TELKOM
NIKA
, Vol.12, No
.2, June 20
14
, pp. 333~3
4
2
ISSN: 1693-6
930,
accredited
A
by DIKTI, De
cree No: 58/DIK
T
I/Kep/2013
DOI
:
10.12928/TELKOMNIKA.v12i2.1444
333
Re
cei
v
ed Ma
y 22, 201
3; Revi
sed
De
ce
m
ber
27, 201
3; Acce
pted Janua
ry 1
1
, 20
14
Evaluation Research o
f
Traction Motor Performance for
Mine Dump Truck Based on Rough Set Theory
Huilai Sun
1
, Chun
Jin
1
*, Shu
y
ang Zh
eng
1
, Haiy
on
g Tian
2
1
School of Me
chan
ical En
gi
n
eeri
ng, Univ
ers
i
t
y
of Scie
nce
&
T
e
chnol
og
y
Beiji
ng, Bei
jin
g
,
China
2
China C
NR C
o
rpor
ation l
i
mit
ed, Be
ij
ing, C
h
i
na, T
e
lp:010-8
237
59
49
*Corres
p
o
ndi
n
g
author, e-ma
i
l
: jinji
nb
it@12
6
.com
A
b
st
r
a
ct
T
h
is p
aper
pre
s
ents the tracti
on
motor
eva
l
u
a
ti
on
metho
d
d
epe
ndi
ng
on th
e el
ectric trans
miss
i
o
n
ener
gy tra
n
sfer
char
acteristics
an
d
differe
nt s
ource
of
s
u
p
p
l
y
, incl
udi
ng
mo
tor man
u
factur
es, di
esel
turb
i
ne
ma
nufactur
e
rs, w
heel sid
e
re
ducer
ma
nufac
turers and
ele
c
tric drive system i
n
tegr
ated ma
nufactur
e
rs. 9
eval
uatio
ns
are pro
pos
ed
in
3 lev
e
ls fr
om the
mot
o
r
b
ody
an
d co
ntrol
p
e
rformanc
e, el
ectric driv
e sys
t
e
m
coordinate index, driving conditions
and s
p
ecific cycle. M
o
tor perfor
m
a
nc
e ev
aluation s
ystem
is publis
hed
by the
me
ans
of electric tra
n
smissio
n
test
s and c
o
m
put
er si
mul
a
tio
n
platfor
m
, usi
n
g
roug
h set the
o
ry.
Experi
m
ental r
e
sults show
t
hat the mo
del c
an accur
a
te ev
alu
a
tion of
state of the traction motor, Eval
u
a
tio
n
of the accurac
y
is better than the subj
ectiv
e
w
e
ight
in
g an
alysis, verifyi
n
g the inte
grity and us
eful
nes
s of
this val
uatio
n
meth
od. At th
e sa
me ti
me,
the co
mpr
ehe
nsive eval
uati
ons
i
ndex of
per
ma
nent ma
gne
t
synchro
nous
motors is hig
h
, it has i
m
p
o
rtant researc
h
valu
e.
Ke
y
w
ords
: Ve
hicle E
ngi
ne
eri
ng, T
r
ansport, tracti
on
motor, r
oug
h set theor
y, evaluati
o
n
1. Introduc
tion
Curre
n
tly, large dum
p tru
ck a
s
the m
a
in mea
n
s of
transport for large o
pen
pit mine
bears
40% of
the wo
rld'
s
coal, 9
0
% of
the iro
n
o
r
e
mining traffic [1]. Electric
Drive i
s
u
s
e
d
in
mining ma
nu
facture
r
s of
more th
an a
hund
red
-
ton
mining d
u
m
p
truck ex
ce
pt the Cate
rpillar
Comp
any. The ele
c
tri
c
d
r
ive syst
em stru
cture
is simplified,
ea
sy to operate, maintain
and
energy efficie
n
t. Large mini
ng tru
c
ks dev
elop to ele
c
tr
i
c
drive i
s
an i
nevitable tren
d. At the same
time, Trac
tion motor
c
h
arac
teris
t
ics
have an
im
portant
impa
ct on
the
vehicl
e dyn
a
m
i
c
para
m
eter. T
he matching
and evalu
a
tio
n
of Motor ve
hicle
driver
a
nd vehi
cle pe
rforma
nce is
no
w
an issue that
need
s to be a
ddre
s
sed a
s
a matter of urgen
cy.
In the p
r
o
c
e
s
s of
cho
o
si
n
g
tra
c
tion m
o
to
r, its eval
u
a
tion an
d a
s
se
ssm
ent h
a
v
e been
often out of the vehicl
e el
ectri
c
drive
system; ju
st re
lying on the d
r
ive motor b
e
n
ch te
st or b
a
si
c
para
m
eters
matchin
g
test. It's difficult to
guarant
ee the accu
racy an
d ob
jectivity of
the
evaluation, m
o
re
difficult to achieve effi
cient u
s
e
of the sy
stem. In the el
e
c
tri
c
drive
system
of
large
tonn
ag
e dum
p truck, optio
nal
range
die
s
el
tu
rbin
e i
s
limi
t
ed in
scop
e. The
r
efo
r
e, it
is
necessa
ry to establi
s
h
co
mpre
hen
sive
evaluation
system as th
e
core of a traction m
o
tor to
provide a the
o
retical ba
sis
for the determinat
ion of the overall de
si
gn of dump truck.
Dump t
r
uck e
l
ectri
c
tran
sm
issi
on evalu
a
tion at home
a
nd ab
roa
d
is
also le
ss
，
an
d often
for the
mat
c
h an
d the
fu
el con
s
umpti
on of
t
he
hybrid
vehicl
e
power sy
ste
m
an
alysi
s
a
nd
evaluation [2
]-[9].Dome
s
tic Beijing
Institute of
Technolo
g
y Wa
ng Wei [10],
finish th
e g
r
ay
correl
ation
an
d expe
rime
ntal si
mulation
of the
m
o
tor
perfo
rman
ce
;Foreig
n
Livin
t
Gheo
rg
he [
11]
illustrate
d evaluation for h
y
brid ele
c
tric vehicle
co
ntrol algo
rithm analysi
s
,Sun
g Chul [12] use
hard
w
a
r
e in t
he rin
g
nee
dl
e evaluation
and an
alysi
s
of electri
c
car motors,T
he
se studie
s
did
not
focu
s on the
electri
c
d
r
ive system.
Acco
rdi
ng to
a vari
ety of vehicle
tra
c
t
i
on
moto
r a
n
d
ele
c
tri
c
d
r
i
v
e system
fe
ature
s
,
different from
the ge
ne
ral
hybrid ve
hicl
es. Thi
s
pap
er p
r
e
s
e
n
ts t
he tra
c
tion
motor
evalua
tion
method
dep
e
nding
on
the
ele
c
tri
c
tra
n
s
missio
n e
n
e
r
gy tra
n
sfe
r
cha
r
a
c
teri
stics a
nd
differe
nt
sou
r
ce
of su
pply ,incl
udin
g
moto
r m
a
nufactu
re
s, d
i
esel
turbi
n
e
man
u
factu
r
ers,
wheel
side
redu
ce
r man
u
facturers an
d
ele
c
tri
c
dri
v
e
syste
m
in
tegrated
ma
n
u
factur
ers. 9
evaluatio
ns
are
prop
osed fro
m
3 levels f
r
om the moto
r body a
nd
control p
e
rfo
r
mance, el
e
c
tric d
r
ive
syst
em
coo
r
din
a
te in
dex, driving condition
s an
d
spe
c
ific
cy
cl
e. Motor pe
rforma
nce eval
uation sy
ste
m
is
Evaluation Warning : The document was created with Spire.PDF for Python.
ISSN: 16
93-6
930
TELKOM
NIKA
Vol. 12, No. 2, June 20
14: 333 – 34
2
334
publi
s
hed
by the mean
s of
electri
c
tra
n
smissi
on te
sts and comp
uter si
mulation
platform, u
s
in
g
rough s
e
t theory.
2. Driv
e motor ev
aluation proces
s
Dep
endin
g
o
n
the type of
traction
moto
r ba
si
c pe
rformance a
nd d
e
mand
chara
c
teri
stics
of mining
du
mp tru
c
k mot
o
r, mini
ng tru
c
ks t
r
acti
o
n
motor evaluat
ion system of
"Two
vertical
and
three
ho
rizon
t
al" is
pro
p
o
s
ed. As Fig
u
re
1
sh
ows,
three h
o
ri
zontal
mainly
refe
rs to
the t
r
a
c
tion
motor
manu
facture
r
s, m
anufa
c
ture
rs of ele
c
tri
c
drive
sy
stems and
in
tegrated
ve
hicle
manufa
c
turers, two vertica
l
mainly
refers to drive motor ben
ch testing and com
puter sim
u
lati
on
platform which is the eval
uation testin
g
mean
s of
dri
v
e motor sy
stem. Bench t
e
st mainly te
sts
the inherent
perfo
rman
ce
of the mo
tor
system, the vehicl
e driving
cycle si
mulat
i
on is to exa
m
ine
the run pe
rformance of driv
e motor in dri
v
ing con
d
ition
s
.
Figure 1. Tra
c
tion moto
r e
v
aluation sy
stem diag
ram
3. Dump truc
k ev
aluation
index
The main ty
pes of d
u
mp
truck drivin
g
motor in
cl
ude[13]:AC i
ndu
ction mot
o
r (IM
)
,
perm
ane
nt magnet syn
c
h
r
onou
s moto
r (PMSM),
brushl
ess DC
motor (BL
DC), DC the b
r
ush
motor (B
DC)and switched
relucta
n
ce
motor (S
RM). Each type of drive motor ha
s a uni
que
stru
cture d
e
si
gn a
nd
co
ntrol alg
o
rithm
s
,
whil
e the
se
l
e
cted
d
r
ive m
o
tor type
the
hybrid
vehicl
e
of
different
stru
ctural fo
rm
s i
s
not the
sam
e
. The
r
ef
o
r
e,
combi
ned
wit
h
the
ba
sic chara
c
te
risti
c
s of
different type
s of vehicl
es and the ve
hicle
con
d
itio
n, nine type
s of evaluati
on is p
r
e
s
en
ted
comp
re
hen
si
vely. Among
these
moto
rs, AC a
s
yn
chronou
s m
o
tor
is the
mo
stly wid
e
ly u
s
ed.
In
orde
r to eval
uate more intuitive and full use of ex
isti
ng data, mult
iple set
s
of ACIM is u
s
ed f
o
r
comp
ari
s
o
n
.
3.1. Motor b
o
d
y
and Con
t
rol indicator
s
Electri
c
dump
truck
whe
e
l motor is pl
aced dire
ctly in the whe
e
l hu
b, and com
b
i
ned with
the drive sy
stem, bra
k
e
s
a
nd wh
eel
sid
e
red
u
cer
a
s
a whol
e; this
installatio
n
a
nd tran
smi
ssi
on
form has a hi
gh dema
nd for the volum
e
of the
motor. Con
s
id
er
the mine du
mp truck ton
nage
load cha
r
act
e
risti
cs, to st
ress ove
r
loa
d
and
con
s
t
ant power
ra
nge, and to
meet the ba
sic
requi
rem
ents of the rated
con
d
ition, the
following
six
indicat
o
rs is comp
re
hen
si
vely propo
se
d:
Efficient are
a
overlo
ad
capa
city, con
s
tant po
we
r
rang
e, re
sp
o
n
se tim
e
, co
st and vol
u
me
manipul
ation.
Among
the
m
, overlo
ad
cap
a
city a
nd
control
re
spo
n
se
time
refe
rs to the
d
a
ta of
the rated
con
d
itions
.
3.2. Electric driv
e s
y
stem combining index
The so-calle
d ele
c
tric
dri
v
e system i
s
that: fuel energy pa
ss throug
h the
engine
,
gene
rato
r re
ctifier inverter,
and finally export en
er
gy a
fter the mech
anical part of
the whe
e
l sid
e
reduc
e
r tire. To make the s
y
s
t
em fully effic
i
ent
ope
ration, the e
n
tire syst
em sho
u
ld ru
n o
n
efficient di
stri
ct. On the
b
a
se
of defin
it
ion of moto
r
itself efficient
distri
ct
，
mot
o
r d
e
velopm
ent
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
1693-6
930
Ev
aluation Res
e
arc
h
of Trac
tion Motor
Perf
ormanc
e
for Mine Dump ....
(Huilai S
un)
335
degree in
dex
is p
r
e
s
ente
d
in the pa
pe
r, they ar
e
die
s
el g
ene
rato
r gro
up effici
e
n
t developm
e
n
t
degree i
ndex
and
wh
eel
side
re
du
cer efficient
developme
n
t de
gree
ind
e
x. The m
o
tor it
sel
f
efficient interval is defined
as follo
wing:
mo
i
mo
eff
mo
N
N
_
_
(1)
Whe
r
e,
N
mo
-
i
is amo
unt of
motor o
perating poi
nt
s d
r
o
p
in the effici
ency
zone,
N
mo
is all
amount of mo
tor ope
rating
points
Acco
rdi
ng to
the corre
s
po
nding
spee
d
relation
shi
p
b
e
twee
n the
m
o
tor
and
die
s
el moto
r
grou
p, efficie
n
t utilizing ind
e
x of diesel el
ectri
c
group
can be obtai
ne
d as follo
wing
:
i
de
i
de
mo
mo
de
i
eff
de
N
N
i
_
_
_
_
_
_
(2)
Whe
r
e,
N
mo
-
d
e
-
i
is
amou
nt o
f
motor and
d
i
esel
ele
c
tri
c
grou
p o
p
e
r
ati
ng p
o
ints d
r
o
p
in th
e
efficien
cy zo
ne at
the
sa
me time,
N
de-i
is all
amou
n
t
of die
s
el
el
ectri
c
gro
up
efficient o
p
e
r
ating
points
The effici
ent
utilizing fo
rm
ula is
simila
r
for w
heel
sid
e
re
ducer
an
d die
s
el el
ect
r
ic
gro
up,
the rang
e wh
ich moto
r accou
n
ts for sh
ould be
con
c
luded in the
whe
e
l side
redu
cer effici
e
n
t
rang
e.
3.3. Driv
ing
c
y
cle combining index
Mining du
mp
truck drivin
g
con
d
ition
s
are com
p
lex an
d cha
nge
able
.
With rega
rd
to such
workin
g condi
tion, we mu
st
also
co
nsi
d
e
r
the ba
si
c sp
eed of the ve
hicle
and m
o
tor to mat
c
h t
he
desi
gn of the
entire sy
ste
m
. In this pro
pose, the v
ehicle in
dex in
the efficient use of inte
rval is
pre
s
ente
d
as
followin
g
:
i
mo
i
mo
i
eff
N
N
_
_
_
R
_
_
R
(3)
Whe
r
e,
N
mc
-
i
is amou
nt of motor commo
n operating
p
o
ints drop in the efficien
cy zon
e
.
Nmc i
s
all am
ount of motor efficient operating point
s.
4. Rough se
t e
v
aluation method
Main id
ea
of rou
gh
set t
heory i
s
to
appr
oximate
portrayed im
pre
c
ise o
r
u
n
ce
rtain
kno
w
le
dge b
y
using the
knowl
edge i
n
the kn
owl
edg
e whi
c
h we h
a
ve kno
w
n. T
hat is, whe
n
the
obje
c
t inform
ation i
s
u
n
certain, in
exa
c
t ap
pr
oxim
a
t
e, cla
ssifyin
g the
data
and i
n
ferring
the
relation
shi
p
b
e
twee
n the
re
aso
n
ing
data
in o
r
de
r to
ide
n
tify implicit
knowl
edge
to
reveal p
o
tenti
a
l
law, and the
n
complete the
judgmental f
o
re
ca
sting an
d deci
s
io
n-m
a
kin
g
of thing
s
[14].
4.1 Determin
ation of the function
al propertie
s
Relatio
nal da
ta modeling:
evaluation in
dex is
use
d
as the conditi
on attribute, and then
the
co
ndition attribute colle
ction C=
﹛
c
1
,c
2
,…,c
n
﹜
; Re
gardi
ng exp
e
r
t evaluation
of the re
sult
s as
the de
cisi
on
attribute, then
the
de
ci
sion attribute set D=
﹛﹜
y
.
Reg
a
rdin
g the i
n
d
e
x value of th
e k-
obje
c
ts to be
evaluated a
nd the final compo
s
ite
sco
r
e a
s
a syste
m
of kno
w
led
ge, then we
ca
n
define u
k
=
（
c
1k
，
c
2k
，
…c
nk
,y
k
），
﹛
thus U=
u
1
,u
2
,…,u
m
﹜
, Two-dim
ensi
onal inf
o
rmatio
n table
con
s
tituted b
y
uk is relatio
nal data mod
e
l about the e
v
aluation obj
ect.
4.2. The func
tion attribute
data pro
ces
sing
First, som
e
attribute
in
di
cators
can b
e
qu
antified in
the evalu
a
tion system
,
som
e
attribute ind
e
x
can n
o
t be
quantified.T
he indi
ca
to
rs whi
c
h
can n
o
t be qu
antified may take
the
form of sco
r
i
ng by expe
rts to dete
r
min
e
the po
ssi
bil
i
ty of good o
r
bad, Q
uanti
f
iable indi
cat
o
rs
Evaluation Warning : The document was created with Spire.PDF for Python.
ISSN: 16
93-6
930
TELKOM
NIKA
Vol. 12, No. 2, June 20
14: 333 – 34
2
336
data can b
e
rated acco
rdin
g to the measure value
s
. Becau
s
e diffe
rent indi
cators is different
on
the magnitud
e
and the dim
ensi
onle
s
s, even the impa
ct dire
ction o
n
evaluation
obje
c
tives is
also
inco
nsi
s
tent.
T
herefore, th
e the ratin
g
rule
s
shoul
d be in u
n
ified mag
n
itud
e and
elimin
ate
dimen
s
ionl
ess, the scori
n
g
method is a
s
follows [15]:
Whe
n
indi
cat
o
rs a
r
e bi
gge
r the better
％
100
y
min
max
j
max
ij
i
i
i
i
x
x
x
x
(4)
Whe
n
indi
cat
o
rs a
r
e
small
e
r the better
％
100
y
min
max
min
ij
i
i
i
ij
x
x
x
x
(5)
Contin
uou
s d
a
ta must be
discreti
zed, t
here
are m
a
n
y
discretizatio
n
method
s.Accordi
ng
to the a
c
tual
situatio
n
so
meone
can
be
sele
cted.I
n
this pa
pe
r, the the
eq
ui
distant
attrib
utes
discreti
zation is
ch
oo
sen.
a.cal
c
ulatin of
the attribute interval length
ni
z
z
z
i
i
i
/
)
(
min
max
(6)
whe
r
e,
zimax
is the m
a
ximum of the i
-
th attr
ibute;
zimin i
s
the t
he miniu
m
of
the i-th
attribute; ni the numbe
r of intervals.
b.Determine t
he pro
p
e
r
ties
of the interval range. Th
e range of ea
ch
interval of the i th attribute is
i
i
i
z
z
z
min
min
，
，
，
，
i
i
i
i
z
z
z
2
z
min
min
，，
…
max
min
z
1
i
i
i
i
z
n
z
，
）
（
(7)
c.Cal
c
ul
ate the quanti
z
ed
v
a
lue of the property.
4.3. Dete
rmination of
fun
c
tional attrib
ute
w
e
igh
t
s
In the multi-index evalu
a
tion, differe
nt
functional
attributes
may have different
importa
nce.By roug
h set theory,
whe
n
some
prope
rt
ies a
dde
d to
the cla
s
sificat
i
on,the sy
ste
m
will directly be affected. In orde
r to find out the importance of
cert
ain functional
properties,the
method is to
remove
som
e
function
al prop
ertie
s
, a
nd then exa
m
ine the cla
s
sificatio
n
ch
a
nge
s
after the attribute. If
the attribute is rem
o
ved,
the correspon
ding
chang
es in the
classificatio
n
is
great, the strength of the prop
erti
e
s
is
high, that is o
f
high im
port
ance. Conve
r
sely, the stre
ngth
of the prope
rties.That i
s
of
lo
w imp
o
rta
n
c
e .
Weight
multi-ind
e
x e
v
aluation
can
be dete
r
min
e
d
by
importa
nce principl
e in rou
gh set attribut
e
Dep
end
ence
of the kno
w
led
ge D (d
eci
s
ion
attrib
ute index) to
the kno
w
le
dge of C
(evaluatio
n set):
)
(
/
)
(
(
)
(
U
card
D
pos
card
D
ci
C
ci
c
(8)
Cal
c
ulation of
the evaluatio
n importa
nce
)
(
ci
:
)
(
)
(
)
(
D
D
ci
ci
c
c
(9)
Weig
ht coeffi
cient of evalu
a
tion:
n
j
j
i
c
ci
1
)
(
/
)
(
(10)
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TELKOM
NIKA
ISSN:
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930
Ev
aluation Res
e
arc
h
of Trac
tion Motor
Perf
ormanc
e
for Mine Dump ....
(Huilai S
un)
337
5. Applicatio
n examples
5.1. Dete
rmination of
attr
ibutes an
d e
v
a
l
uation s
y
stem
16 sets
of traction
motor data mini
ng
trucks
in
different ton
nag
e are ap
plie
d for th
e
referen
c
e sa
mple,ro
ugh
set thory is u
s
ed for d
a
ta m
i
ning an
d allo
cation
weig
hting co
efficient
to
evaluate co
mpre
hen
sive
quality. Condition attribut
e set C=
｛
c
1
Efficient range
，
c
2
Overl
oad
multiple
，
c
3
Con
s
tant p
o
w
er ra
nge
，
c
4
Torq
ue
re
spo
n
s
e
time
，
c
5
Co
st
，
c
6
Vo
l
u
m
e
，
c
7
Di
esel
Electri
c
G
r
ou
p Efficient
ra
nge
，
c
8
Whe
e
l si
de
red
u
cer effi
cient
ra
nge
，
c
9
Traffic
effic
i
ent
range
｝
;
De
cisi
on attri
bute set D=
｛
y The motor
evaluation in
dex averag
e score
｝，
C is
sho
w
n a
s
tabl
e 1:
Table 1. moto
r evaluation p
a
ram
e
ters of variou
s types
Performance
Indicators
c
1
/
％
c
2
c
3
c
4
/ms C
5
$/k
w
C
6
/k
w C
7
/
％
C
8
/
％
C
9
/
％
IM1 81
1.3
3.5
40
9
460
80
90
81
IM2 80
1.2
3
45
10
452
81
91
82
IM3 82
1.35
3
44
8.9
450
90
92
82
IM4 83
1.4
2.5
46
10.2
442
82
89
83
IM 5
84
1.5
3
44
9.5
443
83
92
82
IM6 86
1.2
3
43
9.6
449
81
92
87
PMSM1 93
1.8
3
30
13
410
90
91
89
PMSM 2
88
1.7
3
28
13.5
420
92
92
90
PMSM 3
80
1.3
3.5
42
9.6
455
81
89
82
PMSM 4
88
1.7
2.7
32
13.4
409
93
93
89
BLDC1
77
1.5
3.2
43
11
456
82
92
81
BLDC2
76
1.65
2.5
46
10.2
457
82
91
82
BLDC3
75
1.6
2.4
47
10.1
460
83
92
84
SRM1 76
1.6
2.9
36
11.5
420
92
85
91
SRM2 76
1.62
2.8
38
12
421
91
80
92
SRM3 79
1.6
3.1
43
9.6
452
83
92
85
5.2. Data p
r
o
cessing
Motor
evalua
tion sho
w
s t
hat they
are
all qu
antifiabl
e indi
cato
rs,
except
C
4
, C
5
is the
smalle
r the b
e
tter,the re
st are the
bigge
r the bette
r i
n
dicato
rs.A
cco
r
ding to the
n
a
tional in
stitute
stand
ard
s
an
d the actual
use requi
re
ments,
evalu
a
t
ion of the uppe
r and l
o
we
r limits
are
pre
s
ente
d
as
equatio
n (11
)
.
(1
1)
Table 2. Sco
r
e
min
9
min
8
min
7
min
6
min
5
min
4
min
3
min
2
min
1
x
x
x
x
x
x
x
x
x
max
9
max
8
max
7
max
6
max
5
max
4
max
3
max
2
max
1
x
x
x
x
x
x
x
x
x
70
70
70
400
8
25
2
1
70
95
95
95
500
15
55
4
2
95
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ISSN: 16
93-6
930
TELKOM
NIKA
Vol. 12, No. 2, June 20
14: 333 – 34
2
338
U
C1 C2 C3
C4 C5
C6
C7
C8 C9
D
1
44 30 75
50 86
40
40
80 44
54
2
40 20 50
33 71
48
44
84 48
49
3
48 35 50
37 87
50
80
88 48
58
4
52 40 25
30 69
58
48
76 52
50
5
56 50 50
37 79
57
52
88 48
57
6
64 20 50
40 77
51
44
88 68
56
7
92 80 50
83 29
90
80
84 76
74
8
72 70 50
90 21
80
88
88 80
71
9
40 30 75
43 77
45
44
76 48
53
10
72 70 35
77 23
91
92
92 76
70
11
28 50 60
40 57
44
48
88 44
51
12
24 65 25
30 69
43
48
84 48
48
13
20 60 20
27 70
40
52
88 56
48
14
24 60 45
63 50
80
88
60 84
62
15
24 62 40
57 43
79
84
40 88
57
16
36 60 55
40 77
48
52
88 60
57
5.3. Weight
determina
t
io
n
Usi
ng Eq.11
to cal
c
ulate t
he sco
r
e of
each
index,
su
ch a
s
sho
w
n in T
able
2; Usi
ng
Equation
s
(6) and
(7
) to de
termine
discrete ea
ch attr
i
bute inte
rval, according
to the si
ze
of ea
ch
attribute ra
ng
e. Discrete d
a
ta sho
u
ld be
finished. The
result
s are shown in Tabl
e 3.
Table 3. System simplifie
s
U
C1 C2 C3 C4 C5
C6 C7 C8 C9 D
1
2 1 3 1 3
1 2 3 1
2
2
2 1 3 1 3
1 1 3 1
1
3
2 1 3 1 3
1 3 3 1
2
4
2 1 1 1 3
1 2 3 1
2
5
2 1 3 1 3
1 2 3 1
2
6
2 1 3 1 3
1 2 3 2
2
7
3 3 3 3 1
3 3 3 3
3
8
3 3 3 3 1
3 3 3 3
3
9
2 1 3 1 3
1 2 3 2
2
10
3 3 2 3 1
3 3 3 3
3
11
2 1 3 1 2
1 2 3 1
2
12
2 2 1 1 3
1 2 3 1
1
13
1 2 1 1 3
1 2 3 1
1
14
2 2 2 2 2
2 3 2 3
2
15
2 2 2 2 2
2 3 1 3
2
16
2 2 3 1 3
1 2 3 2
2
From the Ta
b
l
e.3 the dedu
ction is a
s
foll
owin
g:
Evaluation Warning : The document was created with Spire.PDF for Python.
TELKOM
NIKA
ISSN:
1693-6
930
Ev
aluation Res
e
arc
h
of Trac
tion Motor
Perf
ormanc
e
for Mine Dump ....
(Huilai S
un)
339
U/ind
D
={(1,2,
3
,4,5,6,9,12,1
4
,15,16),
(
7,8,
10),(12,13
)}
U/ind
C
=
{
(1,5
)
,
(2),(
3
),(
4
),(
5
)
,
(6),(
7
),(
8
),
(
9
)
,
(10),
(
11
),(12
)
,(13
),(1
4),(
1
5
),(1
6)};
U/ind(c2,
c
3,c4,c5,c6,c7,
c8
,c9,c1
0,
c1
1,c
12)
={
(1,5),
(2)
,
(3),(
4
),(
6
),(
7
),(8),(9),(10),
(
11),(12,13
),(1
4),
(15
)
,(16
)};
U/ind(c1,
c
3,c4,c5,c6,c7,
c8
,c9,c1
0,
c1
1,c12)={
(1,5,16
)
,(2),
(
3),
(
4),
(
6),
(
7),
(
8),
(
9),
(
10
),(11
)
,(1
2
),(1
3),
(14
)
,(15
)};
U/ind(c1,
c
2,c4,c5,c6,c7,
c8
,c9,c1
0,
c1
1,c
12)
={
(1,4,5),
(
2
),(3
),(6
),(7
),
(8,10),(11),
(
12
),(13
)
,(1
4
),(1
5),
(16
)
};
U/ind(c1,
c
2,c3,c5,c6,c7,
c8
,c9,c1
0,
c1
1,c
12)
={
(1,5,9),
(
2
),(3
),(4
),(6
),
(
7
),(8
),(1
0),(
1
1
),(1
2),(
13),
(
14),
(15
)
,(16
)};
U/ind(c1,
c
2,c3,c4,c6,c7,
c8
,c9,c1
0,
c1
1,c12)={
(1,5,11
)
,(2),
(
3),
(
4),
(
6),
(
7),
(
8),
(
9),
(
10
),(12
)
,(1
3
),(1
4),
(15
)
,(16
)};
U/ind(c1,
c
2,c3,c4,c5,c7,
c8
,c9,c1
0,
c1
1,c
12)
={
(1,5),
(2)
,
(3),(
4
),(
5
),
(6,9,16),(7),(8),(10),(11),
(
12
),
(13
)
,(14
),(1
5)
};
U/ind(c1,
c
2,c3,c4,c5,c6,
c8
,c9,c1
0,
c1
1,c
12)
={
(1,5),
(2,
3
),(4
),(5
),(6
),
(
7
),(8
),(9
),(1
0)
,(11),
(
12
),(13
)
,
(14
)
,(15
),(1
6)
};
U/ind(c1,
c
2,c3,c4,c5,c6,
c7
,c9,c1
0,
c1
1,c
12)
={
(1,5),
(2)
,
(3),(
4
),(
5
),(
6
)
,
(7),(
8
),(
9
),(
1
0),(1
1
),(
12),
(
13),
(14,15
),(1
6)};
U/ind(c1,
c
2,c3,c4,c5,c6,
c7
,c8,c1
0,
c1
1,c
12)
={
(1,5,6),
(
2
),(3
),(4
),(5
),
(
6
),(7
),(8
),(9
),(
10),(
11),
(
12
),
(13
)
,(14
),(1
5),(16)};
And then,
posc(D)= 1
4
; posc-c1
(D)= 12;
posc-c2
(D)= 13; po
sc-c3(
D)= 1
1
; po
sc-c4(D)= 13;
posc-c5
(D)= 13; posc-c6
(D)= 11; po
sc-c7(
D)= 1
2
; po
sc-c8(D)=
12;
posc-c9
(D)=
13
From the Eq.
8
and 9, we
can get:
γ
c(D)=14/1
6
;
γ
c-{
c
1}
(D)=1
2
/16;
γ
c-
{c
2}(D
)=
13/16;
γ
c-{
c
3}(D
)=
11/16;
γ
c-{
c
4}
(D)=13/16;
γ
c-{
c
5}
(D)=1
3
/16;
γ
c-
{c
6}(D
)=
11/16;
γ
c-{c
7}(D
)=
12/16;
γ
c-{
c
8}
(D)=12/16;
γ
c
-
{
c
9}D
)
=
1
3
/
16
。
From Eq.10
we get ea
ch
weig
ht indicat
o
rs:
λ
1
=
0.12
5;
λ
2
=
0.06
25;
λ
3
=
0.18
75;
λ
4
=
0.06
25;
λ
5
=
0.06
25;
λ
6
=
0.18
75;
λ
7
=
0.12
5;
λ
8=0.125;
λ
9
=
0.06
25;
Analysis
of the final weight
indicator
sho
w
s th
at: the consta
nt po
we
r ra
nge
and v
o
lume
of a la
rge
r
si
ze
will affe
ct
the moto
r's compr
ehe
nsiv
e evalu
a
tion i
ndex, but
overloa
d
m
u
ltiples,
response tim
e
, cost and traffic ut
ilization factor i
s
little difference i
n
a variety of motor evaluation
sho
u
ld be rel
a
tively weake
ned.
For
example,
take
the
origi
nal ave
r
ag
e t
he 7th
high
est perm
ane
nt
magnet
syn
c
hron
ou
s
motor analy
s
i
s
, we ca
n se
e
than E7 = 74.99%, further
highlightin
g the advantag
e
s
in the origin
al
basi
s
. Ove
r
all
evaluation
of perm
ane
nt
magnet
sy
n
c
hron
ou
s mot
o
r in th
e
co
st and
cont
rol in
dex
is n
o
t very
good,
but th
e go
od
com
p
reh
e
n
s
iv
e u
t
ilization
rate
ma
kes the
co
mprehe
nsive
evaluation i
n
dex is hi
gh;
on the oth
e
r hand, in
du
ction motor al
though
co
st
is lo
w, but t
h
e
comp
re
hen
si
ve utilization
rate is low,
unable to
p
l
ay a maximum efficien
cy of the system.
Switche
d
rel
u
ctan
ce mot
o
r and b
r
u
s
hless DC
m
o
tor control
system b
a
se
d on the m
a
ture
insuffici
ently, the
com
p
re
hen
sive eval
uation i
ndex
in thi
s
field
is
not
high,
but h
a
s b
r
oad
popul
ari
z
atio
n p
r
o
s
pe
ct. Thi
s
a
naly
s
is sho
w
s that this
system can
be
co
nvenie
n
t for
comp
re
hen
si
ve evaluation
of multi-moto
r.
The a
c
tual ro
ad co
ndition
s efficient use
and t
he efficient usin
g of
diesel ele
c
tri
c
group
must b
e
com
b
ined
with th
e re
al vehi
cle
and
platform
experim
ent
and a
nalysi
s
,
In the pl
atform
experim
ent,di
e
sel
ele
c
tri
c
gro
up
and
gen
erato
r
s are
a
s
sh
own
in Fi
gu
re 2,
Moto
r and
dynamom
eter se
ction i
s
sh
own i
n
Fig
u
re
3, the d
a
ta i
n
Tabl
e 3 i
s
f
o
r ma
nufa
c
tu
rers to
provide a
basi
c
d
e
si
gn
data. The
system we built
ensure
s
that
energy tran
sport fro
m
the
diesel-el
e
ct
ric
grou
p to m
o
tor afte
r the
re
ctifier inve
rter, by wa
y of re
ctifier a
nd inv
e
rter. T
hen t
h
e dynam
omet
er
turbine
con
s
umes th
e po
wer.
We sel
e
cted t
he Cu
mmins
En
gin
e
(Cummin
s
QSL9-C3
25) as
sho
w
n i
n
Fig
u
re
2. As
sho
w
n in
Figu
re
4, it's
the e
n
g
i
ne spee
d-to
rque
cu
rve we
mea
s
ured in
the
laboratory. T
he e
ngine
co
mmon i
n
terva
l
is from
120
0 to 1
800
rp
m. This is en
ough
to me
et the
deman
d for g
enerators. Ta
ble 4 for t
he a
c
tual vehi
cle
measurement
data:
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2
340
Figure 2. Die
s
el ele
c
tri
c
group an
d gen
e
r
ators
Figure 3 in-wheel moto
r an
d danam
omet
er.
For efficient use
of
hi
gh efficient
utili
zation
of th
e
actual
ro
ad
con
d
ition
s
a
n
d
die
s
el
gene
rato
r, th
e wheel
redu
cer mu
st
be
combi
ned
wit
h
the
re
al ve
hicle
an
d pl
atform exp
e
rim
ent
were mea
s
u
r
ed and an
alyzed, the ori
g
inal data in Table 3 provid
e basi
c
de
si
gn data for the
factory. Table
4 sho
w
s the
real me
asure
m
ent data.
Table 4 me
asurem
ent data
U
IM PMSM BLDC
Diesel Elect
r
ic Gr
oup
Efficient
ran
ge
/
％
85 90
81
Wheel
side re
d
u
cer efficient ra
nge
/
％
82 92
85
Tra
ffic efficie
n
t
ran
ge
/
％
82 85
80
Comp
ari
s
o
n
of
the
me
asu
r
ed data, we found
t
hat th
e differe
nce i
s
n
o
t big fo
r road u
s
e
efficien
cy, the weig
ht sh
ould be a
p
p
r
op
riately
re
duced, relati
ve to the differences i
n
the
efficien
cy of the use of fire
woo
d
in the e
l
ectri
c
dr
ive i
s
big different f
r
om hyb
r
id ca
rs d
r
ive turbi
n
e
whe
e
l sid
e
redu
cer,
sho
u
l
d be given
full att
ention, adjust the
weig
hts, the
advantage
of
perm
ane
nt m
agnet
synchronou
s m
o
tor i
s
mo
re a
ppa
r
ent, whi
c
h al
so bea
rs out o
u
r roug
h sets to
the accuracy
of the theoret
i
c
al sy
stem ev
aluation.
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Ev
aluation Res
e
arc
h
of Trac
tion Motor
Perf
ormanc
e
for Mine Dump ....
(Huilai S
un)
341
Figure 4.Mea
s
ured commo
nly used e
ngi
ne cu
rve
6. Conclusio
n
In acco
rdan
ce with the
m
a
in source
of sup
p
ly of the dump
tru
c
k elect
r
ic
drive
syste
m
and ele
c
tri
c
d
r
ive ene
rgy transfe
r
characteristics evalu
a
tion index system, a seri
es of evaluati
o
n
indicators propo
sed to
make th
e motor evalu
a
tion more
objective. The metho
d
of
comp
re
hen
si
ve evaluatio
n ba
sed o
n
roug
h sets mining d
u
m
p tru
ck traction m
o
tor, the
evaluation
in
dex to ma
ke
effective u
s
e of the
ro
ug
h set evalu
a
tion
system.
Acco
rdi
ng to
the
importa
nce of perform
an
ce
indicato
rs in
dex, bas
ed o
n
roug
h set
s
empo
we
ring
way, provide
s
a
theoreti
c
al b
a
si
s for the
sele
ction of
para
m
eter
s o
f
transmi
ssio
n system
an
d ele
c
tric
m
o
tor
matchin
g
, sh
orten th
e de
velopment
cycle. The
co
mbination
of
platform
experim
ent dat
a,
simulatio
n
re
sults an
d
real
ca
r l
ong
-term me
a
s
u
r
em
ent data
verif
y
the a
c
curacy and
usefuln
e
ss
of the overall perfo
rman
ce
evaluation m
e
thod ba
se
d on the rou
gh
set method m
o
tor.
Ackn
o
w
l
e
dg
ment
This
work wa
s sup
p
o
r
ted by
the Nation
al
Hi
gh Te
ch
nology Re
se
arch and
Developme
n
t
Program of China (G
ra
nt NO: 2011AA06
0404, Unde
rg
roun
d intellig
ent mining tru
c
k).
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uel
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930
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Vol. 12, No. 2, June 20
14: 333 – 34
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342
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