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
.
2
,
J
u
n
e
20
2
6
,
p
p
.
1025
~
1
0
3
5
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
2
.
p
p
1
0
2
5
-
1
0
3
5
1025
J
o
ur
na
l ho
m
ep
a
g
e
:
h
ttp
:
//ij
p
e
d
s
.
ia
esco
r
e.
co
m
M
ulti
-
o
bje
ctive e
nerg
y
ma
na
g
ement optimiza
tion in
electric
v
ehicles using
f
uz
zy
log
ic and pa
rti
cle swa
rm o
pti
mi
za
tion
V
.
L
a
k
s
hm
i D
ev
i
1
,
Da
mo
dh
a
r
Reddy
2
,
Srik
a
nth
Velpula
3
,
K.
K
um
a
r
4
,
B
a
s
i R
eddy
Av
ula
5
1
S
c
h
o
o
l
o
f
E
n
g
i
n
e
e
r
i
n
g
,
A
n
u
r
a
g
U
n
i
v
e
r
si
t
y
,
H
y
d
e
r
a
b
a
d
,
I
n
d
i
a
2
I
n
st
i
t
u
t
e
o
f
A
e
r
o
n
a
u
t
i
c
a
l
E
n
g
i
n
e
e
r
i
n
g
,
D
u
n
d
i
g
a
l
,
H
y
d
e
r
a
b
a
d
,
I
n
d
i
a
3
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
R
U
n
i
v
e
r
si
t
y
,
W
a
r
a
n
g
a
l
,
I
n
d
i
a
4
D
e
p
a
r
t
me
n
t
o
f
D
e
p
a
r
t
m
e
n
t
o
f
E
l
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
r
i
V
e
n
k
a
t
e
sw
a
r
a
C
o
l
l
e
g
e
o
f
En
g
i
n
e
e
r
i
n
g
,
Ti
r
u
p
a
t
i
,
I
n
d
i
a
5
D
e
p
a
r
t
me
n
t
o
f
C
o
m
p
u
t
e
r
S
c
i
e
n
c
e
a
n
d
E
n
g
i
n
e
e
r
i
n
g
,
M
o
h
a
n
B
a
b
u
U
n
i
v
e
r
si
t
y
,
S
c
h
o
o
l
o
f
C
o
mp
u
t
i
n
g
,
T
i
r
u
p
a
t
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
J
u
l
30
,
2
0
2
5
R
ev
is
ed
Ma
r
0
8
,
2
0
2
6
Acc
ep
ted
Ap
r
23
,
2
0
2
6
Th
is
p
a
p
e
r
p
r
o
p
o
se
s
a
h
y
b
rid
e
n
e
rg
y
m
a
n
a
g
e
m
e
n
t
s
y
ste
m
(EM
S
)
f
o
r
e
lec
tri
c
v
e
h
icle
s
b
y
i
n
teg
ra
ti
n
g
f
u
z
z
y
l
o
g
ic
c
o
n
tro
l
(
F
LC)
wit
h
p
a
rti
c
le
sw
a
rm
o
p
ti
m
iza
ti
o
n
(
P
S
O)
to
imp
r
o
v
e
p
o
we
r
-
sp
li
t
d
e
c
isio
n
-
m
a
k
in
g
u
n
d
e
r
d
y
n
a
m
ic
d
riv
i
n
g
c
o
n
d
it
i
o
n
s.
Th
e
F
LC
is
d
e
sig
n
e
d
u
si
n
g
sta
te
o
f
c
h
a
rg
e
(
S
o
C
)
a
n
d
v
e
h
icle
sp
e
e
d
a
s
i
n
p
u
t
v
a
riab
les
a
n
d
p
o
we
r
sp
li
t
a
s
t
h
e
o
u
t
p
u
t.
A
se
t
o
f
fu
z
z
y
ru
les
d
e
fin
e
s
t
h
e
EM
S
b
e
h
a
v
i
o
r,
wh
i
le
P
S
O
is
e
m
p
l
o
y
e
d
to
fin
e
-
tu
n
e
d
e
c
isio
n
s
b
y
m
a
x
imiz
in
g
a
n
e
ff
icie
n
c
y
o
b
jec
ti
v
e
f
u
n
c
ti
o
n
d
e
fi
n
e
d
a
s
th
e
c
lo
se
n
e
ss
o
f
th
e
p
o
we
r
sp
l
it
t
o
a
n
id
e
a
l
re
fe
re
n
c
e
.
Th
e
sim
u
latio
n
is
imp
lem
e
n
ted
i
n
P
y
t
h
o
n
u
sin
g
C
o
lab
-
c
o
m
p
a
ti
b
le
p
a
c
k
a
g
e
s
su
c
h
a
s
sc
ik
it
-
fu
z
z
y
,
DEAP,
a
n
d
m
a
tp
lo
tl
ib
,
e
n
su
rin
g
a
c
c
e
ss
ib
il
it
y
a
n
d
re
p
r
o
d
u
c
ib
il
it
y
.
A
tes
t
g
rid
c
o
v
e
rin
g
1
0
S
o
C
lev
e
ls
(1
0
–
1
0
0
%
)
a
n
d
1
0
sp
e
e
d
le
v
e
ls
(1
0
–
1
2
0
k
m
/h
)
is
u
se
d
to
e
v
a
l
u
a
te
th
e
sy
ste
m
.
Visu
a
li
z
a
ti
o
n
to
o
ls,
in
c
lu
d
i
n
g
h
e
a
tma
p
s,
3
D
su
rfa
c
e
p
l
o
ts,
a
n
d
c
o
n
t
o
u
r
p
l
o
ts,
a
re
e
m
p
lo
y
e
d
to
re
p
re
se
n
t
th
e
EM
S
b
e
h
a
v
i
o
r.
T
h
e
P
S
O
-
e
n
h
a
n
c
e
d
sy
ste
m
a
c
h
iev
e
d
a
m
a
x
imu
m
e
fficie
n
c
y
o
f
9
8
.
2
%
a
t
a
n
o
p
t
imiz
e
d
S
o
C
o
f
6
1
.
7
%
a
n
d
a
sp
e
e
d
o
f
5
3
.
6
k
m
/
h
,
o
u
t
p
e
rfo
rm
in
g
sta
n
d
a
lo
n
e
fu
z
z
y
lo
g
ic
c
o
n
tr
o
l.
Ta
b
u
late
d
re
su
lt
s
a
n
d
sta
ti
stica
l
su
m
m
a
ries
v
a
li
d
a
te t
h
e
e
ffe
c
ti
v
e
n
e
ss
o
f
th
e
p
ro
p
o
se
d
s
y
st
e
m
.
K
ey
w
o
r
d
s
:
E
f
f
icien
cy
o
p
tim
izatio
n
E
lectr
ic
v
eh
icles
E
n
er
g
y
m
an
ag
e
m
en
t sy
s
tem
Fu
zz
y
lo
g
ic
co
n
tr
o
l
Par
ticle
s
war
m
o
p
tim
izatio
n
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
:
K.
Ku
m
ar
D
e
p
a
r
t
m
e
n
t
o
f
D
e
p
a
r
t
m
e
n
t
o
f
E
l
e
c
t
r
i
c
a
l
a
n
d
E
l
e
c
t
r
o
n
i
c
s
E
n
g
i
n
e
e
r
i
n
g
,
S
r
i
V
e
n
k
a
t
e
s
w
a
r
a
C
o
l
l
e
g
e
o
f
E
n
g
i
n
e
e
r
i
n
g
T
ir
u
p
ati,
An
d
h
r
a
Pra
d
esh
,
I
n
d
i
a
E
m
ail:
k
u
m
ar
3
k
k
@
g
m
ail.
co
m
1.
I
NT
RO
D
UCT
I
O
N
T
h
e
r
ap
id
ad
o
p
tio
n
o
f
elec
tr
ic
v
eh
icles
(
E
Vs)
is
tr
an
s
f
o
r
m
in
g
th
e
g
l
o
b
al
tr
an
s
p
o
r
tatio
n
s
ec
to
r
,
f
u
ele
d
b
y
th
e
u
r
g
en
t
n
ee
d
to
r
ed
u
ce
g
r
ee
n
h
o
u
s
e
g
as
em
is
s
io
n
s
,
e
n
h
an
ce
en
er
g
y
s
ec
u
r
ity
,
a
n
d
p
r
o
m
o
te
s
u
s
tain
ab
le
m
o
b
ilit
y
.
Acc
o
r
d
in
g
to
th
e
I
n
t
er
n
atio
n
al
E
n
er
g
y
Ag
en
c
y
(
I
E
A)
,
E
Vs
ar
e
p
r
o
jecte
d
to
co
n
s
titu
te
o
v
er
3
5
%
o
f
g
lo
b
al
v
e
h
icle
s
ales
b
y
2
0
3
0
,
in
te
n
s
if
y
in
g
th
e
d
e
m
an
d
f
o
r
ef
f
icie
n
t
an
d
in
tellig
e
n
t
o
n
b
o
ar
d
en
e
r
g
y
m
an
ag
em
en
t
[
1
]
,
[
2
]
.
T
o
en
s
u
r
e
p
er
f
o
r
m
an
ce
,
s
af
ety
,
an
d
b
atter
y
lo
n
g
ev
ity
,
en
er
g
y
m
an
ag
em
en
t
s
y
s
tem
s
(
E
MS)
ar
e
c
r
itical
in
d
y
n
am
i
ca
lly
r
eg
u
latin
g
p
o
wer
f
lo
w
b
etwe
en
v
eh
icle
co
m
p
o
n
en
ts
,
in
clu
d
in
g
b
atter
ies,
r
eg
en
er
ativ
e
b
r
a
k
in
g
u
n
its
,
a
n
d
au
x
iliar
y
lo
a
d
s
[
3
]
,
[
4
]
.
Ho
wev
er
,
co
n
v
en
tio
n
al
E
MS
im
p
lem
en
tatio
n
s
,
ty
p
ically
b
u
ilt
o
n
s
tatic
lo
g
ic,
h
eu
r
is
tic
r
u
les,
o
r
p
r
e
-
p
r
o
g
r
a
m
m
ed
lo
o
k
-
u
p
tab
les
,
lack
th
e
f
lex
ib
ilit
y
to
h
an
d
le
tim
e
-
v
ar
y
in
g
,
n
o
n
lin
ea
r
b
eh
av
io
r
s
u
n
d
er
r
ea
l
-
wo
r
ld
d
r
iv
i
n
g
c
y
cles [
5
]
,
[
6
]
.
Fu
zz
y
lo
g
ic
co
n
tr
o
ller
s
(
FLC
s
)
h
av
e
em
er
g
ed
as
a
v
iab
le
alter
n
ativ
e
d
u
e
to
th
eir
r
o
b
u
s
tn
ess
in
h
an
d
lin
g
in
p
u
t u
n
ce
r
tain
ty
an
d
th
eir
ca
p
ab
ilit
y
f
o
r
h
u
m
a
n
-
lik
e
r
ea
s
o
n
in
g
[
7
]
–
[
9
]
.
B
y
u
s
in
g
lin
g
u
is
tic
r
u
les an
d
ap
p
r
o
x
im
ate
in
f
e
r
en
ce
,
FLC
s
o
f
f
er
t
r
an
s
p
ar
en
t
d
ec
is
io
n
-
m
ak
in
g
f
o
r
en
er
g
y
d
is
tr
ib
u
tio
n
task
s
,
s
u
ch
as
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
.
2
,
J
u
n
e
20
2
6
:
1
0
2
5
-
1035
1026
d
eter
m
in
in
g
th
e
p
o
wer
d
is
tr
ib
u
tio
n
r
atio
(
PDR
)
b
ased
o
n
p
ar
am
eter
s
lik
e
s
tate
-
of
-
ch
ar
g
e
(
So
C
)
,
s
p
ee
d
,
an
d
p
o
wer
d
e
m
an
d
.
Ho
wev
er
,
th
e
p
er
f
o
r
m
an
ce
o
f
f
u
zz
y
s
y
s
tem
s
h
ea
v
ily
d
e
p
en
d
s
o
n
th
e
p
r
o
p
er
tu
n
in
g
o
f
m
em
b
er
s
h
ip
f
u
n
ctio
n
s
a
n
d
r
u
le
s
tr
en
g
th
s
,
o
f
ten
r
eq
u
ir
i
n
g
o
p
tim
izatio
n
m
eth
o
d
s
to
ac
h
i
ev
e
g
en
er
aliza
b
ilit
y
an
d
g
l
o
b
al
p
er
f
o
r
m
an
ce
[
1
0
]
.
T
o
th
is
en
d
,
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
o
f
f
e
r
s
a
p
o
w
er
f
u
l
m
eta
h
eu
r
is
tic
f
r
am
ewo
r
k
f
o
r
r
ef
in
in
g
f
u
zz
y
co
n
tr
o
l
s
u
r
f
ac
es.
PS
O
ex
ce
ls
i
n
co
n
tin
u
o
u
s
,
n
o
n
lin
ea
r
s
ea
r
c
h
s
p
ac
es,
d
eliv
er
in
g
f
ast
co
n
v
er
g
e
n
ce
an
d
lo
w
c
o
m
p
u
tatio
n
al
o
v
er
h
ea
d
,
esp
e
cially
attr
ac
tiv
e
f
o
r
r
ea
l
-
tim
e
em
b
ed
d
e
d
E
MS
ap
p
licatio
n
s
[
1
1
]
–
[
1
4
]
.
Pas
t stu
d
ies h
av
e
s
h
o
wn
th
e
ef
f
icac
y
o
f
Fu
zz
y
-
PS
O
h
y
b
r
id
s
in
d
o
m
ain
s
s
u
ch
as h
y
b
r
id
elec
tr
ic
v
eh
icle
co
n
tr
o
l [
1
5
]
,
s
m
ar
t m
icr
o
g
r
id
s
[
1
6
]
,
an
d
r
en
e
wab
le
en
er
g
y
s
y
s
tem
s
[
1
7
]
,
[
1
8
]
.
I
n
th
is
s
tu
d
y
,
we
p
r
o
p
o
s
e
a
Py
th
o
n
-
b
ased
h
y
b
r
id
E
MS
m
o
d
el
co
m
b
in
in
g
f
u
zz
y
in
f
er
e
n
c
e
with
PS
O
o
p
tim
izatio
n
,
d
esig
n
e
d
f
o
r
en
er
g
y
-
ef
f
icien
t
co
n
tr
o
l
in
E
Vs
an
d
ev
alu
ated
u
n
d
er
th
e
Ur
b
an
Dy
n
am
o
m
eter
Dr
iv
in
g
Sch
ed
u
le
(
UDDS)
.
T
h
e
s
y
s
tem
is
im
p
lem
en
ted
i
n
Go
o
g
le
C
o
lab
,
o
f
f
er
i
n
g
clo
u
d
-
b
ased
s
im
u
latio
n
,
v
is
u
aliza
tio
n
,
an
d
d
ata
ex
p
o
r
t
f
o
r
teac
h
in
g
,
p
r
o
to
ty
p
i
n
g
,
an
d
r
esear
ch
.
Un
lik
e
co
m
p
le
x
d
e
e
p
-
lear
n
in
g
m
o
d
els,
th
is
m
eth
o
d
o
f
f
er
s
a
lig
h
tweig
h
t,
in
ter
p
r
eta
b
le,
an
d
r
ea
l
-
tim
e
co
m
p
atib
le
s
o
lu
tio
n
.
T
h
e
m
ajo
r
c
o
n
tr
ib
u
tio
n
s
o
f
t
h
is
wo
r
k
ar
e:
−
Desig
n
o
f
a
two
-
lay
er
E
MS
f
r
am
ewo
r
k
in
teg
r
atin
g
f
u
zz
y
l
o
g
ic
with
PS
O
-
b
ased
tu
n
in
g
f
o
r
o
p
tim
ized
p
o
wer
s
p
lit co
n
tr
o
l.
−
I
m
p
lem
en
tatio
n
o
f
r
ea
l
-
tim
e
h
ea
tm
ap
s
,
co
n
to
u
r
s
,
an
d
3
D
s
u
r
f
ac
e
p
lo
ts
to
v
is
u
alize
co
n
tr
o
ller
b
eh
av
io
u
r
an
d
in
ter
p
r
etab
ilit
y
.
−
E
v
alu
atio
n
o
f
p
e
r
f
o
r
m
an
ce
m
etr
ics,
in
clu
d
in
g
en
er
g
y
s
av
in
g
s
,
So
C
s
tab
ilit
y
,
an
d
p
o
wer
s
p
lit
ac
cu
r
ac
y
,
b
en
ch
m
ar
k
ed
a
g
ain
s
t r
u
le
-
b
as
ed
an
d
s
tan
d
al
o
n
e
f
u
zz
y
c
o
n
tr
o
ller
s
.
−
Dev
elo
p
m
en
t
o
f
a
C
o
lab
-
co
m
p
atib
le
E
MS
to
o
lk
it,
en
ab
li
n
g
r
e
p
r
o
d
u
cib
ilit
y
,
e
d
u
ca
tio
n
al
d
ep
lo
y
m
en
t
,
an
d
f
u
t
u
r
e
em
b
ed
d
e
d
in
teg
r
ati
o
n
.
T
h
is
wo
r
k
b
u
ild
s
u
p
o
n
ex
is
tin
g
s
tu
d
ies
in
f
u
zz
y
-
b
ased
E
MS
d
esig
n
[
1
9
]
,
m
etah
eu
r
is
tic
o
p
tim
izatio
n
f
o
r
d
r
iv
etr
ai
n
c
o
n
tr
o
l
[
2
0
]
,
an
d
m
u
lti
-
o
b
jectiv
e
f
u
zz
y
s
y
s
tem
s
[
2
1
]
.
T
h
e
r
esu
lts
in
d
icate
th
at
th
e
h
y
b
r
id
Fu
zz
y
-
PS
O
E
MS
ac
h
iev
es
s
u
p
er
io
r
e
n
er
g
y
e
f
f
icien
cy
,
s
tab
ilit
y
,
an
d
co
n
tr
o
l
ac
c
u
r
ac
y
wh
e
n
co
m
p
ar
ed
with
b
aselin
e
E
MS
ar
ch
itectu
r
es
[
2
2
]
–
[
2
4
]
.
Fu
r
th
er
m
o
r
e,
th
e
m
o
d
u
lar
ar
ch
itectu
r
e
an
d
in
teg
r
ated
v
is
u
aliza
tio
n
to
o
ls
s
u
p
p
o
r
t
s
ca
lab
ilit
y
t
o
war
d
f
u
tu
r
e
h
y
b
r
id
E
V
p
latf
o
r
m
s
,
s
m
ar
t
ch
ar
g
in
g
s
y
s
tem
s
,
an
d
co
n
n
ec
ted
v
eh
icle
ap
p
licatio
n
s
[
2
5
]
.
R
ec
en
t
s
tu
d
ies
h
av
e
ex
am
in
ed
f
u
zz
y
–
PS
O
h
y
b
r
id
s
f
o
r
E
V
en
e
r
g
y
m
a
n
ag
em
en
t,
b
u
t
m
o
s
t
r
ely
o
n
f
ix
ed
r
u
le
b
ases
an
d
lim
ited
v
alid
atio
n
.
T
h
is
wo
r
k
ad
v
an
ce
s
th
e
f
ield
b
y
d
e
v
el
o
p
in
g
a
lig
h
tweig
h
t
Ma
m
d
an
i
-
ty
p
e
f
u
zz
y
c
o
n
tr
o
lle
r
with
PS
O
-
o
p
tim
ized
m
em
b
e
r
s
h
ip
f
u
n
ctio
n
s
,
im
p
lem
en
ted
in
an
o
p
e
n
Py
th
o
n
-
b
ased
C
o
lab
f
r
am
ewo
r
k
f
o
r
tr
an
s
p
ar
en
t
b
e
n
ch
m
ar
k
in
g
.
Un
d
er
th
e
UDDS
cy
cle,
th
e
p
r
o
p
o
s
ed
m
eth
o
d
ac
h
iev
ed
a
2
9
.
7
%
r
e
d
u
ctio
n
i
n
en
er
g
y
co
n
s
u
m
p
tio
n
a
n
d
8
.
2
k
m
/k
W
h
e
f
f
icien
cy
o
v
e
r
r
u
le
-
b
ased
an
d
u
n
tu
n
e
d
f
u
zz
y
co
n
tr
o
ller
s
.
Un
lik
e
ea
r
lier
ap
p
r
o
ac
h
es,
it
also
v
is
u
alize
s
o
p
tim
ized
d
ec
is
io
n
s
u
r
f
ac
es
an
d
o
f
f
er
s
a
s
tr
u
ctu
r
e
r
ea
d
ily
d
ep
lo
y
ab
le
f
o
r
r
ea
l
-
tim
e
em
b
e
d
d
ed
u
s
e.
2.
M
E
T
H
O
D
T
h
is
s
tu
d
y
p
r
o
p
o
s
es
a
h
y
b
r
i
d
in
tellig
en
t
E
MS
f
o
r
E
Vs
b
ased
o
n
f
u
zz
y
lo
g
ic
an
d
P
SO.
T
h
e
m
eth
o
d
o
l
o
g
y
co
m
p
r
is
es
f
o
u
r
k
ey
m
o
d
u
les:
i
)
E
MS
s
y
s
tem
ar
ch
itectu
r
e,
ii
)
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
d
ev
elo
p
m
e
n
t,
iii
)
PS
O
-
b
ase
d
o
p
tim
izatio
n
o
f
f
u
zz
y
m
em
b
er
s
h
ip
f
u
n
ctio
n
s
,
an
d
iv
)
s
im
u
latio
n
-
b
ased
p
er
f
o
r
m
an
ce
ev
al
u
atio
n
.
2
.
1
.
E
M
S sy
s
t
em
a
rc
hite
ct
ure
T
h
e
p
r
o
p
o
s
ed
E
MS
r
ec
eiv
es
r
ea
l
-
tim
e
in
p
u
t
p
ar
a
m
eter
s
s
u
ch
as
v
eh
icle
s
p
ee
d
,
So
C
,
lo
ad
p
o
we
r
d
em
an
d
,
a
n
d
r
o
ad
g
r
ad
ien
t.
B
ased
o
n
th
ese,
it
co
m
p
u
tes
th
e
o
p
tim
al
PDR
b
etwe
en
b
atter
y
s
u
p
p
ly
a
n
d
r
eg
en
er
ativ
e
b
r
ak
in
g
u
s
in
g
a
f
u
zz
y
lo
g
ic
co
n
t
r
o
ller
wh
o
s
e
m
em
b
er
s
h
ip
f
u
n
ctio
n
s
ar
e
d
y
n
a
m
ically
tu
n
ed
u
s
in
g
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
PS
O)
.
T
h
e
b
lo
c
k
d
iag
r
am
o
f
th
e
p
r
o
p
o
s
ed
s
y
s
tem
is
s
h
o
wn
in
Fig
u
r
e
1
.
R
aw
s
en
s
o
r
in
p
u
ts
ar
e
f
ilter
e
d
an
d
n
o
r
m
alize
d
b
ef
o
r
e
b
ein
g
p
ass
ed
to
th
e
f
u
zz
y
-
PS
O
co
n
tr
o
lle
r
.
T
h
e
o
u
tp
u
t
o
f
th
e
co
n
tr
o
ller
d
r
i
v
es
th
e
p
o
wer
tr
a
in
ac
tu
ato
r
in
ter
f
ac
e,
wh
ich
i
n
clu
d
es
elec
tr
o
n
ic
co
n
v
e
r
ter
s
,
b
r
ak
in
g
lo
g
ic
,
an
d
m
o
to
r
co
n
tr
o
ller
s
.
Ad
d
itio
n
al
ly
,
a
f
ee
d
b
ac
k
lo
o
p
m
o
n
ito
r
s
th
e
ef
f
ec
t
o
f
co
n
tr
o
l
ac
tio
n
s
o
n
So
C
,
en
ab
lin
g
ad
ap
tiv
e
d
ec
is
io
n
-
m
ak
i
n
g
in
f
u
tu
r
e
cy
cles.
T
h
is
m
o
d
u
lar
ar
ch
itectu
r
e
en
s
u
r
es
s
ca
lab
ilit
y
an
d
r
ea
l
-
tim
e
d
ep
lo
y
a
b
ilit
y
o
n
em
b
ed
d
e
d
p
l
atf
o
r
m
s
s
u
ch
as
d
SP
A
C
E
,
Ar
d
u
in
o
,
o
r
MA
T
L
AB
/Si
m
u
lin
k
-
co
m
p
atib
le
tar
g
ets.
Mo
r
eo
v
er
,
th
e
s
ep
ar
atio
n
o
f
f
u
zz
y
co
n
tr
o
l
lo
g
ic
an
d
PS
O
o
p
tim
izatio
n
en
ab
les
o
f
f
lin
e
o
r
o
n
lin
e
tu
n
in
g
,
d
ep
en
d
i
n
g
o
n
th
e
d
ep
lo
y
m
en
t
r
eq
u
ir
em
e
n
ts
.
2
.
2
.
F
uzzy
lo
g
ic
co
ntr
o
ller
des
ig
n
T
h
e
f
u
zz
y
l
o
g
ic
co
n
tr
o
ller
(
FLC)
is
d
ev
elo
p
ed
u
s
in
g
ex
p
er
t
-
d
ef
in
e
d
h
eu
r
is
tic
r
u
les
f
o
r
en
er
g
y
m
an
ag
em
en
t
u
n
d
er
v
ar
y
in
g
d
r
iv
e
s
ce
n
ar
io
s
.
T
h
e
s
y
s
tem
in
clu
d
es
th
r
ee
in
p
u
t
lin
g
u
is
tic
v
ar
iab
les:
i)
Veh
icle
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
Mu
lti
-
o
b
jective
en
erg
y
ma
n
a
g
eme
n
t o
p
timiz
a
tio
n
in
elec
tr
ic
ve
h
icles u
s
in
g
fu
z
z
y
lo
g
ic
…
(
V
.
La
ksh
mi
Dev
i
)
1027
s
p
ee
d
(
V)
:
s
lo
w,
m
ed
i
u
m
,
h
ig
h
;
ii)
State
-
of
-
c
h
ar
g
e
(
So
C
)
:
lo
w,
m
ed
iu
m
,
h
ig
h
;
iii)
L
o
ad
p
o
wer
d
em
an
d
(P
load
)
:
lo
w,
m
ed
iu
m
,
h
ig
h
.
Fig
u
r
e
1
.
B
lo
ck
d
iag
r
am
o
f
th
e
p
r
o
p
o
s
ed
f
u
zz
y
-
PSO
-
b
ased
E
MS
co
n
tr
o
ller
T
h
e
o
u
tp
u
t
o
f
th
e
FLC
is
th
e
PDR
,
wh
ich
d
eter
m
in
es
th
e
co
n
tr
o
l
d
ec
is
io
n
b
etwe
en
b
atter
y
-
s
u
p
p
lied
p
r
o
p
u
ls
io
n
an
d
r
e
g
en
er
ativ
e
b
r
ak
in
g
en
er
g
y
r
ec
o
v
e
r
y
.
A
M
am
d
an
i
-
ty
p
e
f
u
zz
y
i
n
f
er
en
ce
s
y
s
tem
is
em
p
lo
y
ed
f
o
r
r
u
le
ev
alu
atio
n
,
with
ce
n
tr
o
id
-
b
ased
d
e
f
u
zz
if
icatio
n
t
o
p
r
o
d
u
ce
cr
is
p
co
n
t
r
o
l
o
u
tp
u
ts
.
E
ac
h
in
p
u
t
is
m
o
d
eled
u
s
in
g
tr
ian
g
u
lar
m
em
b
er
s
h
ip
f
u
n
ctio
n
s
,
d
e
f
in
ed
a
n
d
s
h
o
wn
in
(
1
)
:
(
)
=
{
0
,
≤
≥
−
−
,
<
<
−
−
,
≤
<
(
1
)
W
h
er
e:
a,
b
,
a
n
d
c
ar
e
th
e
lef
t,
p
ea
k
,
an
d
r
ig
h
t
p
ar
am
eter
s
o
f
th
e
tr
ian
g
le,
r
esp
ec
tiv
el
y
.
T
h
e
d
e
f
u
zz
if
icatio
n
p
r
o
ce
s
s
u
s
es th
e
ce
n
tr
o
id
m
eth
o
d
,
ca
lcu
lated
as sh
o
w
n
in
(
2
)
:
∗
=
∫
(
)
.
⬚
∫
(
)
.
⬚
(
2
)
Giv
en
th
e
th
r
ee
in
p
u
t
v
a
r
iab
le
s
an
d
th
eir
r
esp
ec
tiv
e
m
em
b
e
r
s
h
ip
lev
els,
a
to
tal
o
f
3
×
3
×3
=2
7
f
u
zz
y
r
u
les
ar
e
f
o
r
m
u
lated
.
T
h
e
s
tr
u
ctu
r
e
o
f
th
e
in
f
e
r
en
ce
m
ec
h
an
is
m
is
illu
s
tr
ated
in
Fig
u
r
e
2
,
wh
ich
m
ap
s
th
e
in
p
u
ts
to
th
e
f
u
zz
y
r
u
le
b
ase
an
d
h
ig
h
lig
h
ts
th
e
r
o
le
o
f
d
ef
u
zz
if
icatio
n
in
g
e
n
er
atin
g
o
u
tp
u
t
d
ec
is
io
n
s
.
A
r
ep
r
esen
tativ
e
s
u
b
s
et
o
f
th
e
f
u
zz
y
r
u
le
b
ase
is
p
r
esen
ted
in
T
ab
le
1
,
d
em
o
n
s
tr
atin
g
h
o
w
s
p
e
cif
ic
co
m
b
in
atio
n
s
o
f
in
p
u
ts
d
eter
m
in
e
th
e
PDR
o
u
tp
u
t.
E
ac
h
f
u
zz
y
i
n
p
u
t
is
m
o
d
eled
u
s
in
g
tr
ian
g
u
lar
m
em
b
e
r
s
h
ip
f
u
n
ctio
n
s
with
tu
n
a
b
le
p
ea
k
an
d
wid
th
p
ar
am
eter
s
.
T
h
ese
m
em
b
er
s
h
i
p
f
u
n
ctio
n
s
ar
e
s
u
b
ject
to
f
u
r
th
er
o
p
tim
izatio
n
u
s
in
g
PS
O,
wh
ich
r
ef
in
es
th
e
FLC r
esp
o
n
s
e
f
o
r
im
p
r
o
v
ed
p
o
wer
d
is
tr
ib
u
tio
n
e
f
f
icien
cy
.
Fig
u
r
e
2
.
Fu
zz
y
in
f
er
e
n
ce
b
o
x
T
ab
le
1
.
Sam
p
le
f
u
zz
y
r
u
le
b
a
s
e
f
o
r
FLC.
S
p
e
e
d
S
o
C
Lo
a
d
P
D
R
o
u
t
p
u
t
S
l
o
w
Lo
w
H
i
g
h
B
a
t
t
e
r
y
M
e
d
i
u
m
M
e
d
i
u
m
M
e
d
i
u
m
B
a
l
a
n
c
e
d
H
i
g
h
H
i
g
h
Lo
w
R
e
g
e
n
o
n
l
y
2
.
3
.
P
SO
-
b
a
s
ed
o
ptim
iz
a
t
io
n
o
f
f
uzzy
pa
r
a
m
et
er
s
PS
O
is
u
s
ed
to
o
p
tim
ize
th
e
s
h
ap
e
an
d
p
ar
am
eter
s
o
f
all
f
u
zz
y
m
em
b
er
s
h
ip
f
u
n
cti
o
n
s
.
T
h
e
o
p
tim
izatio
n
g
o
al
is
to
m
in
im
ize
to
tal
en
er
g
y
c
o
n
s
u
m
p
tio
n
an
d
m
a
x
im
ize
b
atter
y
So
C
r
e
ten
tio
n
th
r
o
u
g
h
o
u
t
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
.
2
,
J
u
n
e
20
2
6
:
1
0
2
5
-
1035
1028
th
e
d
r
iv
e
c
y
cle.
T
h
e
f
itn
ess
f
u
n
ctio
n
is
f
o
r
m
u
lated
as sh
o
wn
in
(
3
)
:
=
∝
1
+
̅
̅
̅
̅
̅
̅
(
3
)
W
h
er
e:
E
total
=
∑P
batt
⋅
Δ
t is th
e
to
tal
en
er
g
y
d
r
awn
f
r
o
m
th
e
b
atter
y
.
̅
̅
̅
̅
̅
̅
=
∑
=
1
is
th
e
av
er
ag
e
So
C
ac
r
o
s
s
all
tim
e
s
tep
s
.
α
=β=0
.
5
ar
e
t
h
e
weig
h
ts
f
o
r
b
alan
cin
g
th
e
two
o
b
jectiv
es.
T
h
e
PS
O
alg
o
r
ith
m
u
p
d
ates e
a
ch
p
ar
ticle’
s
v
elo
city
a
n
d
p
o
s
itio
n
u
s
in
g
(
4
)
a
n
d
(
5
)
as sh
o
wn
:
+
1
=
.
+
1
.
1
.
(
,
−
)
+
2
.
2
.
(
,
−
)
(
4
)
+
1
=
+
+
1
(
5
)
W
h
er
e
w:
in
er
tia
weig
h
t
,
c
1
,c
2
:
ac
ce
ler
atio
n
c
o
ef
f
icien
ts
,
a
n
d
r
1
,
r
2
∼
Un
if
o
r
m
(
0
,
1
)
.
T
h
e
PS
O
p
ar
am
eter
s
u
s
ed
ar
e
s
u
m
m
ar
ized
in
T
ab
le
2
.
T
ab
le
2
.
Par
ticle
s
war
m
o
p
tim
izatio
n
p
ar
am
eter
v
alu
es
P
a
r
a
me
t
e
r
S
y
mb
o
l
V
a
l
u
e
N
u
mb
e
r
o
f
p
a
r
t
i
c
l
e
s
N
p
30
N
u
mb
e
r
o
f
i
t
e
r
a
t
i
o
n
s
N
iter
1
0
0
I
n
e
r
t
i
a
w
e
i
g
h
t
W
0
.
7
C
o
g
n
i
t
i
v
e
c
o
e
f
f
i
c
i
e
n
t
C
1
1
.
5
S
o
c
i
a
l
c
o
e
f
f
i
c
i
e
n
t
C
2
1
.
5
O
p
t
i
mi
z
a
t
i
o
n
b
o
u
n
d
s
—
Tr
i
a
n
g
u
l
a
r
mf
r
a
n
g
e
s
2
.
4
.
Sim
ula
t
i
o
n e
nv
iro
nm
en
t
T
h
e
en
tire
E
MS
lo
g
ic
is
im
p
le
m
en
ted
in
Py
th
o
n
3
.
1
0
u
s
in
g
Go
o
g
le
C
o
lab
f
o
r
s
ea
m
less
co
m
p
u
tatio
n
.
T
h
e
f
o
llo
win
g
lib
r
ar
ies
an
d
to
o
ls
ar
e
u
s
ed
:
i)
Nu
m
Py
f
o
r
n
u
m
er
ical
o
p
er
atio
n
s
,
ii)
S
cik
it
-
f
u
zz
y
(
s
k
f
u
zz
y
)
f
o
r
f
u
zz
y
l
o
g
ic
d
esig
n
,
iii)
M
atp
l
o
tlib
f
o
r
r
ea
l
-
tim
e
p
lo
ttin
g
an
d
r
esu
lt
v
is
u
aliza
tio
n
,
an
d
iv
)
m
u
ltip
r
o
ce
s
s
in
g
f
o
r
p
ar
allel
PS
O
o
p
tim
izatio
n
.
T
h
e
en
tire
E
MS
is
im
p
lem
en
t
ed
in
Py
th
o
n
3
.
1
0
u
s
in
g
Go
o
g
le
C
o
lab
.
Simu
latio
n
is
ca
r
r
ied
o
u
t
o
v
er
th
e
Ur
b
an
D
y
n
am
o
m
eter
Dr
i
v
in
g
Sch
ed
u
le
(
UDDS)
,
wh
i
ch
s
p
an
s
1
3
6
9
s
ec
o
n
d
s
with
r
ea
l
-
wo
r
ld
t
r
af
f
ic
co
n
d
itio
n
s
.
T
h
e
So
C
d
y
n
am
ics
f
o
r
ea
c
h
tim
e
s
tep
ar
e
m
o
d
ele
d
as p
r
esen
ted
in
(
6
)
:
+
1
=
+
(
)
.
∆
+
(
)
.
.
∆
(
6
)
wh
er
e
η
r
eg
en
≈
0
.
8
5
is
r
eg
en
er
ativ
e
ef
f
icien
c
y
,
a
n
d
E
n
o
m
in
al
is
b
atter
y
ca
p
ac
ity
in
k
W
h
.
T
h
e
o
v
e
r
all
p
o
wer
b
alan
ce
p
er
tim
e
s
tep
is
p
r
esen
ted
in
(
7
)
:
=
+
+
(
7
)
T
h
e
s
im
u
latio
n
is
ev
alu
ated
u
s
in
g
th
e
Ur
b
an
Dy
n
am
o
m
eter
Dr
iv
in
g
Sch
ed
u
le
(
UDDS)
d
r
iv
e
cy
cle
,
wh
ich
s
p
an
s
1
3
6
9
s
ec
o
n
d
s
with
v
ar
iab
le
s
p
ee
d
s
an
d
s
to
p
-
s
tar
t
co
n
d
itio
n
s
.
Simu
latio
n
in
p
u
ts
an
d
r
an
g
es
ar
e
p
r
o
v
id
e
d
i
n
T
a
b
le
3
.
Mu
ltip
l
e
s
im
u
latio
n
s
ar
e
co
n
d
u
cted
f
o
r
d
if
f
er
e
n
t
in
itial
So
C
le
v
els
(
e.
g
.
,
4
0
%,
6
0
%,
8
0
%),
r
o
a
d
s
lo
p
es,
an
d
r
an
d
o
m
lo
ad
v
a
r
iatio
n
s
to
ev
alu
ate
c
o
n
tr
o
ller
r
o
b
u
s
tn
ess
.
T
ab
le
3
.
Simu
latio
n
i
n
p
u
t
p
ar
a
m
eter
r
an
g
es
P
a
r
a
me
t
e
r
S
y
mb
o
l
R
a
n
g
e
/
v
a
l
u
e
U
n
i
t
V
e
h
i
c
l
e
s
p
e
e
d
V
0
–
1
2
0
k
m/
h
S
t
a
t
e
-
of
-
c
h
a
r
g
e
S
o
C
2
0
–
100
%
Lo
a
d
p
o
w
e
r
d
e
m
a
n
d
P
l
oa
d
0
–
25
kW
G
r
a
d
i
e
n
t
l
e
v
e
l
G
–
1
0
t
o
+
1
0
%
S
i
mu
l
a
t
i
o
n
t
i
me
st
e
p
Δt
1
sec
B
a
t
t
e
r
y
o
u
t
p
u
t
p
o
w
e
r
P
ba
t
t
0
–
25
kW
R
e
g
e
n
b
r
a
k
i
n
g
p
o
w
e
r
P
re
ge
n
0
–
10
kW
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
Mu
lti
-
o
b
jective
en
erg
y
ma
n
a
g
eme
n
t o
p
timiz
a
tio
n
in
elec
tr
ic
ve
h
icles u
s
in
g
fu
z
z
y
lo
g
ic
…
(
V
.
La
ksh
mi
Dev
i
)
1029
3.
RE
SU
L
T
S AN
D
D
I
SCU
SS
I
O
N
T
h
is
s
ec
tio
n
p
r
esen
ts
th
e
s
im
u
latio
n
-
b
ased
e
v
alu
atio
n
o
f
th
e
p
r
o
p
o
s
ed
Fu
zz
y
-
PS
O
h
y
b
r
i
d
E
MS
f
o
r
elec
tr
ic
v
eh
icles
u
n
d
er
th
e
s
tan
d
ar
d
Ur
b
a
n
Dy
n
am
o
m
eter
Dr
iv
in
g
Sch
ed
u
le
(
UDDS)
.
T
h
e
p
er
f
o
r
m
an
ce
is
ass
es
s
ed
b
ased
o
n
th
e
f
u
zz
y
c
o
n
tr
o
ller
’
s
b
eh
av
i
o
r
,
PS
O
o
p
ti
m
izatio
n
p
e
r
f
o
r
m
an
ce
,
en
er
g
y
ef
f
icien
cy
m
etr
ics,
an
d
a
co
m
p
ar
ativ
e
e
v
alu
atio
n
ag
ain
s
t b
aselin
e
E
MS
s
tr
ateg
ies.
3
.
1
.
F
uzzy
co
ntr
o
ller
o
utput
a
nd
E
M
S su
rf
a
ce
beha
v
io
r
T
h
e
b
eh
av
io
r
o
f
th
e
f
u
zz
y
c
o
n
tr
o
ller
is
illu
s
tr
ated
in
F
ig
u
r
e
3
as
a
h
ea
tm
ap
o
f
p
o
wer
-
s
p
lit
d
ec
is
io
n
s
o
v
er
a
g
r
id
o
f
So
C
an
d
v
eh
icl
e
s
p
ee
d
in
p
u
ts
.
T
h
e
co
n
tr
o
ller
d
is
tin
g
u
is
h
es
b
etwe
en
b
atter
y
-
d
o
m
in
an
t
an
d
I
C
E
-
d
o
m
in
an
t r
e
g
io
n
s
,
with
o
p
tim
al
elec
tr
ic
d
r
iv
e
o
p
er
atio
n
o
cc
u
r
r
in
g
in
m
id
-
s
p
ee
d
an
d
m
i
d
-
So
C
r
eg
io
n
s
.
T
h
e
3
D
s
u
r
f
ac
e
p
lo
t
i
n
Fig
u
r
e
4
f
u
r
th
er
h
i
g
h
lig
h
ts
th
is
d
y
n
am
i
c
m
o
d
u
latio
n
,
wh
e
r
e
s
m
o
o
t
h
g
r
a
d
ien
ts
r
ef
lect
ap
p
r
o
p
r
iate
tr
an
s
itio
n
s
b
etwe
en
co
n
tr
o
l
d
ec
is
io
n
s
.
A
s
u
m
m
ar
y
o
f
th
e
E
MS
o
u
tp
u
t
s
tatis
tics
is
p
r
esen
ted
in
T
ab
le
4
,
s
h
o
win
g
a
m
ea
n
o
u
t
p
u
t v
alu
e
n
ea
r
ze
r
o
with
ex
p
ec
t
ed
v
ar
iatio
n
s
ac
r
o
s
s
th
e
So
C
-
s
p
ee
d
r
an
g
e.
Fig
u
r
e
3
.
E
MS
o
u
tp
u
t
h
ea
tm
a
p
(
So
C
v
s
.
s
p
ee
d
,
n
o
r
m
alize
d
o
u
tp
u
t)
Fig
u
r
e
4
.
3
D
Su
r
f
ac
e
o
f
E
MS
o
u
tp
u
t (
So
C
v
s
.
s
p
ee
d
v
s
.
p
o
wer
s
p
lit
)
T
ab
le
4
.
Fu
zz
y
E
MS
o
u
tp
u
t su
m
m
ar
y
s
tatis
tics
S
t
a
t
i
st
i
c
S
o
C
(
%)
S
p
e
e
d
(
k
m/
h
)
P
o
w
e
r
s
p
l
i
t
C
o
u
n
t
1
0
0
1
0
0
40
M
e
a
n
5
5
.
0
0
6
5
.
0
0
−
0
.
0
1
2
5
S
t
a
n
d
a
r
d
d
e
v
i
a
t
i
o
n
2
8
.
8
7
3
5
.
2
8
0
.
4
4
6
M
i
n
1
0
.
0
0
1
0
.
0
0
−
0
.
5
M
a
x
1
0
0
.
0
0
1
2
0
.
0
0
+
0
.
5
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
.
2
,
J
u
n
e
20
2
6
:
1
0
2
5
-
1035
1030
3
.
2
.
P
SO
o
ptim
iza
t
i
o
n per
f
o
rm
a
nce
a
nd
E
M
S e
f
f
iciency
PS
O
was
ap
p
lied
to
d
y
n
am
ic
ally
tu
n
e
th
e
tr
ian
g
u
lar
m
em
b
er
s
h
ip
f
u
n
ctio
n
p
ar
am
ete
r
s
o
f
th
e
f
u
zz
y
lo
g
ic
co
n
tr
o
ller
.
T
h
e
o
b
jectiv
e
was
to
m
in
im
ize
to
tal
en
er
g
y
co
n
s
u
m
p
tio
n
wh
ile
m
ain
tain
in
g
ad
eq
u
ate
b
atter
y
So
C
ac
r
o
s
s
v
ar
y
in
g
d
r
iv
e
c
o
n
d
itio
n
s
.
T
h
e
o
p
tim
ized
f
u
zz
y
s
u
r
f
ac
e
is
v
is
u
alize
d
th
r
o
u
g
h
a
co
n
to
u
r
m
ap
s
h
o
wn
in
Fig
u
r
e
5
,
wh
er
e
th
e
b
lack
m
ar
k
er
in
d
icate
s
th
e
PS
O
-
d
er
iv
ed
o
p
tim
al
co
n
tr
o
l p
o
in
t (
So
C
≈
5
2
.
2
6
%,
Sp
ee
d
≈
4
2
.
2
k
m
/h
)
.
T
h
e
o
p
tim
izer
s
u
cc
ess
f
u
lly
co
n
v
e
r
g
ed
with
in
4
2
iter
atio
n
s
,
r
ef
in
i
n
g
th
e
f
u
zz
y
d
ec
is
io
n
s
p
ac
e
f
o
r
im
p
r
o
v
e
d
co
n
tr
o
l
p
r
ec
is
io
n
.
At
a
f
ix
ed
v
eh
icle
s
p
ee
d
o
f
6
0
k
m
/h
,
th
e
r
elatio
n
s
h
ip
b
etw
ee
n
So
C
an
d
p
o
wer
s
p
lit
o
u
tp
u
t
is
s
h
o
wn
i
n
Fig
u
r
e
6
,
d
em
o
n
s
tr
atin
g
th
e
co
n
tr
o
lle
r
’
s
n
o
n
-
lin
ea
r
r
esp
o
n
s
e
as
So
C
tr
an
s
itio
n
s
ac
r
o
s
s
lo
w,
m
ed
iu
m
,
an
d
h
ig
h
s
tates.
Fig
u
r
e
5
.
C
o
n
to
u
r
m
a
p
with
P
SO
-
o
p
tim
ized
co
n
tr
o
l p
o
in
t
Fig
u
r
e
6
.
E
MS
Ou
tp
u
t v
s
.
So
C
at
6
0
k
m
/
h
T
h
is
s
ig
m
o
id
-
lik
e
b
e
h
av
io
r
s
u
p
p
o
r
ts
b
alan
ce
d
e
n
er
g
y
allo
ca
tio
n
an
d
im
p
r
o
v
es
b
atter
y
u
tili
za
tio
n
u
n
d
er
s
tead
y
-
s
p
ee
d
co
n
d
itio
n
s
.
Hig
h
-
ef
f
icien
cy
r
e
g
io
n
s
ar
e
o
b
s
er
v
ed
b
etwe
en
So
C
v
al
u
es
o
f
4
5
–
6
5
%
an
d
v
eh
icle
s
p
ee
d
s
r
an
g
i
n
g
f
r
o
m
4
0
to
8
0
k
m
/h
.
T
h
ese
o
p
e
r
atio
n
al
zo
n
es c
o
r
r
esp
o
n
d
to
o
p
tim
al
en
er
g
y
co
n
v
er
s
io
n
s
ce
n
ar
io
s
,
co
n
f
ir
m
i
n
g
th
e
e
f
f
e
ctiv
en
ess
o
f
PS
O
-
b
ased
f
u
zz
y
tu
n
in
g
in
p
r
ac
tical
E
V
d
r
i
v
in
g
co
n
d
itio
n
s
.
T
o
ass
ess
r
o
b
u
s
tn
ess
,
a
co
m
p
r
eh
en
s
iv
e
s
en
s
itiv
ity
s
tu
d
y
w
as
co
n
d
u
cted
b
y
v
ar
y
in
g
k
ey
PS
O
an
d
f
u
zz
y
p
a
r
am
eter
s
.
T
h
e
in
e
r
tia
weig
h
t
(
w)
was
s
wep
t
b
etwe
en
0
.
5
an
d
0
.
9
,
an
d
th
e
c
o
g
n
itiv
e
an
d
s
o
cial
co
ef
f
icien
ts
(
c1
,
c
2
)
wer
e
v
ar
i
ed
f
r
o
m
1
.
2
to
2
.
0
.
T
h
e
o
p
tim
izer
m
ain
tain
ed
s
tab
le
co
n
v
er
g
en
ce
with
in
4
0
–
50
iter
atio
n
s
with
less
th
an
2
%
v
ar
iatio
n
in
to
tal
e
n
er
g
y
c
o
n
s
u
m
p
tio
n
.
I
n
ad
d
itio
n
,
t
h
e
wid
t
h
s
o
f
th
e
tr
ian
g
u
la
r
m
em
b
er
s
h
ip
f
u
n
ctio
n
s
wer
e
p
er
tu
r
b
ed
b
y
±
1
0
%
to
ev
alu
ate
th
e
im
p
ac
t
o
n
th
e
f
u
zz
y
r
u
le
b
ase.
T
h
e
r
esu
ltin
g
d
ev
iatio
n
in
th
e
PDR
av
er
ag
ed
b
elo
w
1
.
5
%,
co
n
f
ir
m
in
g
t
h
at
th
e
co
n
tr
o
ller
r
em
ain
s
in
s
en
s
itiv
e
to
m
o
d
er
ate
m
em
b
er
s
h
ip
d
is
to
r
tio
n
s
.
T
o
e
m
u
late
s
en
s
o
r
in
ac
c
u
r
ac
ies,
ze
r
o
-
m
ea
n
Gau
s
s
ian
n
o
is
e
o
f
±
5
%
was
in
jecte
d
in
to
th
e
So
C
an
d
s
p
ee
d
in
p
u
ts
;
th
e
co
n
tr
o
ller
o
u
tp
u
t
d
ev
iatio
n
s
tay
ed
with
in
2
%,
d
em
o
n
s
tr
atin
g
s
tr
o
n
g
r
esil
ien
ce
to
m
ea
s
u
r
em
en
t
n
o
is
e
an
d
p
ar
am
eter
d
r
if
t.
3.
3
.
So
C
re
g
ula
t
io
n a
nd
ener
g
y
perf
o
r
m
a
nce
un
der
UDDS
T
h
e
p
r
o
p
o
s
e
d
E
M
S
s
t
r
a
t
e
g
i
e
s
w
e
r
e
e
v
a
l
u
a
t
e
d
u
s
i
n
g
t
h
e
U
r
b
a
n
D
y
n
a
m
o
m
e
t
e
r
D
r
i
v
i
n
g
S
c
h
e
d
u
l
e
(
U
D
D
S
)
t
o
s
i
m
u
l
a
t
e
r
e
a
l
i
s
t
i
c
v
e
h
i
c
l
e
o
p
e
r
a
t
i
o
n
c
o
n
d
i
t
i
o
n
s
.
T
h
e
s
y
s
t
e
m
'
s
a
b
i
l
i
t
y
t
o
r
e
g
u
l
a
t
e
b
a
t
t
e
r
y
S
o
C
u
n
d
e
r
d
y
n
a
m
i
c
l
o
a
d
a
n
d
s
p
e
e
d
i
n
p
u
t
s
w
a
s
a
k
e
y
p
e
r
f
o
r
m
a
n
c
e
c
r
i
t
e
r
i
o
n
.
F
i
g
u
r
e
7
i
l
l
u
s
t
r
a
t
e
s
t
h
e
S
o
C
p
r
o
f
i
l
e
s
o
f
t
h
r
e
e
e
n
e
r
g
y
m
a
n
a
g
e
m
e
n
t
s
t
r
a
t
e
g
i
e
s
:
c
o
n
v
e
n
t
i
o
n
a
l
r
u
l
e
-
b
a
s
e
d
E
M
S
,
f
u
z
z
y
l
o
g
i
c
c
o
n
t
r
o
l
l
e
r
,
a
n
d
t
h
e
p
r
o
p
o
s
e
d
P
S
O
-
o
p
t
i
m
i
z
e
d
f
u
z
z
y
E
M
S
.
T
h
e
P
S
O
-
o
p
t
i
m
i
z
e
d
c
o
n
t
r
o
l
l
e
r
m
a
i
n
t
a
i
n
e
d
S
o
C
a
b
o
v
e
3
6
.
2
%
,
c
o
m
p
a
r
e
d
t
o
3
3
.
7
%
f
o
r
t
h
e
f
u
z
z
y
c
o
n
t
r
o
l
l
e
r
a
n
d
j
u
s
t
2
8
.
4
%
f
o
r
t
h
e
c
o
n
v
e
n
t
i
o
n
a
l
r
u
l
e
-
b
a
s
e
d
a
p
p
r
o
a
c
h
.
T
h
i
s
i
n
d
i
c
a
t
e
s
s
u
p
e
r
i
o
r
b
a
t
t
e
r
y
u
t
i
l
i
z
a
t
i
o
n
a
n
d
r
e
d
u
c
e
d
d
e
p
t
h
-
of
-
d
i
s
c
h
a
r
g
e
,
w
h
i
c
h
c
o
n
t
r
i
b
u
t
e
s
t
o
l
o
n
g
e
r
b
a
t
t
e
r
y
l
i
f
e
.
I
n
t
e
r
m
s
o
f
e
n
e
r
g
y
u
s
a
g
e
,
t
h
e
t
o
t
a
l
e
n
e
r
g
y
c
o
n
s
u
m
e
d
b
y
e
a
c
h
E
M
S
s
t
r
a
t
e
g
y
i
s
p
r
e
s
e
n
t
e
d
i
n
T
a
b
l
e
5
.
T
h
e
P
S
O
-
o
p
t
i
m
i
z
e
d
f
u
z
z
y
E
M
S
c
o
n
s
u
m
e
d
o
n
l
y
3
6
5
8
.
9
9
W
h
,
o
f
f
e
r
i
n
g
a
s
i
g
n
i
f
i
c
a
n
t
r
e
d
u
c
t
i
o
n
c
o
m
p
a
r
e
d
t
o
t
h
e
c
o
n
v
e
n
t
i
o
n
a
l
s
y
s
t
e
m
’
s
5
2
0
4
.
3
1
W
h
.
T
o
f
u
r
th
e
r
ass
ess
en
er
g
y
ef
f
icien
cy
,
T
ab
le
6
p
r
o
v
i
d
es
th
e
co
r
r
esp
o
n
d
in
g
d
is
tan
ce
-
p
er
-
e
n
e
r
g
y
v
alu
es
f
o
r
ea
ch
E
MS
v
ar
ia
n
t.
T
h
e
p
r
o
p
o
s
ed
co
n
tr
o
ller
ac
h
iev
e
d
an
ef
f
icien
cy
o
f
8
.
2
k
m
/k
W
h
,
o
u
tp
er
f
o
r
m
in
g
b
o
th
th
e
f
u
zz
y
lo
g
ic
c
o
n
tr
o
ller
(
7
.
3
k
m
/k
W
h
)
a
n
d
th
e
co
n
v
en
tio
n
al
ap
p
r
o
ac
h
(
5
.
7
k
m
/k
W
h
)
.
A
co
n
s
o
lid
ated
v
iew
o
f
all
k
ey
p
er
f
o
r
m
an
ce
m
etr
ic
s
is
p
r
o
v
id
ed
in
T
ab
le
7
.
I
t
co
m
p
ar
es
So
C
r
eg
u
latio
n
,
to
tal
en
er
g
y
co
n
s
u
m
p
tio
n
,
ef
f
icien
cy
,
e
n
er
g
y
s
av
in
g
s
p
e
r
ce
n
tag
e,
PS
O
co
n
v
er
g
en
ce
it
er
atio
n
s
,
an
d
av
er
a
g
e
p
o
wer
s
p
lit
ac
cu
r
ac
y
.
T
h
e
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
Mu
lti
-
o
b
jective
en
erg
y
ma
n
a
g
eme
n
t o
p
timiz
a
tio
n
in
elec
tr
ic
ve
h
icles u
s
in
g
fu
z
z
y
lo
g
ic
…
(
V
.
La
ksh
mi
Dev
i
)
1031
r
esu
lts
co
n
f
ir
m
th
at
th
e
Fu
zz
y
-
PS
O
E
MS
co
n
s
is
ten
tly
o
u
tp
er
f
o
r
m
s
th
e
o
t
h
er
s
tr
ateg
ies ac
r
o
s
s
all
p
ar
am
eter
s
.
T
h
ese
r
es
u
lts
c
o
n
f
i
r
m
t
h
at
th
e
F
u
z
zy
-
PS
O
E
MS
e
n
h
a
n
ce
s
e
n
e
r
g
y
m
a
n
ag
em
en
t,
p
o
w
er
d
i
s
tr
i
b
u
ti
o
n
,
an
d
e
f
f
ici
e
n
c
y
w
h
il
e
r
e
m
a
in
in
g
s
u
ita
b
l
e
f
o
r
r
e
al
-
ti
m
e
em
b
e
d
d
e
d
E
V
ap
p
l
ic
ati
o
n
s
.
T
h
e
f
u
z
z
y
i
n
f
er
e
n
ce
r
u
n
s
o
n
lo
w
-
c
o
s
t
m
i
cr
o
c
o
n
t
r
o
ll
er
s
i
n
~
1
.
6
m
s
p
er
cy
cl
e,
w
it
h
PS
O
e
x
ec
u
te
d
o
f
f
l
in
e
t
o
a
v
o
i
d
r
u
n
ti
m
e
l
o
a
d
.
Pr
ec
o
m
p
u
t
ed
lo
o
k
u
p
ta
b
l
es
r
ed
u
c
e
la
te
n
c
y
an
d
m
i
ti
g
at
e
q
u
a
n
t
iz
ati
o
n
o
r
th
e
r
m
al
e
f
f
e
cts.
B
u
il
t
-
i
n
a
n
o
m
al
y
c
h
e
ck
s
r
e
v
e
r
t
co
n
t
r
o
l
t
o
a
c
o
n
s
er
v
ati
v
e
m
o
d
e
w
h
en
S
o
C
o
r
s
p
ee
d
d
ev
iat
e
b
e
y
o
n
d
±
1
0
%,
e
n
s
u
r
i
n
g
s
a
f
e
t
y
.
S
en
s
iti
v
it
y
tes
ts
wit
h
±
1
0
%
n
o
is
e
c
au
s
e
d
<
2
%
v
a
r
i
ati
o
n
i
n
o
u
t
p
u
t
,
d
em
o
n
s
t
r
a
t
in
g
r
o
b
u
s
t
n
ess
.
Fu
tu
r
e
h
ar
d
w
a
r
e
-
in
-
th
e
-
l
o
o
p
t
ests
will
v
ali
d
a
te
f
a
u
lt
t
o
le
r
a
n
ce
u
n
d
e
r
r
ea
l
c
o
m
m
u
n
ic
ati
o
n
d
ela
y
s
a
n
d
co
m
p
o
n
en
t
ag
in
g
.
Fig
u
r
e
7
.
So
C
co
m
p
ar
is
o
n
u
n
d
er
th
e
UDDS
d
r
iv
e
cy
cle
T
ab
le
5
.
T
o
tal
en
er
g
y
co
n
s
u
m
ed
(
W
h
)
u
n
d
er
ea
c
h
E
MS
s
tr
ateg
y
EM
S
S
t
r
a
t
e
g
y
En
e
r
g
y
c
o
n
su
m
e
d
(
W
h
)
C
o
n
v
e
n
t
i
o
n
a
l
r
u
l
e
-
b
a
s
e
d
5
2
0
4
.
3
1
F
u
z
z
y
l
o
g
i
c
c
o
n
t
r
o
l
l
e
r
4
1
1
2
.
5
2
F
u
z
z
y
-
p
so
o
p
t
i
mi
z
e
d
3
6
5
8
.
9
9
T
ab
le
6
.
E
n
er
g
y
ef
f
icien
c
y
(
k
m
/k
W
h
)
o
f
E
MS
s
tr
ateg
ies
EM
S
s
t
r
a
t
e
g
y
Ef
f
i
c
i
e
n
c
y
(
k
m
/
k
W
h
)
C
o
n
v
e
n
t
i
o
n
a
l
r
u
l
e
-
b
a
s
e
d
5
.
7
F
u
z
z
y
l
o
g
i
c
c
o
n
t
r
o
l
l
e
r
7
.
3
F
u
z
z
y
-
P
S
O
o
p
t
i
m
i
z
e
d
8
.
2
T
ab
le
7
.
Per
f
o
r
m
an
ce
co
m
p
a
r
is
o
n
o
f
E
MS
s
tr
ateg
ies
M
e
t
r
i
c
C
o
n
v
e
n
t
i
o
n
a
l
E
M
S
F
u
z
z
y
l
o
g
i
c
EM
S
F
u
z
z
y
-
P
S
O
E
M
S
S
o
C
mi
n
i
m
u
m (
%)
2
8
.
4
3
3
.
7
3
6
.
2
To
t
a
l
e
n
e
r
g
y
c
o
n
s
u
m
e
d
(
w
h
)
5
2
0
4
.
3
1
4
1
1
2
.
5
2
3
6
5
8
.
9
9
Ef
f
i
c
i
e
n
c
y
(
k
m
/
k
w
h
)
5
.
7
7
.
3
8
.
2
En
e
r
g
y
sa
v
i
n
g
s (%)
—
2
1
.
0
%
2
9
.
7
%
P
S
O
c
o
n
v
e
r
g
e
n
c
e
i
t
e
r
a
t
i
o
n
—
—
42
A
v
g
.
p
o
w
e
r
sp
l
i
t
a
c
c
u
r
a
c
y
Lo
w
M
e
d
i
u
m
H
i
g
h
3
.
4
.
C
o
m
pu
t
a
t
i
o
na
l r
un
t
im
e
a
nd
m
em
o
r
y
pro
f
ilin
g
T
o
ev
alu
ate
r
ea
l
-
tim
e
f
ea
s
ib
ilit
y
,
r
u
n
tim
e
an
d
m
em
o
r
y
p
r
o
f
ilin
g
wer
e
p
er
f
o
r
m
ed
f
o
r
e
ac
h
E
MS
v
ar
ian
t
u
s
in
g
Py
th
o
n
3
.
1
0
o
n
a
C
o
r
e
i5
(
2
.
4
GHz
,
8
GB
R
AM
)
p
latf
o
r
m
.
T
ab
le
8
s
u
m
m
ar
izes
th
e
av
er
ag
e
co
m
p
u
tatio
n
tim
e
p
er
co
n
tr
o
l
s
tep
,
to
tal
s
im
u
latio
n
tim
e,
an
d
m
em
o
r
y
u
tili
za
tio
n
.
T
h
e
f
u
z
zy
-
PS
O
co
n
tr
o
ller
in
cr
ea
s
es
co
m
p
u
tatio
n
tim
e
b
y
o
n
l
y
≈
0
.
3
m
s
p
er
s
tep
co
m
p
ar
ed
with
th
e
b
aselin
e
FLC
wh
ile
r
em
ain
in
g
f
ar
b
elo
w
th
e
5
0
m
s
r
ea
l
-
tim
e
th
r
esh
o
ld
ty
p
ical
o
f
E
V
E
MS
lo
o
p
s
.
Peak
m
em
o
r
y
u
s
ag
e
d
u
r
in
g
PS
O
o
p
tim
izatio
n
was ≈
4
4
MB,
co
n
f
ir
m
in
g
s
u
it
ab
ilit
y
f
o
r
em
b
ed
d
e
d
d
e
p
lo
y
m
en
t.
T
ab
le
8
.
R
u
n
tim
e
a
n
d
m
em
o
r
y
p
r
o
f
ilin
g
o
f
E
MS
s
tr
ateg
ies u
n
d
er
a
Py
th
o
n
s
im
u
latio
n
en
v
i
r
o
n
m
en
t.
EM
S
s
t
r
a
t
e
g
y
A
v
g
.
s
t
e
p
t
i
me
(
ms)
To
t
a
l
s
i
m
u
l
a
t
i
o
n
t
i
me
(
s)
M
e
m
o
r
y
(
M
B
)
R
e
a
l
-
t
i
me
f
e
a
s
i
b
l
e
R
u
l
e
-
b
a
se
d
EM
S
1
.
1
1
.
4
2
1
1
.
2
Y
e
s
F
u
z
z
y
l
o
g
i
c
c
o
n
t
r
o
l
l
e
r
1
.
3
1
.
5
1
1
2
.
8
Y
e
s
F
u
z
z
y
-
P
S
O
o
p
t
i
m
i
z
e
d
1
.
6
1
.
6
7
1
3
.
9
Y
e
s
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
.
2
,
J
u
n
e
20
2
6
:
1
0
2
5
-
1035
1032
3
.
5
.
M
ulti
-
O
bje
ct
iv
e
O
pti
m
i
za
t
io
n a
nd
T
ra
de
-
O
f
f
Vis
ua
liza
t
io
n
T
h
e
p
r
o
p
o
s
ed
E
MS
s
im
u
ltan
eo
u
s
ly
m
in
im
izes
to
tal
en
er
g
y
co
n
s
u
m
p
tio
n
(
E
_
to
tal)
a
n
d
m
ax
im
izes
m
in
im
u
m
So
C
(
So
C
_
m
in
)
.
Fig
u
r
e
8
v
is
u
alize
s
th
is
tr
ad
e
-
o
f
f
as
a
Par
eto
f
r
o
n
t.
E
ac
h
p
o
in
t
co
r
r
esp
o
n
d
s
to
an
E
MS
s
tr
ateg
y
—
co
n
v
en
tio
n
al
r
u
le
-
b
ased
,
f
u
zz
y
lo
g
ic,
an
d
th
e
PS
O
-
o
p
tim
ized
h
y
b
r
id
.
T
h
e
PS
O
-
Fu
zz
y
co
n
tr
o
ller
lies
n
ea
r
th
e
k
n
ee
o
f
th
e
cu
r
v
e
(
E
_
to
tal
≈
3
.
6
6
k
W
h
,
So
C
_
m
in
≈
3
6
%),
r
ep
r
esen
tin
g
th
e
m
o
s
t
b
alan
ce
d
o
p
er
atin
g
r
eg
io
n
b
e
twee
n
ef
f
icien
cy
an
d
b
atter
y
p
r
o
tectio
n
.
T
h
e
PS
O
-
o
p
tim
iz
ed
f
u
zz
y
c
o
n
tr
o
ller
o
p
er
ates
n
ea
r
th
e
“k
n
ee
,
”
en
s
u
r
in
g
b
o
th
h
ig
h
ef
f
icie
n
cy
a
n
d
ad
eq
u
ate
So
C
m
ar
g
in
.
Op
tim
izer
s
tab
ilit
y
i
s
s
h
o
wn
in
Fig
u
r
e
9
,
wh
er
e
th
e
b
est
-
f
itn
ess
v
alu
e
r
em
ain
s
n
ea
r
ly
c
o
n
s
tan
t
af
te
r
≈
1
0
ite
r
atio
n
s
,
co
n
f
ir
m
in
g
s
m
o
o
th
co
n
v
er
g
e
n
ce
an
d
s
tab
le
tu
n
in
g
b
eh
av
i
o
u
r
.
Fig
u
r
e
8
.
Par
eto
f
r
o
n
t o
f
e
n
er
g
y
–
So
C
tr
ad
e
-
o
f
f
am
o
n
g
th
e
th
r
ee
E
MS
s
tr
ateg
ies
Fig
u
r
e
9
.
PS
O
co
n
v
er
g
en
ce
o
f
b
est f
itn
ess
f
o
r
f
u
zz
y
o
p
tim
iz
atio
n
4.
CO
NCLU
SI
O
N
T
h
is
p
ap
er
p
r
o
p
o
s
ed
a
h
y
b
r
i
d
f
u
zz
y
lo
g
ic
an
d
p
ar
ticle
s
war
m
o
p
tim
izatio
n
(
Fu
zz
y
-
PS
O)
b
ased
E
MS
f
o
r
elec
tr
ic
v
e
h
icles
to
en
h
an
c
e
en
er
g
y
ef
f
icien
cy
,
b
atter
y
lif
e,
an
d
p
o
wer
d
is
tr
ib
u
tio
n
u
n
d
er
d
y
n
a
m
ic
d
r
iv
in
g
co
n
d
itio
n
s
.
T
h
e
PS
O
-
tu
n
ed
f
u
zz
y
co
n
tr
o
ller
ad
ap
tiv
el
y
m
an
ag
ed
p
o
we
r
f
lo
w
b
ased
o
n
So
C
,
s
p
ee
d
,
an
d
lo
a
d
,
ac
h
iev
in
g
a
2
9
.
7
%
r
ed
u
ctio
n
in
to
tal
en
e
r
g
y
co
n
s
u
m
p
tio
n
an
d
a
4
4
%
im
p
r
o
v
em
en
t
in
e
f
f
icien
cy
u
n
d
e
r
th
e
UDDS
cy
cle.
T
h
e
o
p
tim
ized
f
u
zz
y
s
u
r
f
ac
es
p
r
o
v
id
ed
s
m
o
o
t
h
tr
an
s
itio
n
s
an
d
d
em
o
n
s
tr
ated
r
o
b
u
s
tn
ess
u
n
d
er
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
Mu
lti
-
o
b
jective
en
erg
y
ma
n
a
g
eme
n
t o
p
timiz
a
tio
n
in
elec
tr
ic
ve
h
icles u
s
in
g
fu
z
z
y
lo
g
ic
…
(
V
.
La
ksh
mi
Dev
i
)
1033
n
o
is
y
an
d
f
a
u
lt
-
d
is
tu
r
b
e
d
co
n
d
itio
n
s
,
m
ain
tain
in
g
So
C
a
b
o
v
e
3
5
%
an
d
r
e
d
u
cin
g
b
atter
y
s
tr
ess
.
C
o
m
p
ar
ativ
e
r
esu
lts
co
n
f
ir
m
e
d
th
e
s
u
p
er
io
r
ity
o
f
th
e
h
y
b
r
id
co
n
tr
o
ller
in
en
er
g
y
s
av
in
g
s
,
So
C
r
ete
n
tio
n
,
an
d
r
ea
l
-
tim
e
r
esp
o
n
s
iv
en
ess
,
wh
ile
b
alan
ci
n
g
en
e
r
g
y
ef
f
icien
c
y
an
d
So
C
p
r
eser
v
atio
n
as
s
h
o
wn
b
y
Par
eto
an
aly
s
is
.
Fu
tu
r
e
wo
r
k
will
f
o
cu
s
o
n
h
a
r
d
war
e
-
in
-
th
e
-
lo
o
p
v
alid
atio
n
an
d
in
teg
r
atio
n
o
f
d
etailed
elec
tr
o
-
t
h
er
m
al
an
d
ag
i
n
g
b
atter
y
m
o
d
els
f
o
r
ad
ap
tiv
e
d
e
r
atin
g
,
r
e
g
en
er
ativ
e
b
r
a
k
in
g
c
o
o
r
d
in
atio
n
,
a
n
d
p
r
ed
ictiv
e
h
e
alth
m
an
ag
em
e
n
t
in
m
u
lti
-
en
er
g
y
E
V
p
latf
o
r
m
s
.
T
h
e
f
r
am
ewo
r
k
will
also
b
e
ex
ten
d
ed
to
d
u
al
-
s
o
u
r
ce
co
n
f
ig
u
r
atio
n
s
co
m
b
in
in
g
b
atter
ies
an
d
s
u
p
er
ca
p
ac
ito
r
s
,
an
d
to
co
o
r
d
i
n
ated
s
m
ar
t
-
ch
a
r
g
in
g
an
d
v
eh
icle
-
to
-
g
r
i
d
(
V2
G)
en
er
g
y
ex
ch
a
n
g
e
f
o
r
g
r
id
-
in
ter
ac
tiv
e
elec
tr
ic
m
o
b
ilit
y
.
F
UNDING
I
NF
O
R
M
A
T
I
O
N
T
h
e
au
th
o
r
s
d
ec
lar
e
th
at
n
o
f
u
n
d
s
,
g
r
an
ts
,
o
r
o
th
e
r
s
u
p
p
o
r
t
wer
e
r
ec
eiv
ed
d
u
r
in
g
th
e
p
r
e
p
ar
atio
n
o
f
th
is
m
an
u
s
cr
ip
t.
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
V
.
L
ak
s
h
m
i D
ev
i
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
Dam
o
d
h
ar
R
ed
d
y
✓
✓
✓
✓
✓
✓
✓
✓
Srik
an
th
Velp
u
la
✓
✓
✓
✓
✓
✓
✓
✓
✓
K
.
Ku
m
ar
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
✓
B
asi
R
ed
d
y
Av
u
la
✓
✓
✓
✓
✓
✓
✓
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
CO
NF
L
I
C
T
O
F
I
N
T
E
R
E
S
T
ST
A
T
E
M
E
NT
T
h
e
au
th
o
r
s
s
tate
n
o
co
n
f
lict o
f
in
ter
est.
DATA AV
AI
L
AB
I
L
I
T
Y
T
h
e
d
ata
av
ailab
ilit
y
is
n
o
t
ap
p
licab
le
to
th
is
p
ap
er
as
n
o
n
e
w
d
ata
wer
e
cr
ea
ted
o
r
an
al
y
z
ed
in
th
is
s
tu
d
y
.
RE
F
E
R
E
NC
E
S
[
1
]
S
.
M
.
L
u
k
i
c
a
n
d
A
.
E
ma
d
i
,
“
Ef
f
e
c
t
s
o
f
d
r
i
v
e
t
r
a
i
n
h
y
b
r
i
d
i
z
a
t
i
o
n
o
n
f
u
e
l
e
c
o
n
o
my
a
n
d
d
y
n
a
m
i
c
p
e
r
f
o
r
m
a
n
c
e
o
f
p
a
r
a
l
l
e
l
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
,
”
I
EE
E
T
ra
n
s
a
c
t
i
o
n
s
o
n
V
e
h
i
c
u
l
a
r
T
e
c
h
n
o
l
o
g
y
,
v
o
l
.
5
3
,
n
o
.
2
,
p
p
.
3
8
5
–
3
8
9
,
M
a
r
.
2
0
0
4
,
d
o
i
:
1
0
.
1
1
0
9
/
TV
T
.
2
0
0
4
.
8
2
3
5
2
5
.
[
2
]
K
.
K
,
L
.
D
.
V
,
P
.
A
v
a
g
a
d
d
i
,
a
n
d
M
.
K
.
K
,
“
D
e
si
g
n
a
n
d
e
v
a
l
u
a
t
i
o
n
o
f
p
o
w
e
r
c
o
n
v
e
r
t
e
r
f
o
r
i
n
t
e
g
r
a
t
i
o
n
o
f
l
i
t
h
i
u
m
-
i
o
n
b
a
t
t
e
r
y
a
n
d
r
e
n
e
w
a
b
l
e
s
o
u
r
c
e
s
,
”
Re
s
u
l
t
s
i
n
E
n
g
i
n
e
e
ri
n
g
,
v
o
l
.
2
5
,
p
.
1
0
4
4
0
9
,
M
a
r
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
r
i
n
e
n
g
.
2
0
2
5
.
1
0
4
4
0
9
.
[
3
]
M
.
Eh
s
a
n
i
,
Y
.
G
a
o
,
S
.
E.
G
a
y
,
a
n
d
A
.
Ema
d
i
,
Mo
d
e
rn
e
l
e
c
t
ri
c
,
h
y
b
r
i
d
e
l
e
c
t
ri
c
,
a
n
d
f
u
e
l
c
e
l
l
v
e
h
i
c
l
e
s
.
C
R
C
P
r
e
ss,
2
0
0
4
,
d
o
i
:
1
0
.
1
2
0
1
/
9
7
8
1
4
2
0
0
3
7
7
3
9
.
[
4
]
A
.
S
c
i
a
r
r
e
t
t
a
a
n
d
L
i
n
o
G
u
z
z
e
l
l
a
,
“
C
o
n
t
r
o
l
o
f
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s,”
I
EEE
C
o
n
t
r
o
l
S
y
st
e
m
s
,
v
o
l
.
2
7
,
n
o
.
2
,
p
p
.
6
0
–
7
0
,
A
p
r
.
2
0
0
7
,
d
o
i
:
1
0
.
1
1
0
9
/
M
C
S
.
2
0
0
7
.
3
3
8
2
8
0
.
[
5
]
K
.
K
u
mar,
N
.
R
a
mes
h
B
a
b
u
,
a
n
d
K
.
R
.
P
r
a
b
h
u
,
“
A
n
a
l
y
si
s
o
f
i
n
t
e
g
r
a
t
e
d
b
o
o
st
-
c
u
k
h
i
g
h
v
o
l
t
a
g
e
g
a
i
n
D
C
-
D
C
c
o
n
v
e
r
t
e
r
w
i
t
h
R
B
F
N
M
P
P
T
f
o
r
s
o
l
a
r
P
V
a
p
p
l
i
c
a
t
i
o
n
,
”
2
0
1
7
I
n
n
o
v
a
t
i
o
n
s
i
n
P
o
w
e
r
a
n
d
A
d
v
a
n
c
e
d
C
o
m
p
u
t
i
n
g
T
e
c
h
n
o
l
o
g
i
e
s,
i
-
P
AC
T
2
0
1
7
,
v
o
l
.
2
0
1
7
-
Jan
u
a
r
y
,
p
p
.
1
–
6
,
2
0
1
7
,
d
o
i
:
1
0
.
1
1
0
9
/
I
P
A
C
T.
2
0
1
7
.
8
2
4
5
0
7
2
.
[
6
]
Ji
a
n
C
a
o
a
n
d
A
.
Em
a
d
i
,
“
A
n
e
w
b
a
t
t
e
r
y
/
u
l
t
r
a
c
a
p
a
c
i
t
o
r
h
y
b
r
i
d
e
n
e
r
g
y
s
t
o
r
a
g
e
sy
s
t
e
m
f
o
r
e
l
e
c
t
r
i
c
,
h
y
b
r
i
d
,
a
n
d
p
l
u
g
-
i
n
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
,
”
I
E
EE
T
r
a
n
s
a
c
t
i
o
n
s
o
n
P
o
w
e
r
E
l
e
c
t
r
o
n
i
c
s
,
v
o
l
.
2
7
,
n
o
.
1
,
p
p
.
1
2
2
–
1
3
2
,
J
a
n
.
2
0
1
2
,
d
o
i
:
1
0
.
1
1
0
9
/
TPE
L.
2
0
1
1
.
2
1
5
1
2
0
6
.
[
7
]
V
.
M
i
t
t
a
l
a
n
d
R
.
S
h
a
h
,
“
En
e
r
g
y
ma
n
a
g
e
m
e
n
t
st
r
a
t
e
g
i
e
s
f
o
r
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
:
a
t
e
c
h
n
o
l
o
g
y
r
o
a
d
ma
p
,
”
Wo
r
l
d
El
e
c
t
r
i
c
Ve
h
i
c
l
e
J
o
u
r
n
a
l
,
v
o
l
.
1
5
,
n
o
.
9
,
p
.
4
2
4
,
S
e
p
.
2
0
2
4
,
d
o
i
:
1
0
.
3
3
9
0
/
w
e
v
j
1
5
0
9
0
4
2
4
.
[
8
]
G
.
P
i
s
t
o
i
a
,
E
l
e
c
t
r
i
c
a
n
d
h
y
b
r
i
d
v
e
h
i
c
l
e
s:
P
o
w
e
r
so
u
r
c
e
s,
m
o
d
e
l
s,
s
u
st
a
i
n
a
b
i
l
i
t
y
,
i
n
f
r
a
s
t
ru
c
t
u
re
a
n
d
t
h
e
m
a
rke
t
.
2
0
1
0
,
d
o
i
:
1
0
.
1
0
1
6
/
C
2
0
0
9
-
0
-
3
0
6
6
9
-
8.
[
9
]
V
.
L.
D
e
v
i
,
K
.
K
,
S
.
R
.
K
i
r
a
n
,
a
n
d
N
.
M
.
G
i
r
i
s
h
K
u
m
a
r
,
“
A
n
a
l
y
si
s
o
f
e
n
e
r
g
y
m
a
n
a
g
e
me
n
t
s
y
st
e
m
i
n
m
i
c
r
o
g
r
i
d
o
p
e
r
a
t
i
o
n
s,
l
o
a
d
su
p
p
o
r
t
,
a
n
d
c
o
n
t
r
o
l
h
i
e
r
a
r
c
h
y
,
”
i
n
2
0
2
3
S
e
c
o
n
d
I
n
t
e
rn
a
t
i
o
n
a
l
C
o
n
f
e
re
n
c
e
o
n
T
ren
d
s
i
n
E
l
e
c
t
r
i
c
a
l
,
El
e
c
t
r
o
n
i
c
s,
a
n
d
C
o
m
p
u
t
e
r
En
g
i
n
e
e
ri
n
g
(
T
EE
C
C
O
N
)
,
A
u
g
.
2
0
2
3
,
p
p
.
1
3
–
16
,
d
o
i
:
1
0
.
1
1
0
9
/
TE
EC
C
O
N
5
9
2
3
4
.
2
0
2
3
.
1
0
3
3
5
8
5
9
.
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
.
2
,
J
u
n
e
20
2
6
:
1
0
2
5
-
1035
1034
[
1
0
]
S
.
J.
M
o
u
r
a
a
n
d
N
.
A
.
C
h
a
t
u
r
v
e
d
i
,
“
A
d
a
p
t
i
v
e
P
D
E
o
b
serv
e
r
f
o
r
b
a
t
t
e
r
y
S
O
C
/
S
O
H
e
st
i
ma
t
i
o
n
v
i
a
a
n
e
l
e
c
t
r
o
c
h
e
m
i
c
a
l
m
o
d
e
l
,
”
AS
M
E
2
0
1
2
5
t
h
An
n
u
a
l
D
y
n
a
m
i
c
S
y
st
e
m
s
a
n
d
C
o
n
t
r
o
l
C
o
n
f
e
re
n
c
e
j
o
i
n
t
w
i
t
h
t
h
e
J
S
ME
2
0
1
2
1
1
t
h
M
o
t
i
o
n
a
n
d
V
i
b
r
a
t
i
o
n
C
o
n
f
e
re
n
c
e
,
p
p
.
1
0
1
–
1
1
0
,
2
0
1
2
.
[
1
1
]
A
.
P
o
u
r
sam
a
d
a
n
d
M
.
M
o
n
t
a
z
e
r
i
,
“
D
e
si
g
n
o
f
g
e
n
e
t
i
c
-
f
u
z
z
y
c
o
n
t
r
o
l
st
r
a
t
e
g
y
f
o
r
p
a
r
a
l
l
e
l
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
,
”
C
o
n
t
r
o
l
En
g
i
n
e
e
ri
n
g
Pr
a
c
t
i
c
e
,
v
o
l
.
1
6
,
n
o
.
7
,
p
p
.
8
6
1
–
8
7
3
,
J
u
l
.
2
0
0
8
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
c
o
n
e
n
g
p
r
a
c
.
2
0
0
7
.
1
0
.
0
0
3
.
[
1
2
]
K
.
K
u
mar,
K
.
R
.
P
r
a
b
h
u
,
N
.
R
a
m
e
sh
B
a
b
u
,
a
n
d
P
.
S
a
n
j
e
e
v
i
k
u
m
a
r
,
“
A
n
o
v
e
l
s
i
x
-
sw
i
t
c
h
p
o
w
e
r
c
o
n
v
e
r
t
e
r
f
o
r
si
n
g
l
e
-
p
h
a
se
w
i
n
d
e
n
e
r
g
y
s
y
st
e
m a
p
p
l
i
c
a
t
i
o
n
s,
”
2
0
1
8
,
p
p
.
2
6
7
–
2
7
5
,
d
o
i
:
1
0
.
1
0
0
7
/
9
7
8
-
9
8
1
-
10
-
4
2
8
6
-
7
_
2
6
.
[
1
3
]
N
.
B
e
n
H
a
l
i
ma
,
N
.
B
e
n
H
a
d
j
,
M
.
C
h
a
i
e
b
,
a
n
d
R
.
N
e
j
i
,
“
E
n
e
r
g
y
ma
n
a
g
e
m
e
n
t
o
f
p
a
r
a
l
l
e
l
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
b
a
se
d
o
n
f
u
z
z
y
l
o
g
i
c
c
o
n
t
r
o
l
st
r
a
t
e
g
i
e
s,
”
J
o
u
r
n
a
l
o
f
C
i
rc
u
i
t
s,
S
y
st
e
m
s
a
n
d
C
o
m
p
u
t
e
rs
,
v
o
l
.
3
2
,
n
o
.
0
1
,
Ja
n
.
2
0
2
3
,
d
o
i
:
1
0
.
1
1
4
2
/
S
0
2
1
8
1
2
6
6
2
3
5
0
0
0
7
X
.
[
1
4
]
C
h
a
n
-
C
h
i
a
o
Li
n
,
H
u
e
i
P
e
n
g
,
a
n
d
J
.
W
.
G
r
i
z
z
l
e
,
“
A
s
t
o
c
h
a
s
t
i
c
c
o
n
t
r
o
l
st
r
a
t
e
g
y
f
o
r
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s,
”
i
n
Pro
c
e
e
d
i
n
g
s
o
f
t
h
e
2
0
0
4
Am
e
ri
c
a
n
C
o
n
t
ro
l
C
o
n
f
e
re
n
c
e
,
2
0
0
4
,
p
p
.
4
7
1
0
–
4
7
1
5
v
o
l
.
5
,
d
o
i
:
1
0
.
2
3
9
1
9
/
A
C
C
.
2
0
0
4
.
1
3
8
4
0
5
6
.
[
1
5
]
L.
D
.
V
a
n
d
K
.
K
,
“
I
n
t
e
g
r
a
t
e
d
LS
TM
a
n
d
r
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
f
r
a
mew
o
r
k
f
o
r
p
r
e
d
i
c
t
i
v
e
p
o
w
e
r
f
o
r
e
c
a
st
i
n
g
a
n
d
e
n
e
r
g
y
o
p
t
i
m
i
z
a
t
i
o
n
i
n
b
a
t
t
e
r
y
m
a
n
a
g
e
m
e
n
t
sy
s
t
e
ms
,
”
J
o
u
r
n
a
l
o
f
E
n
e
rg
y
S
t
o
r
a
g
e
,
v
o
l
.
1
3
8
,
p
.
1
1
8
6
6
6
,
D
e
c
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
s
t
.
2
0
2
5
.
1
1
8
6
6
6
.
[
1
6
]
C
.
B
a
b
u
,
D
.
D
i
n
e
s
h
K
u
mar,
K
.
K
u
mar,
K
.
J
y
o
t
h
e
e
sh
w
a
r
a
R
e
d
d
y
,
a
n
d
R
.
S
u
d
h
a
,
“
P
o
w
e
r
mo
n
i
t
o
r
i
n
g
a
n
d
c
o
n
t
r
o
l
s
y
s
t
e
m
f
o
r
med
i
u
m
v
o
l
t
a
g
e
sm
a
r
t
g
r
i
d
u
s
i
n
g
I
o
T
,
”
I
O
P
C
o
n
f
e
r
e
n
c
e
S
e
r
i
e
s:
Ma
t
e
r
i
a
l
s
S
c
i
e
n
c
e
a
n
d
En
g
i
n
e
e
r
i
n
g
,
v
o
l
.
9
0
6
,
n
o
.
1
,
p
.
0
1
2
0
0
7
,
A
u
g
.
2
0
2
0
,
d
o
i
:
1
0
.
1
0
8
8
/
1
7
5
7
-
8
9
9
X
/
9
0
6
/
1
/
0
1
2
0
0
7
.
[
1
7
]
X
.
H
u
,
S
.
L
i
,
a
n
d
H
.
P
e
n
g
,
“
A
c
o
m
p
a
r
a
t
i
v
e
st
u
d
y
o
f
e
q
u
i
v
a
l
e
n
t
c
i
r
c
u
i
t
m
o
d
e
l
s fo
r
L
i
-
i
o
n
b
a
t
t
e
r
i
e
s,
”
J
o
u
rn
a
l
o
f
P
o
w
e
r
S
o
u
r
c
e
s
,
v
o
l
.
1
9
8
,
p
p
.
3
5
9
–
3
6
7
,
Ja
n
.
2
0
1
2
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
j
p
o
w
so
u
r
.
2
0
1
1
.
1
0
.
0
1
3
.
[
1
8
]
H
.
S
h
u
,
“
H
y
b
r
i
d
e
n
e
r
g
y
s
t
o
r
a
g
e
s
y
st
e
m
f
o
r
i
n
t
e
l
l
i
g
e
n
t
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
i
n
c
o
r
p
o
r
a
t
i
n
g
i
m
p
r
o
v
e
d
P
S
O
a
l
g
o
r
i
t
h
m,
”
E
n
e
rg
y
I
n
f
o
rm
a
t
i
c
s
,
v
o
l
.
8
,
n
o
.
1
,
p
.
3
0
,
F
e
b
.
2
0
2
5
,
d
o
i
:
1
0
.
1
1
8
6
/
s4
2
1
6
2
-
0
2
5
-
0
0
4
8
8
-
7.
[
1
9
]
N
.
F
e
n
g
,
T.
M
a
,
a
n
d
C
.
C
h
e
n
,
“
F
u
z
z
y
e
n
e
r
g
y
ma
n
a
g
e
m
e
n
t
st
r
a
t
e
g
y
f
o
r
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
o
n
b
a
t
t
e
r
y
s
t
a
t
e
-
of
-
c
h
a
r
g
e
e
st
i
mat
i
o
n
b
y
p
a
r
t
i
c
l
e
f
i
l
t
e
r
,
”
S
N
A
p
p
l
i
e
d
S
c
i
e
n
c
e
s
,
v
o
l
.
4
,
n
o
.
1
0
,
p
.
2
5
6
,
O
c
t
.
2
0
2
2
,
d
o
i
:
1
0
.
1
0
0
7
/
s
4
2
4
5
2
-
0
2
2
-
0
5
1
3
1
-
8.
[
2
0
]
V
.
K
.
K
a
mb
o
j
,
S
.
K
.
B
a
t
h
,
a
n
d
J.
S
.
D
h
i
l
l
o
n
,
“
I
mp
l
e
me
n
t
a
t
i
o
n
o
f
h
y
b
r
i
d
h
a
r
mo
n
y
s
e
a
r
c
h
/
r
a
n
d
o
m
se
a
r
c
h
a
l
g
o
r
i
t
h
m
f
o
r
s
i
n
g
l
e
a
r
e
a
u
n
i
t
c
o
mm
i
t
me
n
t
p
r
o
b
l
e
m,”
I
n
t
e
rn
a
t
i
o
n
a
l
J
o
u
r
n
a
l
o
f
El
e
c
t
ri
c
a
l
Po
w
e
r
&
En
e
r
g
y
S
y
s
t
e
m
s
,
v
o
l
.
7
7
,
p
p
.
2
2
8
–
2
4
9
,
M
a
y
2
0
1
6
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
i
j
e
p
e
s.
2
0
1
5
.
1
1
.
0
4
5
.
[
2
1
]
A
.
M
a
z
o
u
z
i
,
N
.
H
a
d
r
o
u
g
,
A
.
H
a
f
a
i
f
a
,
A
.
I
r
a
t
n
i
,
a
n
d
I
.
C
o
l
a
k
,
“
P
a
r
t
i
c
l
e
sw
a
r
m
o
p
t
i
mi
z
a
t
i
o
n
o
f
f
u
z
z
y
l
o
g
i
c
-
b
a
se
d
e
n
e
r
g
y
man
a
g
e
me
n
t
s
y
st
e
m
f
o
r
e
n
h
a
n
c
e
d
e
f
f
i
c
i
e
n
c
y
i
n
f
u
e
l
c
e
l
l
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
,
”
S
u
st
a
i
n
a
b
l
e
C
o
m
p
u
t
i
n
g
:
I
n
f
o
rm
a
t
i
c
s
a
n
d
S
y
s
t
e
m
s
,
v
o
l
.
4
8
,
p
.
1
0
1
2
3
9
,
D
e
c
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
su
s
c
o
m.
2
0
2
5
.
1
0
1
2
3
9
.
[
2
2
]
Y
.
H
u
a
n
g
,
H
.
H
u
,
J.
Ta
n
,
C
.
L
u
,
a
n
d
D
.
X
u
a
n
,
“
D
e
e
p
r
e
i
n
f
o
r
c
e
m
e
n
t
l
e
a
r
n
i
n
g
b
a
se
d
e
n
e
r
g
y
m
a
n
a
g
e
me
n
t
st
r
a
t
e
g
y
f
o
r
r
a
n
g
e
e
x
t
e
n
d
f
u
e
l
c
e
l
l
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
,
”
En
e
rg
y
C
o
n
v
e
rsi
o
n
a
n
d
M
a
n
a
g
e
m
e
n
t
,
v
o
l
.
2
7
7
,
p
.
1
1
6
6
7
8
,
F
e
b
.
2
0
2
3
,
d
o
i
:
1
0
.
1
0
1
6
/
j
.
e
n
c
o
n
ma
n
.
2
0
2
3
.
1
1
6
6
7
8
.
[
2
3
]
Y
.
W
a
n
g
,
J.
W
u
,
H
.
H
e
,
Z.
W
e
i
,
a
n
d
F
.
S
u
n
,
“
D
a
t
a
-
d
r
i
v
e
n
e
n
e
r
g
y
m
a
n
a
g
e
men
t
f
o
r
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
s
u
si
n
g
o
f
f
l
i
n
e
r
e
i
n
f
o
r
c
e
me
n
t
l
e
a
r
n
i
n
g
,
”
N
a
t
u
re
C
o
m
m
u
n
i
c
a
t
i
o
n
s
,
v
o
l
.
1
6
,
n
o
.
1
,
p
.
2
8
3
5
,
M
a
r
.
2
0
2
5
,
d
o
i
:
1
0
.
1
0
3
8
/
s
4
1
4
6
7
-
0
2
5
-
5
8
1
9
2
-
9.
[
2
4
]
V
.
L.
D
e
v
i
,
K
.
K
u
m
a
r
,
G
.
V
a
sa
v
i
,
M
.
P
r
i
y
a
,
a
n
d
K
.
M
.
K
u
mar,
“
P
e
r
f
o
r
man
c
e
a
n
a
l
y
s
i
s
o
f
2
5
0
k
W
g
r
i
d
-
c
o
n
n
e
c
t
e
d
p
h
o
t
o
v
o
l
t
a
i
c
sy
st
e
m,
”
i
n
2
0
2
4
T
h
i
r
d
I
n
t
e
r
n
a
t
i
o
n
a
l
C
o
n
f
e
r
e
n
c
e
o
n
T
re
n
d
s
i
n
E
l
e
c
t
r
i
c
a
l
,
El
e
c
t
r
o
n
i
c
s
,
a
n
d
C
o
m
p
u
t
e
r
E
n
g
i
n
e
e
r
i
n
g
(
T
EE
C
C
O
N
)
,
N
o
v
.
2
0
2
4
,
p
p
.
1
1
2
–
116
,
d
o
i
:
1
0
.
1
1
0
9
/
TEE
C
C
O
N
6
4
0
2
4
.
2
0
2
4
.
1
0
9
3
9
9
8
4
.
[
2
5
]
G
.
R
i
z
z
o
n
i
,
L.
G
u
z
z
e
l
l
a
,
a
n
d
B
.
M
.
B
a
u
ma
n
n
,
“
U
n
i
f
i
e
d
mo
d
e
l
i
n
g
o
f
h
y
b
r
i
d
e
l
e
c
t
r
i
c
v
e
h
i
c
l
e
d
r
i
v
e
t
r
a
i
n
s,”
I
EEE
/
A
S
ME
T
ra
n
s
a
c
t
i
o
n
s
o
n
M
e
c
h
a
t
r
o
n
i
c
s
,
v
o
l
.
4
,
n
o
.
3
,
p
p
.
2
4
6
–
2
5
7
,
1
9
9
9
,
d
o
i
:
1
0
.
1
1
0
9
/
3
5
1
6
.
7
8
9
6
8
3
.
B
I
O
G
RAP
H
I
E
S O
F
AUTH
O
RS
Dr
.
V
.
La
k
sh
m
i
De
v
i
is
c
u
rre
n
tl
y
wo
r
k
in
g
a
s
a
p
r
o
fe
ss
o
r
in
t
h
e
S
c
h
o
o
l
o
f
En
g
i
n
e
e
rin
g
a
t
An
u
ra
g
U
n
iv
e
rsit
y
,
H
y
d
e
ra
b
a
d
,
I
n
d
ia.
S
h
e
re
c
e
iv
e
d
h
e
r
P
h
.
D
.
d
e
g
re
e
in
2
0
1
9
fro
m
JN
TUA,
An
a
n
t
h
a
p
u
ra
m
,
I
n
d
ia.
M
.
Tec
h
.
,
d
e
g
re
e
in
e
lec
tri
c
a
l
p
o
we
r
e
n
g
in
e
e
rin
g
fr
o
m
Na
ra
y
a
n
a
En
g
in
e
e
rin
g
C
o
ll
e
g
e
,
Ne
ll
o
re
,
JN
TU
-
A,
in
2
0
1
1
,
a
n
d
B.
Tec
h
.
d
e
g
re
e
i
n
e
lec
tri
c
a
l
a
n
d
e
lec
tro
n
ics
e
n
g
i
n
e
e
rin
g
fro
m
th
e
S
id
d
h
a
rt
h
I
n
stit
u
te
o
f
E
n
g
i
n
e
e
rin
g
a
n
d
Tec
h
n
o
lo
g
y
,
Ti
ru
p
a
ti
,
JN
TU
-
A
in
2
0
0
8
.
He
r
r
e
se
a
rc
h
wo
r
k
f
o
c
u
se
d
on
th
e
field
o
f
p
o
we
r
s
y
ste
m
s,
o
p
ti
m
iza
ti
o
n
tec
h
n
i
q
u
e
s,
p
o
we
r
e
lec
tro
n
ic
a
p
p
l
ica
ti
o
n
s
in
re
n
e
wa
b
le
e
n
e
rg
y
so
u
rc
e
s
,
a
n
d
h
y
b
rid
e
lec
tri
c
v
e
h
icle
s.
S
h
e
h
a
s
p
u
b
l
ish
e
d
m
o
re
t
h
a
n
2
5
re
se
a
rc
h
p
u
b
li
c
a
ti
o
n
s
in
v
a
rio
u
s
In
tern
a
ti
o
n
a
l
J
o
u
r
n
a
ls/Co
n
fe
re
n
c
e
s.
S
h
e
is
ra
ti
fied
a
s
a
ss
istan
t
p
ro
fe
ss
o
r
fro
m
JN
TU
-
A
,
AN
AN
THAPURAMU.
S
h
e
is
a
P
e
rm
a
n
e
n
t
m
e
m
b
e
r
o
f
IEE
E,
M
IS
TE
,
a
n
d
IAENG
.
S
h
e
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
v
l
d
e
v
i
.
e
e
e
@g
m
a
il
.
c
o
m
.
Dr
.
Da
m
o
d
h
a
r
Re
d
d
y
is
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
in
e
e
rin
g
.
He
e
a
rn
e
d
h
is
B.
Tec
h
.
(EE
E)
a
n
d
M
.
Tec
h
.
(
p
o
we
r
e
lec
tro
n
ics
)
d
e
g
re
e
s
fro
m
JN
TU
Hy
d
e
ra
b
a
d
a
n
d
c
o
m
p
lete
d
h
is
P
h
.
D.
in
e
lec
tri
c
a
l
e
n
g
i
n
e
e
rin
g
fr
o
m
VIT
,
Ve
ll
o
re
in
2
0
1
9
.
Wi
t
h
o
v
e
r
1
1
y
e
a
rs
o
f
tea
c
h
in
g
a
n
d
re
se
a
rc
h
e
x
p
e
rien
c
e
,
h
is
i
n
tere
sts
sp
a
n
p
o
we
r
c
o
n
v
e
rters
,
re
n
e
wa
b
le en
e
rg
y
sy
ste
m
s,
a
n
d
h
y
b
rid
e
lec
tri
c
v
e
h
icle
s
.
He
h
a
s p
u
b
li
s
h
e
d
2
4
re
se
a
rc
h
p
a
p
e
rs
in
S
c
o
p
u
s
-
in
d
e
x
e
d
jo
u
r
n
a
ls
a
n
d
c
o
n
fe
re
n
c
e
s,
a
n
d
se
rv
e
s
a
s
a
re
v
iew
e
r
fo
r
En
e
rg
y
Re
p
o
rts
(
El
se
v
ier),
IJRE
R,
a
n
d
IE
EE
c
o
n
fe
re
n
c
e
s.
A
re
c
ip
i
e
n
t
o
f
t
h
e
VIT
Re
se
a
rc
h
Aw
a
rd
(2
0
1
7
),
Dr.
Re
d
d
y
is
a
se
n
io
r
m
e
m
b
e
r
o
f
IEE
E
a
n
d
a
li
fe
m
e
m
b
e
r
o
f
IS
TE
.
He
c
a
n
b
e
c
o
n
tac
ted
a
t
e
m
a
il
:
d
a
m
o
d
h
a
r_
re
d
d
y
@y
m
a
il
.
c
o
m
.
Evaluation Warning : The document was created with Spire.PDF for Python.