Int
ern
at
i
onal
Journ
al of
P
ower E
le
ctr
on
i
cs a
n
d
Drive
S
ystem
(I
J
PE
D
S
)
Vo
l.
11
,
No.
2
,
June
2020
,
pp.
618
~
624
IS
S
N:
20
88
-
8694
,
DOI: 10
.11
591/
ij
peds
.
v
1
1
.i
2
.
pp
618
-
624
618
Journ
al h
om
e
page
:
http:
//
ij
pe
ds
.i
aescore.c
om
Loss minimi
zati
on DTC
electric
m
otor driv
e syst
em
ba
s
ed
on
adapti
ve ANN str
ategy
Sim Sy Yi
1
,
W
ah
yu
Mulyo
Uto
m
o
2
,
G
oh
H
ui Hw
ang
3
,
C
hien Sio
ng K
ai
4
, A
lvin
Joh
n
Li
m Men
g
Si
ang
5
,
No
r
A
ir
a
Z
am
bri
6
, Yon
is
M. Y. B
us
wig
7
, Kah
H
aw La
w
8
, S
im
Gia
Yi
9
1
,4,6
Facul
ty
of E
ngine
er
ing
T
ec
h
nology,
Univ
ersi
ti
Tun
Hus
sein O
nn
Mala
ysia
,
Mala
ysia
2
,9
Faculty
of
Ele
ct
ri
ca
l
and
Elec
t
ronic
Engi
ne
eri
n
g,
Univer
si
ti T
u
n
Hus
sein
Onn
Mala
ysia
,
Ma
la
y
sia
3
School
of El
ec
t
ric
a
l
Eng
ineeri
n
g,
Guangxi
Univ
ersit
y
,
Mal
aysia
5
Facul
ty
of
Civ
i
l
and
Environme
nta
l
Engi
n
ee
r
ing
,
Univer
si
ti T
un
Hus
sein
Onn Mal
aysia,
Ma
la
ysia
7
Facul
ty
of Engi
nee
ring
,
Univ
ersit
i
M
al
aysi
a
Sar
a
wak,
Mal
aysia
8
Depa
rtment of
El
e
ct
ri
ca
l
and
co
mput
er
Engi
n
ee
r
ing,
Cur
ti
n
Univ
er
sity
Ma
la
ysia
,
Mala
ysia
Art
ic
le
In
f
o
ABSTR
A
CT
Art
ic
le
history:
Re
cei
ved
Oct
2
7
, 201
9
Re
vised
Dec
2
8
, 2
01
9
Accepte
d
Fe
b
3
, 2
0
20
El
e
ct
ri
c
mo
tor
drive
sys
te
ms
(
EMDS
)
have
b
ee
n
r
ec
ogni
ze
d
as
one
of
the
most
prom
ising
mo
tor
sys
te
ms
r
ec
en
tl
y
due
to
th
ei
r
low
en
erg
y
consumpt
ion
an
d
red
u
ce
d
em
issi
ons.
W
it
h
only
s
ome
ex
ce
pt
ions,
EMDS
are
the
m
ai
n
sourc
e
for
th
e
provi
sion
of
mecha
n
ic
a
l
en
e
rgy
in
i
ndustry
and
ac
coun
ts
for
ab
out
60%
of
glo
bal
industri
a
l
e
l
ec
tr
ic
i
ty
co
nsumpti
on.
La
rg
e
ene
rgy
eff
i
ci
en
c
y
pote
n
ti
a
ls
hav
e
be
en
ide
nt
ifie
d
in
EMDS
wit
h
ver
y
short
payba
ck
ti
m
e
an
d
high
-
cost
ef
fe
ct
iv
ene
ss
.
Typ
ical,
dur
ing
oper
ation
at
r
ated
mode
,
th
e
mot
or
driv
e
abl
e
to
h
old
i
ts
good
eff
i
ci
en
ci
es.
How
ev
er,
a
mo
tor
usuall
y
oper
at
es
out
from
r
at
ed
mode
in
ma
ny
a
ppli
c
at
ions,
espe
ci
a
ll
y
whil
e
under
li
gh
t
loa
d
,
it
r
educed
the
mot
or’s
eff
i
cie
ncy
seve
re
ly.
H
enc
e
,
it
is
nec
essary
that
a
conve
nt
iona
l
dri
ve
sys
t
e
m
to
embed
with
loss
minimi
z
at
ion
strat
egy
to
op
timize
th
e
driv
e
sys
te
m
eff
ic
i
ency
over
al
l
oper
at
ion
ran
ge
.
Convent
ionally
,
th
e
f
lux
val
u
e
is
kee
p
ing
co
nstant
ly
over
t
he
r
ange
of
oper
ation,
wh
er
e
it
should
b
e
highl
igh
te
d
th
at
for
any
oper
at
ing
po
int,
th
e
losses
cou
ld
be
mi
n
im
i
ze
wi
t
h
the
prop
er
adjus
tm
ent
of
the
fl
ux
le
ve
l
to
a
suita
ble
val
u
e
a
t
tha
t
po
int
.
Henc
e,
with
the
int
en
ti
on
to
g
ene
r
at
e
an
ada
p
ti
ve
flux
l
eve
l
cor
r
e
sponding
to
an
y
oper
a
ti
ng
poi
nt,
espe
c
ia
l
ly
at
li
ght
lo
ad
condi
ti
on
,
an
o
nli
ne
l
ea
r
n
ing
Artifi
c
ia
l
Neur
a
l
Ne
twork
(AN
N)
cont
ro
ller
was
proposed
i
n
thi
s
study
,
t
o
mi
ni
mi
z
e
the
sys
te
m
losses.
The
entire
proposed
stra
te
gi
c
dr
ive
sys
te
m
would
be
v
e
rifi
ed
under
the
MA
TL
AB/
Simul
ink
softw
are
e
nvironmen
t.
It
is
exp
ec
t
e
d
tha
t
wi
th
the
proposed
on
li
ne
le
a
rning
Art
ifi
cial
N
eur
al
Network
cont
ro
lle
r
eff
i
ci
en
cy
opti
mization
a
lg
orit
hm
c
an
a
chieve
be
tt
er
ene
r
gy
saving
compare
d
with
tra
ditiona
l
bl
end
ed
stra
te
gi
es.
Ke
yw
or
d
s
:
Ad
a
ptive
flu
x con
t
ro
l
Eff
ic
ie
nc
y o
ptimi
zat
ion
Loss
minimi
za
ti
on
M
ot
or drive
syst
em
On
li
ne
ann
This
is an
open
acc
ess arti
cl
e
un
der
the
CC
BY
-
SA
l
ic
ense
.
Corres
pond
in
g
Aut
h
or
:
Sim S
y Yi
,
Dep
a
rtme
nt of
Ele
ct
rical
En
gi
neer
i
ng Tec
hnology,
Faculty
of E
ngineerin
g
T
ech
nolo
gy,
Un
i
ver
sit
i T
un
Hu
s
sei
n O
nn
M
al
aysia
,
86
400 Pa
rit R
aj
a, J
ohor,
M
al
ay
sia
.
Emai
l:
sy
sim
@u
t
hm
.e
du.m
y
1.
INTROD
U
CTION
In
a
n
ef
fort
m
ov
i
ng
t
ow
a
rds
new
e
ra
of
me
chan
iz
at
io
n,
re
al
iz
at
ion
of
m
or
e
pr
eci
sio
n
a
nd
acc
ur
ac
y
work
ca
n
be
at
ta
in
by
r
eplace
d
t
he
huma
n
w
it
h
mac
hin
es
[
1
]
.
Ele
ct
ric
dr
i
ves
ha
ve
be
en
getti
ng
popula
r
a
nd
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
P
ow Elec
& Dri S
ys
t
IS
S
N:
20
88
-
8
694
Lo
ss
m
i
nimiza
t
ion
DT
C
elec
tri
c m
ot
or
dr
iv
e
syste
m
B
as
e
d o
n ada
ptive
AN
N st
ra
te
gy
(
Sim Sy Yi
)
619
dep
l
oy
e
d
in
va
rio
us
of
a
ppli
cat
ion
w
hich
in
vo
l
ved
mo
ti
on.
I
n
dri
v
e
s
ys
te
ms,
a
p
rime
m
ov
e
r
are
neces
sary
in
order
to
gen
e
ra
te
ene
rgy
that
i
s
use
d
to
creat
e
m
otion.
This
highli
gh
ts
in
a
n
e
nor
mous
en
ergy
savi
ng
pote
ntial
by
e
ne
rgy
-
ef
fici
ent
el
ect
rical
dr
i
ve
s
olu
ti
on
s
[
2
].
This
e
ne
rgy
gain
from
diff
e
re
nt
sourc
es
su
c
h
as
die
s
el
and
petr
ol
e
ng
i
nes,
hy
dr
a
ulic
m
ot
or
s
an
d
el
ect
r
ic
mo
t
or
s
et
c.
D
rives
in
w
hi
ch
el
ect
ric
m
otors
a
re
t
he
pr
ime
movers
a
re
known
as
el
ect
ri
cal
dr
ives
[
1
].
Plenty
of
a
dva
ntages
a
re
re
porte
d
by
im
plement
el
ect
ric
dr
i
ves
,
su
c
h
as
nim
ble
co
ntr
ol,
le
ss
mainta
in
a
nce,
high
e
ff
ic
ie
nc
y,
exte
ns
ive
li
mit
s
of
powe
r,
s
peed
an
d
tor
qu
e,
lo
w
no
ise
, a
nd n
eat
operati
on.
A
total
of
65
-
70% total
elec
tri
ci
ty supp
l
y
to
industr
y
is c
ons
um
e
d by
t
he
el
ect
ric mo
t
or
gl
ob
al
ly
. I
t i
s
exp
ect
e
d
t
o
ha
ve
a
co
ns
ide
ra
ble
am
ount
of
savi
ng
in
e
ne
rgy
pr
ic
e
an
d
reducti
on
in
c
oal
co
nsum
ption
an
d
gr
ee
nhouse
e
missi
on
by
ha
ving
on
l
y
1%
achieve
me
n
t
in
inc
reasi
ng
el
ect
ric
m
otor
ef
fici
enc
y.
With
the
co
mp
le
te
ne
ss
impleme
nt
at
ion
of
the
prop
e
r
e
ff
ic
ie
nc
y
opti
miza
ti
on
t
echn
i
qu
e
,
it
is
exp
ect
e
d
to
ha
ve
7%
lowe
r
el
ect
rici
ty
de
man
i
n
glo
be
,
re
ported
by
va
rio
us
inte
rn
at
io
nal
age
nc
ie
s
of
dev
el
opin
g
co
untrie
s
[
3
,
4
].
Op
e
rati
ng
of
mo
to
r
in
unrat
ed
c
onditi
on,
e
sp
eci
al
ly
pa
rtia
l
loading
for
an
e
xten
ded
ti
me
is
the
mai
n
reasons
resu
lt
in
g
in
l
ow
ene
r
gy
e
ff
ic
ie
ncy
i
n
el
ect
ric
dr
i
ve
s
ys
te
m
,
as
co
mp
a
re
d
to
othe
rs
facto
rs.
As
ma
ke
know
in
el
ect
ric
power
researc
h
in
sti
t
ute
(EPR
I),
m
os
t
of
the
pe
riod
of
ti
me,
60
-
65%
of
el
ect
ric
mo
t
or
oper
at
es
in
industr
y
are
60%
bel
ow
t
he
rated
loa
d.
T
hat
is,
unde
r
r
at
ed
co
nd
it
io
n,
35
-
40%
of
t
he
mo
to
rs
is
en
dlessl
y
wasti
ng
the
el
ect
rici
ty
due
t
o
th
e
poor
ef
fi
ci
ency
[
5
,
6
],
and
seem
s
to
b
e
fo
c
us
e
d
as
wide
area
f
or
energ
y
-
savin
g
an
d
e
ne
rgy
-
e
ff
ic
ie
nt
c
on
ce
pt
[
7
]
.
As
per
r
ep
or
t
in
a
M
al
aysia
c
ommerci
al
bu
il
ding,
it
is
cl
os
e
to
50%
of
el
ect
rici
ty
consu
med
i
n
HVAC
a
pp
li
c
at
ion
,
t
he
in
duct
ion
m
otors
are
normall
y
operate
d
in
unrated
conditi
on
f
or
a
prol
onge
d
ti
me
[
1
]
.
Hen
c
e,
an
en
er
gy
eff
ic
ie
nt
c
ontr
ol
strat
eg
y
ar
e
nee
ded
to
e
ns
ure
the
ma
ximum
gen
e
rated
ene
r
gy
can
be
co
nsume
d[
8
-
10
]
.In
order
to
fu
l
fil
the
ef
fici
enc
y
e
nh
a
nceme
nt
,
some
stud
ie
s
pro
pos
ed
high
-
qu
al
it
y
mate
rial
s
,
desi
gn
an
d
c
onstr
uc
ti
on
te
ch
niqu
es
[
10]
.
Ne
ver
t
heless
,
t
her
e
is
oth
e
r
value
d
s
olu
ti
on
, n
a
mely e
xper
t con
t
ro
l al
gori
thm
wh
ic
h
a
bl
e to a
pp
l
y dire
ct
ly to
a
dri
ve system
[
11
].
In
m
os
t
cases
,
the
el
ect
ric
mot
or
are
desi
gn
and
de
velo
p
to
run
at
50
-
100%
of
rated
lo
a
d
[
5
]
,
w
hich
in
tu
r
n
hold
a
maxim
um
ef
fi
ci
ency
w
he
n
operati
ng
nea
r
t
o
rated
c
onditi
on
[
1
2
]
.
H
ow
e
ver,
one
e
ff
ic
i
ency
is
bad
l
y
reduce
d
[
1
3,
1
4
]
due
to
ov
e
r
-
e
xcita
ti
on
[
8
]
w
hile
at
par
ti
al
l
oad,
w
hich
re
su
lt
s
in
exces
sive
i
n
ir
on
losses.
T
he
refor
e
,
an
e
nerg
y
ef
fici
ent
opti
mal
con
tr
ol,
a
strat
egy
t
hat
work
f
or
a
dju
sti
ng
the
fl
ux
le
ve
l
accor
ding
t
o
l
oad
c
hanges
t
o
ac
hieve
ma
xi
mu
m
ef
fici
en
cy
is
re
qu
ir
ed
[
5
]
.
wh
ic
h
is
al
so
ref
e
r
as
ef
fi
ci
ency
op
ti
miza
ti
on c
on
t
ro
l.
Numer
ous
of
s
trat
egis
has
be
en
re
porte
d
to
op
ti
mize
e
ff
ic
ie
ncy
f
or
EMD
S
pa
rtic
ularly
at
li
gh
t
loa
d.
Gen
e
rall
y,
the
real
-
ti
me
op
ti
miza
ti
on
co
ntr
ol
te
c
hn
i
qu
e
of
E
MDS
e
ff
ic
ie
ncy
ca
b
be
a
sso
rt
as
(
1)
S
earch
Con
tr
ol
(S
C
),
and
(2)
L
os
s
-
M
ode
l
-
Ba
se
d
Con
tr
ol
(L
M
C
).
T
he
pri
ncip
al
ideology
for
these
met
hods
is
t
o
al
te
rn
at
e
the
a
mp
li
tud
e
of
th
e
flu
x
with
va
r
ie
s
of
mo
t
or
operati
ng
c
onditi
on
al
th
ough
th
ese
two
c
ontr
ol
s
hav
e
diff
e
re
nt
exec
ution
[
15
-
17
].
In
SC
,
I
M
’s
powe
r
i
nput
or
DC
li
nk
powe
r
will
be
us
e
d
in
t
he
op
ti
mi
zat
ion
process
.
It
ma
nipulat
es
the
c
on
t
ro
l
in
pu
t
irr
especti
ve
of
m
otor
par
a
mete
r
to
minimi
ze
t
he
i
nput
powe
r
from
the
meas
ured
current
an
d
vo
lt
age
.
T
his
me
thod
w
orked
on
t
he
basic
t
o
al
te
rn
at
e
the
fl
ux
le
vel
in
t
he
dri
ve
sy
ste
m
unti
l
th
e
minim
um
power
in
put
is
ac
hieve
d
f
or
one
po
i
nt
of
op
e
rati
on
[
18
-
19
].
T
he
malp
racti
ce
of
thi
s
appr
oach
is
t
ha
t
it
de
no
te
a
rat
her
lo
ng
r
esp
on
se
ti
me
and
a
slo
w
c
onve
r
gen
ce
to
t
he
opti
mal
val
ue.
I
n
add
it
io
n,
t
he
c
apab
il
it
y
of
S
C
is
mu
c
hly
de
pends
on
t
he
input
po
wer
qual
it
y.
On
the
oth
e
r
hand,
Lo
ss
m
od
e
l
con
t
ro
ll
er,
L
MC
w
orks
dep
e
nd
on
t
he
mo
t
or
par
a
mete
r.
It
us
ed
t
he
I
M
dri
ve
los
se
s
m
odel
to
de
te
rmin
e
the
opti
mum
f
lux
le
vel
w
hic
h
mi
nimize
th
e
losses
of
th
e
dr
i
ve
s
ys
te
m
for
a
gi
ven
l
oad
an
d
s
pee
d.
This
methods
is
f
re
e
from
po
wer
measu
reme
nts
bu
t
it
util
iz
e
fe
edb
ac
k
[
1
6
,
2
0
-
2
1
]
,
yet,
t
he
LM
C
perf
or
m
ance
is
gr
eat
ly
de
pend
s
on
m
otor
dri
ve
m
odel
li
ng
and
it
’
s
losses
.
Dev
el
opme
nt
of
L
M
C
e
xist
a
trade
-
off
bet
ween
sy
ste
m c
omple
xity a
nd
acc
ur
a
cy [1
5
,
2
2
-
2
4
].
Ther
e
f
or
e,
the
ai
m
for
this
study
is
t
o
de
sig
ning
a
rob
us
t
eff
ic
ie
nc
y
op
ti
miza
ti
on
c
on
t
r
ol
t
o
pr
e
dict
the
mini
mum
f
lux
value
,
at
a
ny
ope
rati
ng
point
ov
e
r
t
he
e
ntire
sel
ect
ed
dri
ve
s
ys
te
m
spe
ed
range
t
hat
able
t
o
maximize
t
he dri
ve’
s
ef
fici
en
cy
a
nd maintai
n
the
s
ys
te
m
pe
rformance
at the sa
me ti
me.
2.
CHAR
A
CTERIZATI
ON O
F MA
XIMU
M
E
NERGY
EFFICIE
NCY A
C
HIEVE
MENT
Virtuall
y,
E
M
sh
ows
best
tra
ns
ie
nt
re
spo
nse
and
im
pose
high
ef
fici
ency
wh
e
n
op
e
rate
at
it
s
rated
tor
qu
e
a
nd
s
pe
ed.
H
ow
e
ver,
EM
w
orks
far
from
it
s
rate
d
conditi
on
in
m
os
t
of
the
ap
pl
ic
at
ion
,
es
peci
al
ly
at
minimu
m loa
d l
evels
,
w
hich
t
he
init
ia
l va
lue
o
f
t
he
re
fer
e
nc
e flux is k
e
pt
,
wh
e
re it
giv
e
ri
se
to
some
pr
oble
ms
in
the
dri
ve
s
ys
te
ms.
O
wing
to
the
im
bal
ance
betwee
n
coppe
r
a
nd
ir
on
losses
at
li
gh
t
l
oads,
rated
flu
x
op
e
rati
on
ca
use
s
la
r
ge
c
or
e
l
os
e
,
th
us
re
duci
ng
the
ef
fici
ency
of
the
dr
ive
[
25,
26]
.
At
a
ce
rtai
n
operati
ng
po
i
nt,
the
e
ff
ic
ie
ncy
of
t
he
E
M
ca
n
be
im
prov
e
d
by
re
du
ci
ng
t
o
a
mini
m
um
lo
ss
an
d
de
creasin
g
the
le
vel
of
the
ma
gnet
ic
fl
ux
a
ppr
opriat
el
y
or
by
balanci
ng
the
c
oppe
r
and
ir
on
l
os
ses
th
rou
gh
progr
ammi
ng
t
he
fl
ux.
As
it
is
known,
the
los
ses
of
a
n
el
ect
r
om
a
gnet
ic
in
a
mac
hin
e
a
re
a
dir
ect
functi
on
of
the
mag
netic
flu
x,
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8
694
In
t J
P
ow
Ele
c
&
Dr
i
S
ys
t
,
V
ol
.
1
1
, N
o.
2
,
J
un
e
2020
:
618
–
624
620
therefr
om
,
with
a
n
ap
pro
pr
ia
te
flu
x
le
vel
ca
li
br
at
ion,
t
he
pro
portio
nate
ba
la
nce
of
losse
s
bet
ween
the
c
oppe
r
and
ir
on
co
uld
be
ob
ta
ine
d
.
H
ence,
t
he
ai
r
g
a
p flu
x
m
us
t
be mi
nimize
to
enhance
the
m
otor ef
fici
enc
y.
Fr
om
the
ba
s
ic
of
t
he
m
oto
r
’s
tor
que
is
f
orme
d
by
t
he
t
orq
ue
pro
du
ci
ng
ro
t
or
current
a
nd
mag
netiz
ing
c
urren
t,
it
is
w
orka
ble
wit
h
di
ff
ere
nt
c
ombi
nation
of
cu
rrent
a
nd
fl
ux
va
lue
to
gain
t
he
same
tor
qu
e
value
.
Ordina
rily,
t
he
EM
is
desig
ne
d
to
operate
cl
os
e
to
t
he
rated
loa
d,
howe
ve
r,
the
re
is
a
n
opti
mu
m
flu
x
value
w
he
re
t
he
dr
i
ve’s
ma
xim
um
e
ff
ic
ie
nc
y
ca
n
be
ac
hieve
d
f
or
an
y
ope
rati
ng
s
peed
a
nd
loa
d
conditi
on.
I
n
a
simple
wa
y,
le
ss
e
ff
ic
ie
nt
occurre
nces
at
low
loa
d
conditi
ons
ha
ppen
s
beca
us
e
of
the
un
s
uitabil
it
y
of
the
flu
x
le
vel
sel
ect
ion
a
nd
it
cou
ld
be
im
pro
ved
in
a
wa
y
of
cal
ibrati
ng
base
d
on
the
A
NN
base
d
ef
fici
enc
opti
miza
ti
on
c
on
t
ro
l st
rateg
y
3.
DEVELOP
M
ENT OF
PRO
POSED
A
N
N
BASED
EFFI
CIENC
Y
OP
TIMIZATI
O
N
CONTROL
STRA
TE
G
Y
On
the
basic
of
the
fl
ux
re
du
ct
ion
,
at
a
ce
rtai
n
loa
d,
f
ull
e
ff
ic
ie
nc
y
ca
n
be
obta
ine
d
with
the
c
orrect
flu
x
le
vel
adj
ust
ment
to
get
a
n
op
ti
m
um
fl
ux
value
.
T
her
e
fore,
t
he
first
s
te
p
f
or
this
stu
dy
is
to
c
har
ac
te
rise
the
e
ff
ic
ie
nc
y
beh
a
viou
r
patte
rn
f
or
a
ny
po
ssible
op
e
rati
ng
mode
in
E
MDS
to
obta
in
it
s
re
sp
ect
ive
opti
mu
m
flu
x
values
th
at
ena
ble
the
maxim
um
ef
fici
ency
in
t
he
dr
i
ve
s
ys
te
m.
In
this
st
udy
,
the
e
ne
r
gy
ef
f
ic
ie
ncy
op
ti
miza
ti
on
c
on
t
ro
ll
er
is
pro
po
s
ed
an
d
desi
gn
e
d
base
d
on
the
fl
ux
re
du
ct
ion
c
oncept
by
the
im
pleme
ntati
on
of
A
rtific
ia
l
N
eur
al
Netw
ork
(ANN)
[22
-
23]
.
T
he
maxi
mum
ef
fici
enc
y
of
E
M
D
S
ca
n
be
achiev
ed
w
he
n
the
minimu
m
in
put
power
is
obt
ai
ned
wi
th
the
con
sta
nt
outp
ut
powe
r
re
qu
ired
by
the
l
oa
d.
T
his
pro
pose
d
appr
oach
is
ba
sed
on
va
r
ying
the
fl
ux
up
t
o
the
point
w
here
the
mea
surin
g
in
put
po
wer
is
a
minim
um
of
one
po
i
nt
of
ope
ra
ti
on
.
T
h
e
a
da
pt
ive
opti
mu
m
flu
x
val
ue
is
predict
ed
by
th
e
pro
po
se
d
e
ffi
ci
ency
op
ti
mi
zat
ion
ANN
base
d
e
f
fici
ency
opti
m
iz
at
ion
c
on
t
ro
l
le
r
al
gorith
m
f
or
an
y
dif
fer
e
nt
operati
on
mode,
ie
,
var
i
ou
s
sp
ee
d
and
va
rio
us
lo
ad
to
ob
ta
in
it
s
opti
mum
flu
x
value
co
rr
es
pondin
g
t
o
dif
fer
e
nt
cases
as
sho
wn
in
Fig
ur
e
1.
The
predict
io
n
of
the
f
l
ux
va
lue
ca
n
be
a
chieve
d
due
t
o
the
po
s
sessi
on
of
t
he
onli
ne
le
ar
ning
ab
il
it
y
in
the
pro
posed
a
lgorit
hm
.
The
diff
e
re
nce
bet
ween
t
he
cal
cu
la
te
d
input
an
d
the
real
in
put
powe
r
is
fe
d
a
s
input
for
the
n
e
ural
. [2
6
-
28]
The
propose
d
ANN
based
e
nerg
y
ef
fici
en
cy
opti
miza
ti
on
of
DTC
E
MDS
,
as
sho
wn
in
Fig
ur
e
1,
wh
e
re
it
is
ta
r
ge
te
d
to
mai
ntain
t
he
fast
dyna
mic
cha
racteri
s
ti
cs
an
d
bette
r
respo
ns
e,
an
d
al
so
ai
me
d
in
ge
tt
ing
minimu
m l
os
se
s
especial
ly
f
or the li
ght l
oa
d and l
igh
t
sp
ee
d d
rive’s
op
e
rati
on
.
Figure
1.
Bl
oc
k Diag
ram of
the
pro
po
se
d A
NN b
ase
d ene
r
gy ef
fici
enc
y o
ptimi
zat
ion
c
ontr
ol E
M
D
S.
4.
RESU
LT
S
A
ND AN
ALYSIS
The
propose
d
ANN
e
ff
ic
ie
nc
y
opti
miza
ti
on
con
t
ro
ll
er
is
sh
ow
n
in
Fig
ure
2
.
T
he
er
ror
of
in
put
powe
r
is
us
e
d
as
in
pu
t
for
t
he
pro
posed
co
nt
r
oller
w
hile
t
he
ou
t
pu
t
of
it
impleme
nted
as
the
opti
mum
fl
ux
ref
e
ren
ce
.
Figure
2
.
Sim
ul
ink
circ
uit f
or
the pr
opos
e
d A
NN ef
fici
ency
op
ti
miza
ti
on c
on
t
ro
ll
er.
In
order
to
ve
rify
the
e
ff
ect
i
ven
e
ss
of
t
he
pro
po
se
d
A
N
N
e
ff
ic
ie
nc
y
opti
miza
ti
on
co
ntr
oller
for
the
D
TC
el
ect
ric
dri
ve
sy
ste
m,
the
in
vestigat
ions
of
t
he
dr
i
ve
s
ys
te
m
hav
e
bee
n
c
ar
ried
out
f
or
di
ff
e
ren
t
values
of
sp
ee
d
an
d
t
orqu
e
.
The
e
ff
ect
s
of
sp
ee
d
an
d
to
r
que
va
riat
ion
on
the
s
ys
te
m
’s
eff
ic
ie
nc
y
as
well
as
P
r
opos
e
d
A
N
N
E
O
C
on
t
r
ol
l
e
r
o
p
t
i
m
u
m
f
l
u
x
*
1
S
a
t
u
r
a
t
i
o
n
1
S
a
t
u
r
a
t
i
o
n
S
-
F
u
n
c
t
i
o
n
A
N
N
E
O
P
i
n
e
r
r
1
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
P
ow Elec
& Dri S
ys
t
IS
S
N:
20
88
-
8
694
Lo
ss
m
i
nimiza
t
ion
DT
C
elec
tri
c m
ot
or
dr
iv
e
syste
m
B
as
e
d o
n ada
ptive
AN
N st
ra
te
gy
(
Sim Sy Yi
)
621
t
he
ca
pab
il
it
y
of
the
dri
ve
s
yst
em
to
mainta
in
the
good
s
pe
ed
res
pons
e
a
chievem
ent
f
or
var
ie
ty
s
peed
an
d
tor
qu
e
are
te
ste
d.
The
sel
ect
io
n
ti
me
is
set
at
ti
me
=
0.5s
t
o
act
ivate
t
he
pro
posed
ANN
e
ff
ic
ie
nc
y
op
ti
miza
ti
on
con
t
ro
ll
er
to
c
ompare
the
e
ffi
ci
ency
pe
rformance
be
f
or
e
and
a
fter
the
pro
po
se
d
co
ntr
oller
is
injec
te
d
i
nto
the
s
ys
te
m
.
Th
e
sim
ulati
on
re
su
lt
s
of
m
otor
sp
ee
d
of
1100
and
800
rpm
te
ste
d
with
ma
xi
mu
m
a
nd
mini
mu
m
tor
qu
es
a
ppli
ed,
wh
ic
h
are
0.2
an
d
0.8Nm
r
especti
vely
a
re
giv
e
n
in
Fi
gur
e
3
-
6
.
T
he
s
y
s
te
m
respo
ns
e
s
how
n
in
Fi
gure
3
-
6
,
f
rom
t
op
to
bott
om
,
r
ep
rese
nt
the
m
otor
s
peed
(
r
pm
)
,
t
he
d
-
q
a
xis
vo
lt
age
(V),
the
d
-
q
a
xis
current
(
A)
,
op
ti
mal flux (
W
b), a
nd last
ly
t
he
drive i
nput
powe
r (W
)
.
(a)
(b)
Fig
ure
3
.
D
rive
sy
ste
m
p
e
rfo
r
mance
w
her
e
the
pro
po
se
d A
NN
ef
fici
ency
op
ti
miza
ti
on
c
on
t
ro
ll
er is
init
ia
te
d
at
the time =
0.5
s
at
t
he
m
otor
sp
ee
d of 8
00
r
pm
with
an ap
pl
ie
d
0.2
Nm
loa
d
to
r
qu
e
(a
)
be
fore the
AN
N
eff
ic
ie
nc
y o
ptimi
zat
ion
c
ontr
oller
is i
niti
at
ed
; (
b)
a
fter t
he AN
N
e
ff
ic
ie
n
c
y op
ti
miza
ti
on
con
t
ro
ll
er
is
ini
ti
at
ed
.
(a)
(b)
Fig
ure
4
.
D
rive
sy
ste
m
p
e
rfo
r
mance
w
her
e
the
pro
po
se
d A
NN ef
fici
ency
op
ti
miza
ti
on c
on
t
ro
ll
er is
init
ia
te
d
at
the time =
0.5s
at
t
he
m
otor
sp
e
e
d of 8
00
r
pm
with
an ap
pl
ie
d
0.8
Nm
loa
d
to
r
qu
e
(
a
) be
fore the
AN
N
eff
ic
ie
nc
y o
ptimi
zat
ion
c
ontr
oller is init
ia
te
d; (b)
a
fter t
he AN
N
e
ff
ic
ie
nc
y op
ti
miza
ti
on
con
t
ro
ll
er is
ini
ti
at
ed.
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
790
800
810
S
p
e
e
d
(
r
p
m
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
-
1
0
0
0
100
V
d
,
q
(
V
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
-2
0
2
I
d
,
q
(
A
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
0
.
6
0
.
8
1
O
p
t
i
m
u
m
F
l
u
x
(
W
b
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
30
40
50
I
n
p
u
t
P
o
w
e
r
(
W
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
16
1
6
.
5
17
t
i
m
e
(
s
)
O
u
t
p
u
t
P
o
w
e
r
(
W
)
0
.
6
0
.
7
0
.
8
0
.
9
1
790
800
810
S
p
e
e
d
(
r
p
m
)
0
.
6
0
.
7
0
.
8
0
.
9
1
-
1
0
0
0
100
V
d
,
q
(
V
)
0
.
6
0
.
7
0
.
8
0
.
9
1
-2
0
2
I
d
,
q
(
A
)
0
.
6
0
.
7
0
.
8
0
.
9
1
0
.
6
0
.
8
1
O
p
t
i
m
u
m
F
l
u
x
(
W
b
)
0
.
6
0
.
7
0
.
8
0
.
9
1
30
40
50
I
n
p
u
t
P
o
w
e
r
(
W
)
0
.
6
0
.
7
0
.
8
0
.
9
1
16
1
6
.
5
17
t
i
m
e
(
s
)
O
u
t
p
u
t
P
o
w
e
r
(
W
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
790
800
810
S
p
e
e
d
(
r
p
m
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
-
1
0
0
0
100
V
d
,
q
(
V
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
-2
0
2
I
d
,
q
(
A
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
0
.
6
0
.
8
1
O
p
t
i
m
u
m
F
l
u
x
(
W
b
)
0
.
6
0
.
7
0
.
8
0
.
9
1
790
800
810
S
p
e
e
d
(
r
p
m
)
0
.
6
0
.
7
0
.
8
0
.
9
1
-
1
0
0
0
100
V
d
,
q
(
V
)
0
.
6
0
.
7
0
.
8
0
.
9
1
-2
0
2
I
d
,
q
(
A
)
0
.
6
0
.
7
0
.
8
0
.
9
1
0
.
6
0
.
8
1
O
p
t
i
m
u
m
F
l
u
x
(
W
b
)
0
.
6
0
.
7
0
.
8
0
.
9
1
6
6
.
5
67
6
7
.
5
t
i
m
e
(
s
)
O
u
t
p
u
t
P
o
w
e
r
(
W
)
0
.
6
0
.
7
0
.
8
0
.
9
1
90
100
110
I
n
p
u
t
P
o
w
e
r
(
W
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
6
6
.
5
67
6
7
.
5
t
i
m
e
(
s
)
O
u
t
p
u
t
P
o
w
e
r
(
W
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
90
100
110
I
n
p
u
t
P
o
w
e
r
(
W
)
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8
694
In
t J
P
ow
Ele
c
&
Dr
i
S
ys
t
,
V
ol
.
1
1
, N
o.
2
,
J
un
e
2020
:
618
–
624
622
(a)
(b)
Fig
ure
5
.
D
rive
sy
ste
m
p
e
rfo
r
mance
w
her
e
the
pro
po
se
d A
NN
ef
fici
ency
op
ti
miza
ti
on
c
on
t
ro
ll
er is
init
ia
te
d
at
the time =
0.5
s
at
t
he
m
otor
sp
ee
d of 1
100
rp
m
with
a
n
a
ppli
ed
0.2
Nm
lo
ad
to
r
qu
e
(a
)
be
fore the
AN
N
eff
ic
ie
nc
y o
ptimi
zat
ion
c
ontr
oller
is i
niti
at
ed
; (
b)
a
fter t
he AN
N
e
ff
ic
ie
nc
y op
ti
miza
ti
on
con
t
ro
ll
er
is
ini
ti
at
ed
.
(a)
(b)
Fig
ure
6
.
D
rive
sy
ste
m
p
e
rfo
r
mance
w
her
e
the
pro
po
se
d A
NN
ef
fici
ency
op
ti
miza
ti
on
c
on
t
ro
ll
er is
init
ia
te
d
at
the time =
0.5
s
at
t
he
m
otor
sp
ee
d of 1
100
rp
m
with
a
n
a
ppli
ed
0.8
Nm
lo
ad
to
r
qu
e
(a
)
be
fore the
AN
N
eff
ic
ie
nc
y o
ptimi
zat
ion
c
ontr
oller
is i
niti
at
ed
; (
b)
a
fter t
he AN
N
e
ff
ic
ie
nc
y op
ti
miza
ti
on
con
t
ro
ll
er
is
ini
ti
at
ed
.
The
ANN
e
ff
i
ci
ency
op
ti
miz
at
ion
co
ntr
oller
is
ai
me
d
to
pro
du
ce
a
n
ad
aptive
opti
mum
flu
x
val
ue
with
re
sp
ect
t
o
dif
fer
e
nt
sp
ee
d
under
va
rio
us
tor
que
le
vel
t
o
gain
the
ma
xi
mu
m
dr
i
ve
e
f
f
ic
ie
ncy
,
es
peci
al
ly
at
li
gh
t
sp
ee
d
a
nd
li
gh
t
loa
d
operati
on
s
.
T
he
r
esulti
ng
a
da
ptive
fl
ux
le
vel
ge
ner
at
e
d
f
rom
the
A
NN
e
ff
ic
ie
ncy
op
ti
miza
ti
on
f
or
eac
h
te
ste
d
ope
rati
ng
c
onditi
on
is
show
n
in
T
a
ble
1,
in
ste
ad
of
a
0.9
Nm
c
on
sta
nt
ref
e
ren
ce
f
l
ux
.
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
1090
1100
1110
S
p
e
e
d
(
r
p
m
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
-
1
0
0
0
100
V
d
,
q
(
V
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
-2
0
2
I
d
,
q
(
A
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
0
.
6
0
.
8
1
O
p
t
i
m
u
m
F
l
u
x
(
W
b
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
40
50
60
I
n
p
u
t
P
o
w
e
r
(
W
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
2
2
.
5
23
2
3
.
5
t
i
m
e
(
s
)
O
u
t
p
u
t
P
o
w
e
r
(
W
)
0
.
6
0
.
7
0
.
8
0
.
9
1
1090
1100
1110
S
p
e
e
d
(
r
p
m
)
0
.
6
0
.
7
0
.
8
0
.
9
1
-
1
0
0
0
100
V
d
,
q
(
V
)
0
.
6
0
.
7
0
.
8
0
.
9
1
-2
0
2
I
d
,
q
(
A
)
0
.
6
0
.
7
0
.
8
0
.
9
1
0
.
6
0
.
8
1
O
p
t
i
m
u
m
F
l
u
x
(
W
b
)
0
.
6
0
.
7
0
.
8
0
.
9
1
40
50
60
I
n
p
u
t
P
o
w
e
r
(
W
)
0
.
6
0
.
7
0
.
8
0
.
9
1
2
2
.
5
23
2
3
.
5
t
i
m
e
(
s
)
O
u
t
p
u
t
P
o
w
e
r
(
W
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
1090
1100
1110
S
p
e
e
d
(
r
p
m
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
-
1
0
0
0
100
V
d
,
q
(
V
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
-2
0
2
I
d
,
q
(
A
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
0
.
6
0
.
8
1
O
p
t
i
m
u
m
F
l
u
x
(
W
b
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
125
130
135
I
n
p
u
t
P
o
w
e
r
(
W
)
0
.
1
0
.
2
0
.
3
0
.
4
0
.
5
9
1
.
5
92
9
2
.
5
t
i
m
e
(
s
)
O
u
t
p
u
t
P
o
w
e
r
(
W
)
0
.
6
0
.
7
0
.
8
0
.
9
1
1090
1100
1110
S
p
e
e
d
(
r
p
m
)
0
.
6
0
.
7
0
.
8
0
.
9
1
-
1
0
0
0
100
V
d
,
q
(
V
)
0
.
6
0
.
7
0
.
8
0
.
9
1
-2
0
2
I
d
,
q
(
A
)
0
.
6
0
.
7
0
.
8
0
.
9
1
0
.
6
0
.
8
1
O
p
t
i
m
u
m
F
l
u
x
(
W
b
)
0
.
6
0
.
7
0
.
8
0
.
9
1
125
130
135
I
n
p
u
t
P
o
w
e
r
(
W
)
0
.
6
0
.
7
0
.
8
0
.
9
1
9
1
.
5
92
9
2
.
5
t
i
m
e
(
s
)
O
u
t
p
u
t
P
o
w
e
r
(
W
)
Evaluation Warning : The document was created with Spire.PDF for Python.
In
t J
P
ow Elec
& Dri S
ys
t
IS
S
N:
20
88
-
8
694
Lo
ss
m
i
nimiza
t
ion
DT
C
elec
tri
c m
ot
or
dr
iv
e
syste
m
B
as
e
d o
n ada
ptive
AN
N st
ra
te
gy
(
Sim Sy Yi
)
623
Table
1
.
Re
s
ulti
ng
flu
x
le
vel
obta
ined
by t
he
pro
po
se
d
a
da
ptive AN
NE
O
f
or
var
io
us
opera
ti
ng
c
onditi
on.
Torq
u
e (
N
m
)
0
.2
0
.8
Sp
eed (r
p
m
)
Op
tim
u
m
Flu
x
L
e
v
el
1100
0
.66
9
7
0
.74
6
8
800
0
.67
5
3
0
.76
3
6
5.
CONCL
US
I
O
N
This
pa
per
pre
sents
a
s
trat
eg
y
t
o
op
ti
mise
t
he
e
ff
ic
ie
nc
y
f
or
D
TC
Ele
ct
ri
c
Moto
r
D
rive
Sy
ste
m
.
An
ANN
base
d
en
ergy
e
ff
ic
ie
ncy
opti
miza
ti
on
c
on
t
ro
ll
er
with
t
he
obje
ct
ive
of
ge
nerat
ing
a
n
adap
ti
ve
flu
x
l
evel
to
opti
mize
th
e
eff
ic
ie
nc
y
of
dif
fer
e
nt
op
erati
ng
points
has
be
en
pro
po
s
ed
i
n
this
study
.
T
he
propose
d
op
ti
m
um
fl
ux
con
t
ro
ll
er
is
a
bl
e
to
decr
ea
se
s
ta
tor
flu
x
rap
i
dl
y
f
r
om
rated
va
lue
of
0.9
W
b
to
it
s
c
orres
pond
i
ng
op
ti
mal
value.
Ther
e
f
or
e,
cu
rrent
an
d
volt
ag
e
will
be
re
du
c
ed
an
d
th
us
minimi
zes
the
in
pu
t
powe
r
to
a
chie
ve
maxim
um
e
ff
i
ci
ency
of
t
he
dri
ve
s
ys
te
m.
A
t
the
same
ti
me,
it
is
able
to
pr
ese
r
ve
go
od
dynam
ic
respo
ns
e
o
f
the
dr
i
ve
syst
em
by
mainta
in
ing
the
s
pee
d
in
co
ns
ta
nt
acc
ordin
g
to
s
pee
d
re
fer
e
nce
co
mmand
f
or
dif
fer
e
nt
op
e
rati
ng
c
ondi
ti
on
s o
f
s
pee
d
and
to
rque.
As
a
res
ult,
a
si
gn
i
ficant
ef
fici
enc
y
im
pro
veme
nt
has
bee
n
ac
hie
ved
by
the
op
ti
mal
fl
ux
le
vel
det
ermine
d
by
th
e
pr
opos
e
d
A
NN
based
e
nergy
e
ff
ic
ie
nc
y
op
ti
miza
ti
on
c
ompare
d
with the
consta
ntly
rated
flu
x value
,
the
obje
ct
ive
of the
stu
dy h
a
s
been ac
hieve
d
.
ACKN
OWLE
DGE
MENTS
The
aut
hors
w
ou
l
d
li
ke
t
o
t
ha
nk
the
M
inist
ry
of
E
du
cat
io
n,
M
a
-
la
ysi
a
(
M
O
E)
a
nd
the
Re
searc
h
M
a
nag
e
ment
Ce
ntre
(R
M
C),
U
ni
-
ve
rsiti
Tu
n
H
us
sei
n
O
nn
M
al
aysia
(
UT
HM)
f
or
fina
nc
ia
ll
y
sup
-
porti
ng
t
his
researc
h
unde
r
the
Fun
dame
nt
al
Re
search
G
ran
t
Sche
me
(
FRGS
)
Vo
t.
N
o.
FR
GS
/1/
2018
/TK1
0/UT
H
M
/
03
/
8
and p
a
rtia
ll
y
s
ponsore
d b
y U
niv
e
rsiti
Tun
H
us
sei
n O
nn
M
a
la
ys
ia
.
REFERE
NCE
S
[1]
Woosuk
Sung,
Jinche
ol
Shin
,
Yu
-
seok
Jeong,
"Ene
rgy
-
Eff
ici
ent
and
Robust
Control
for
High
-
Perform
an
ce
Induc
ti
on
Motor
Drive
W
it
h
an
Applic
a
ti
on
in
El
e
ct
ri
c
Vehi
cle
s
,
"
IEE
E
transacti
ons
on
ve
hi
c
ular
te
chno
logy
,
vol.
61
,
no
.
8
,
O
ct
2012
.
[2]
J.
Aus
te
rm
ann,
H.
Borch
erd
ing
,
H.
Stic
hweh
,
V
.
Grabs,
"H
igh
e
f
fic
i
ent
modular
drive
sys
tem
-
A
n
ideal
appr
o
ac
h
for
gre
en
int
ra
l
ogisti
cs
app
li
c
ations,"
2016
18t
h
Europe
an
Co
nfe
ren
c
e
on
Po
wer
El
e
ct
ron
ic
s
and
Appli
ca
t
io
n
s
(EPE'16
ECC
E Europe
), Karl
sru
he,
pp
.
1
-
10
,
201
6
.
[3]
T.
Fletier,
W.
Eichha
m
me
r
and
J.
Schl
eich,
"Ene
rgy
eff
ic
i
enc
y
in
elec
tri
c
mo
tor
s
ystem
s:
Techni
c
al
po
te
nt
ials
an
d
poli
cy
appr
oa
ch
es
for
d
eve
lop
in
g
count
r
ie
s,"
Un
it
ed
Nati
ons
Ind
ustria
l
Deve
lop
me
nt
,
Vi
enna
,
2
011.
[4]
P.
K.
Choudhary
and
S.
P.
Dubey
,
"Efficie
n
cy
opt
im
izati
on
of
ind
uct
ion
mot
or
dri
ve
in
ste
ady
-
sta
t
e
using
Artifici
al
Neura
l
Networ
k,
"
2016
Int
er
nat
ion
al
Confer
enc
e
on
Com
puta
ti
on
of
Po
wer,
Ene
rgy
I
nforma
t
ion
and
Comm
uincati
on
(ICCPEIC),
Che
nnai
,
pp.
295
-
30
2
,
2016
.
[5]
R.
Ra
za
l
i,
A
.
A.
Abdall
a
,
R
.
Gh
oni
and
C
.
Venk
at
ase
sha
ia
h
,
"Im
proving
squirre
l
ca
ge
induction
mot
or
ef
ficien
cy
:
te
chn
ic
a
l
r
evi
ew
,
"
Int
ernati
onal
j
ournal
of
ph
ysical
sci
enc
es
,
vol
.
7,
no
.
8
,
pp
.
112
9
-
1140,
16
Feb
2012.
[6]
J.
Mali
nows
ki,
W.
Hoyt
,
P.
Zw
anz
ig
er
and
B
.
Finle
y,
"Rev
ie
w
of
upcom
ing
m
otor
and
driv
e
s
ystem
s
eff
i
ci
en
c
y
reg
ulations
in
U.
S.
and
Europe,"
IEE
E
Petroleum
and
Chemi
cal
I
ndustry
Comm
it
t
ee
Con
fe
renc
e
(
PCIC)
,
Hous
ton,
TX,
2015
,
pp
.
1
-
8
,
2015
.
[7]
A.
M.
Ba
zz
i
an
d
P.
T.
Kre
in,
"
Revi
ew
of
me
th
ods
for
r
ea
l
-
ti
m
e
loss
mi
ni
mi
z
ation
in
indu
ct
ion
machin
es,
"
I
EE
E
transacti
ons on
I
ndustry
application
,
vol
.
46
,
no
.
6
,
pp
.
2319
-
2328
,
Nov/Dec
2010.
[8]
B.
Bl
anusa
,
"N
e
w
tre
nds
in
ef
ficien
cy
optimizat
i
on
of
indu
ction
mot
or
dr
ive
s,"
u
nive
rsity
of
B
an
ja
Luka,
Bosnia
and
Her
ze
govin
a
,
2010
.
[9]
J.
F.
Stump
er,
A
.
Dotl
inge
r
and
R.
Kenne
l,
"Loss
mi
nimization
o
f
induc
t
ion
m
ac
h
ine
s
in
dyn
am
i
c
oper
ation,
"
I
EE
E
transacti
ons on energy
convers
ion
,
vol
.
28
,
no
.
3
,
pp
.
726
-
735
,
S
ept
2013
.
[10]
G.
Cui,
L
.
L
iu,
S.
Li
,
P.
Y
ang,
F.
Yang,
L
.
Che
n,
and
J.
Dong,
“Opti
miza
ti
on
D
esign
of
High
Ef
fic
i
enc
y
Vari
able
Freque
ncy
Indu
ct
ion
Motor
B
a
sed
on
Fin
it
e
El
ement
Analys
is,”
in
In
te
rnat
i
onal
Conf
ere
nc
e
on
Elec
tric
al
Mac
hine
s and
S
yste
ms
,
pp
.
701
-
705
,
2014
.
[11]
K.
T
.
Ch
au,
"
E
le
c
tri
c
Vehi
cle
Mac
hine
s
and
Drive
s:
Design
,
Analysis
and
Applic
a
ti
on
,"
W
il
e
y
-
IEEE
Press
,
pp.
375
,
2015
.
[12]
M.
Gai
ceanu,
E
.
Rosu,
R.
Padur
aru
and
T.
Mun
te
anu
,
"V
ec
tor
-
c
ontrol
le
d
op
ti
m
a
l
dr
ive
sys
te
m
f
or
th
e
induction
mot
or,
"
4
th
In
te
rnational
Sym
posium
on
El
e
ct
rical
and
E
l
ec
troni
cs
Engi
n
ee
ring
(ISE
EE
)
,
Gal
at
i
,
2013,
pp.
1
-
6
,
2013
.
[13]
Y.
L
.
Karn
ava
s,
C.
K.
Vac
h
ari
d
e
s
and
A.
D.
Karl
is,
"O
n
th
e
d
evelopme
nt
of
an
o
n
-
site
induc
t
ion
mot
or
eff
i
ci
en
cy
esti
mator
fr
ame
work,"
MedPow
er
2014,
Athens
,
pp.
1
-
6
,
2014
.
[14]
N.
Kumar
,
T
.
R
.
Chel
l
ia
h
and
S
.
P.
Sr
iva
st
ava,
"
Adapti
ve
cont
ro
l
sche
m
es
for
improving
dyna
mic
per
for
ma
n
ce
o
f
eff
icienc
y
-
optim
iz
ed
induction
m
otor
driv
es,
"
IS
A
Tr
ansacti
ons
,
v
ol.
57
,
pp
.
301
-
3
10,
2014
.
Evaluation Warning : The document was created with Spire.PDF for Python.
IS
S
N
:
2088
-
8
694
In
t J
P
ow
Ele
c
&
Dr
i
S
ys
t
,
V
ol
.
1
1
, N
o.
2
,
J
un
e
2020
:
618
–
624
624
[15]
M.
Fara
sa
t
and
E.
K
ara
m
an,
"
Ef
fic
i
enc
y
-
Opti
mized
Hybr
id
Fie
l
d
Orien
t
ed
and
Dire
ct
Torqu
e
C
o
ntrol
of
Induc
tion
Motor
Drive
,
"
in
Inte
rnat
ional
C
onfe
renc
e
on
Ele
ct
rical Mac
h
ine
s
and
Syst
ems
,
no
.
5
,
pp
.
20
-
23
,
2
011
.
[16]
A.
M.
Bazzi
,
S.
Membe
r
,
and
P
.
T
.
Krein
,
"
Rev
ie
w
of
Methods
for
Real
-
Time
Loss
Minim
ization
in
Induc
t
ion
Mac
hine
s,
"
IEEE
Tr
ansacti
ons
o
n
Industry
App
l
ic
ati
ons
,
vol
.
46
,
no.
6,
pp.
2319
-
2328,
2010
.
[17]
S.
T
.
Varghe
se
a
nd
K.
R.
R
aj
ago
pal
,
"E
conom
i
c
and
eff
i
ci
en
t
ind
uct
ion
mo
tor
co
ntrol
ler
for
el
e
ctric
vehicl
e
using
im
prove
d
sc
al
ar
al
gorit
h
m,
"
2016
IE
EE
1st
Int
ernati
onal
Conf
ere
n
ce
on
Powe
r
E
lec
tronic
s,
In
te
l
li
g
ent
Control
and
Ene
rgy
S
yste
ms
(ICPE
ICES)
,
De
lhi
,
India,
pp
.
1
-
7
,
2016
.
[18]
A.
Ta
h
eri
,
A
.
Rahm
ati,
and
S.
Kaboli
,
"
Eff
ici
enc
y
Improv
ement
in
DTC
of
Six
-
Phase
Induc
ti
on
Mac
h
ine
b
y
Adapti
ve
Gradi
e
nt
Desce
n
t
of
Fl
ux,
"
IE
EE
Tr
ansacti
ons on
Power
El
e
ct
ronics
,
vo
l.
27
,
no
.
3
,
pp
.
1
552
-
1562,
2012
.
[19]
Z.
Qu,
M.
R
anta
,
M.
Hinkk
ane
n,
and
J.
Luomi,
"
Loss
-
Minim
iz
in
g
Flux
Le
v
el
Co
ntrol
of
Indu
ct
io
n
Motor
Dr
ive
s,
"
IEE
E
Tr
ansacti
o
ns on
Industry A
ppli
cations
,
vo
l.
48,
no
.
3
,
pp
.
95
2
-
961,
Ma
y
201
2.
[20]
F.
T
azera
rt
,
N.
T
aï
b,
T
.
Reki
ou
a,
and
D.
R
eki
oua
,
"
Dire
c
t
Torque
Control
Opt
im
i
z
at
ion
with
Loss
Minim
izati
on
of
Induc
ti
on
Motor
,
"
in
Inte
rnat
ion
al
Conf
ere
nce o
n
Elec
tri
cal Sc
i
e
nce
s and
Te
chno
logi
es
in
Maghr
eb
,
pp
.
1
-
8
,
2014
.
[21]
Islam
,
M.R
.
,
Sa
dhu,
P.K
.
,
Isla
m
,
M.M
.
and
Hos
sain,
M.K.
,
"
Per
forma
nc
e
Analy
sis
of
a
DTC
a
nd
SV
M
Based
Fiel
d
-
Orien
ta
t
io
n
Control
Indu
ction
Motor
Drive
,"
Inte
rnat
ional
Journal
of
Pow
e
r
El
ectronics
an
d
Dr
iv
e
Syst
ems
,
vol.
5
,
no
.
3
,
p
p.
336
,
2015
.
[22]
S.
Y.
Sim
,
W.
M.
Utomo,
Z
.
A
.
Haron
,
A.
A
.
B
ohar
i,
N.
M.
Zi
n
,
and
R.
M
.
Arif
f,
"
Neura
l
Netw
ork
SV
PWM
-
D
TC
of
Induc
t
ion
M
otor
for
EV
Lo
ad
Model
,
"
in
El
e
ct
rica
l
Pow
e
r,
Elec
tronic
s,
Comm
unic
ati
ons,
Controls,
and
Informatic
s Se
mi
nar
,
vol. 00, no.
c,
pp
.
23
-
28
,
201
4
.
[23]
S.
Y.
Sim,
W.
M.
Utomo
,
Z.
A
.
Haron
,
A.
A
.
Bohari
,
and
N.
M.
Z
in,
"
Modeling
of
an
Online
AN
N
base
d
DT
C
Speed
Controlle
r
towar
ds
th
e
Eff
ect
of
Par
a
me
t
er
Sensit
ivi
t
ie
s,
"
in
The
Th
ird
Inte
rnationa
l
Confe
ren
ce
o
n
Computer
Engi
n
ee
ring a
nd
Math
emati
ca
l
Sc
i
en
ces
,
no.
Ic
ce
ms,
pp
.
225
-
232
,
2014
.
[24]
Krim,
S.
,
Gdai
m,
S.,
Mt
ibaa,
A.
and
Mimoun
i,
M.
F.
,
"
FP
G
A
-
base
d
im
pl
e
me
nt
at
ion
d
ire
c
t
torque
con
trol
of
induc
ti
on
mo
tor
,"
Inte
rnationa
l J
ournal
of Powe
r
El
e
ct
ronics
and
Dr
iv
e
Syst
ems
,
v
ol.
5
,
no
.
3
,
p
p.
2
93
,
2015
.
[25]
Sim,
S.
Y.,
Uto
mo,
W.
M.,
Har
on,
Z
.
A.
,
Boh
ar
i,
A.
A.
,
Z
in,
N.
M.
and
Arif
f,
R
.
M.,
"
Indu
ct
ion
mot
or
dr
ive
b
ase
d
neur
al
ne
twork
dir
ec
t
torqu
e
control
,"
In
Information
Technol
ogy
Co
nve
rgenc
e
Spri
nger
,
Dordre
ch
t,
pp.
255
-
262
,
20
13.
[26]
Utomo,
W
.
M.,
Sim,
S
.
Y.,
H
aro
n,
Z.
A.
and
Zi
n,
N.M.
,
"
Onlin
e
ada
pt
ive
flux
co
ntrol
for
spa
ce
v
ec
tor
PWM
-
DT
C
IM dri
ves
tow
ar
ds opt
im
um
eff
i
ci
en
cy
d
esign
,"
AR
PN
Journal
o
f
Eng
ine
ering
an
d
Applied
S
cienc
es
,
2015
.
[27]
Utomo,
W.
M.
,
Zi
n,
N.M.
,
Haro
n,
Z
.
A.
,
Sim
,
S.
Y.,
Boh
ari
,
A
.
A.
,
Ariff
,
R
.
M.
an
d
Hana
fi
,
D
.
.
"
Speed
Tracki
ng
o
f
Fiel
d
Ori
ent
ed
Control
Per
ma
n
ent
Magn
et
Synchronous
Motor
Us
ing
Neura
l
Network
,"
Int
ernati
onal
Journal
of
Powe
r E
le
c
troni
cs
and
Dr
ive
Sys
te
ms
,
vol
.
4
,
no
.
3,
pp
.
290
,
2014
.
[28]
Utomo,
W.
M.
,
S
im
,
S.Y.,
Haron
,
Z.
A
.
,
Boh
aria,
A.A.,
Muha
mm
a
d
Zi
n
,
N.
,
Ma
t
Ar
iff,
R
.
and
Sis
wanto,
W.
A
.
,
A
N
"
Improve
d
DTC
of
an
induc
t
ion
mot
or
driv
e
with
neur
al
net
work
cont
roller
,"
Inte
r
nati
onal
Journal
of
Me
chani
ca
l
&
Me
chat
ronics
Engi
ne
ering
,
vol
.
14
,
no
.
2
,
pp
.
54
-
59
,
2014
.
Evaluation Warning : The document was created with Spire.PDF for Python.