre
n
tl
y
w
o
rk
i
n
g
a
s
a
su
b
jec
t
m
a
tt
e
r
e
x
p
e
rt
a
t
L&T
Ed
u
Tec
h
,
Ch
e
n
n
a
i,
In
d
ia.
His
re
se
a
rc
h
i
n
tere
sts
i
n
c
lu
d
e
e
lec
tri
c
a
l
d
riv
e
s
a
n
d
c
o
n
t
ro
l,
e
lec
tri
c
v
e
h
icle
s,
so
ft
c
o
m
p
u
ti
n
g
a
p
p
l
ica
ti
o
n
s
in
re
n
e
wa
b
le
e
n
e
rg
y
,
a
n
d
m
a
c
h
in
e
lea
rn
i
n
g
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
v
a
sa
n
p
ra
b
h
u
@g
m
a
il
.
c
o
m
.
S
.
K
a
m
a
l
a
k
k
a
n
n
a
n
o
b
tai
n
e
d
h
is
B
.
E.
d
e
g
re
e
i
n
e
lec
tri
c
a
l
a
n
d
e
lec
tro
n
ics
e
n
g
in
e
e
rin
g
fro
m
M
a
d
ra
s
Un
iv
e
rsity
,
Ch
e
n
n
a
i,
In
d
ia,
in
1
9
9
7
,
h
is
M
.
E.
d
e
g
re
e
in
p
o
we
r
e
lec
tro
n
ics
a
n
d
d
riv
e
s
fro
m
B
h
a
ra
th
id
a
sa
n
Un
i
v
e
rsity
,
Tri
c
h
y
,
In
d
ia,
in
2
0
0
1
,
a
n
d
h
is
P
h
.
D.
d
e
g
re
e
in
e
lec
tri
c
a
l
e
n
g
in
e
e
rin
g
fr
o
m
S
a
th
y
a
b
a
m
a
Un
i
v
e
rsity
,
C
h
e
n
n
a
i,
I
n
d
ia,
i
n
2
0
1
9
.
He
h
a
s
p
u
b
li
sh
e
d
se
v
e
ra
l
re
se
a
rc
h
p
a
p
e
r
s
in
t
h
e
a
re
a
s
o
f
p
o
we
r
e
lec
tro
n
i
c
s
a
n
d
i
n
d
u
strial
d
riv
e
s
i
n
v
a
rio
u
s
j
o
u
r
n
a
ls
a
n
d
c
o
n
fe
re
n
c
e
s.
His
re
se
a
rc
h
in
tere
sts
in
c
lu
d
e
p
o
we
r
e
lec
tro
n
i
c
s,
in
d
u
strial
d
riv
e
s,
re
n
e
wa
b
le en
e
rg
y
sy
ste
m
s
,
a
n
d
e
lec
tri
c
v
e
h
icle
s.
He
is cu
rre
n
tl
y
wo
r
k
i
n
g
a
s a
p
ro
fe
ss
o
r
in
th
e
De
p
a
rtme
n
t
o
f
El
e
c
tri
c
a
l
a
n
d
El
e
c
tro
n
ics
En
g
i
n
e
e
rin
g
a
t
S
.
A.
En
g
in
e
e
rin
g
Co
ll
e
g
e
,
Ch
e
n
n
a
i,
In
d
ia.
He
c
a
n
b
e
c
o
n
tac
t
e
d
a
t
e
m
a
il
:
m
y
p
k
g
1
9
4
@g
m
a
il
.
c
o
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.