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Chapter
Stator Winding Fault Diagnosis of
Permanent Magnet Synchronous
MotorBased DTCSVM Dedicated
to Electric Vehicle Applications
Fatma Ben Salem
Abstract
Electric vehicles (EVs) have several advantages such as energy efficiency, virtu
ally lack of pollution, and the availability of electric energy through electric distri
bution systems. Among the major components of an EV is the block control of the
AC motor. Many modern highperformance control technologies are being used in
EV controllers, such as direct torque controlbased space vector modulation (DTC
SVM). Given that permanent magnet synchronous motor (PMSM) has a small
volume, a lightweight, and a high reliability, attracting the interest of EV industrial
designers. The fault diagnosis about the PMSM problems is essential because the
PMSM has a huge influence on the safety and economic efficiency with the vehicles.
In this background, the chapter concerns the modeling and simulation of an electric
vehicle drive system including a PMSMbased DTCSVM without and with stator
winding fault. The performance of the motor under both the normal and faulty
conditions is simulated. For the diagnosis of the fault, the chapter proposes the
technique based on the motor current spectrum analysis.
Keywords: permanent magnet synchronous motor, electric vehicles, DTCSVM,
stator winding fault, diagnosis, fault signature extraction
1. Introduction
Electric vehicles (EVs) have several advantages such as energy efficiency, virtu
ally lack of pollution, and the availability of electric energy through electric distri
bution systems [1–4]. Among the major components of an electric vehicle is the
controlling block of the AC motor. The controller should be designed to make the
drive system robust and efficient on both dynamic and steadystate performances.
Many modern highperformance control technologies are being used in EV
controllers, such as direct torque controlbased space vector modulation (DTC
SVM) [5–12]. The advantage of the DTCSVM methodology is that it has all the
merits of DTC strategy [13–16] by adding the fact of having a fixed switching
frequency, which guarantees low vibrations in order to provide passenger comfort.
Permanent magnet synchronous motor (PMSM) becomes more suitable in wide
speed range application due to their high efficiency and wide constant power speed
range. In fact, the absence of rotor windings and therefore the absence of external
1
excitation increase the efficiency of the PMSM and greatly reduce its maintenance
cost. In addition, the drop in the price of permanent magnets promotes a strong use
of this type of machine particularly in the field of electric vehicle applications
[17–20]. In fact, such motor has a small volume, lightweight, and high reliability
attracting the interest of EV industrial designers.
So the fault diagnosis about the PMSM problems is essential because the PMSM
has a huge influence on the safety and economic efficiency of the vehicles. The
stator winding fault is a common fault that has interested researchers for many
years [21–27]. It is resulting from the degradation of the interturn interphase and
main isolation of the motor winding. This internal fault will increase the torque
ripples that deteriorate machine performance. However such fault can be rapidly
propagated to motor stator turn since it makes a large circulating current in the
shorted path yielding excessive heat. The adverse condition of heat will occasionally
lead to the progressive deterioration and eventual breakdown of winding insulation
in the phase of the motor.
Several methods have been used to detect and estimate the type and the degree
of this fault in PMSM. The motor signature current analysis is one of the most
common online methods for fault detection. In fact, it is widely used in the field of
PMSM fault diagnosis, because it is fast and does not need any specific model. This
method uses spectral analysis techniques by comparing the healthy to the faulty
case; faults can be detected.
In this chapter, as for signal processing tools, fast Fourier transform (FFT) is
used to extract the frequency characteristics of the stator current signal. This
method will be proposed to detect whether a PMSM, under DTCSVM traction
system, is healthy or faulty.
The chapter is organized as follows. Electric vehicle propulsion system scheme is
developed in Section 2. In Section 3, the mathematical model of PMSM in (a, b, c)
frame in healthy conditions is introduced and which is followed by Section 4, the
PMSM with interturn fault modeling. Then, the design of a conventional DTC
SVM traction system is presented. Simulation result, considering steadystate oper
ation, is discussed in Section 6.
2. Electric vehicle propulsion system scheme
The major electric propulsion system of EV consists of motor, controller, power
source, charger, transmission device, and wheels (Figure 1) [28]. The proposed
motor drive includes the electric motor (PMSM), power converter (threephase
voltage inverter), energy storage (battery), and electronic controller (DTCSVM).
These components are the core of the EV propulsion system.
The tractive effort (Fte) is the force propelling the vehicle forward, transmitted
to the ground through the drive wheels. Consider a vehicle of mass Mv, proceeding
at a velocity Vv,asinFigure 2. The force propelling the vehicle forward, the
tractive effort, has to overcome the following forces:
•The rolling resistance force: Frrol ¼μMvg
where μis the coefficient of rolling resistance (μ¼0:005 for tires developed
especially for electric vehicles), Mvis the vehicle mass, and gis the gravitational
constant
•The aerodynamic drag: Fad ¼1
2ρACdV2
v
2
Autonomous Vehicle and Smart Traffic
where ρis the air density, Ais the frontal area, Cdis the drag coefficient, and Vv
is the vehicle speed
•The hill climbing force: Fhc ¼Mvgsinα
where αis the angle of a slope for a vehicle climbing a hill (in the case of Figure 2
α¼0).
Fte is equal to the sum of the resistance forces [28, 29], as shown in the sequel
equation:
Fte ¼Frrol þFad þFhc (1)
2.1 Voltage source inverter
The DC voltage made constant by the rectifier is delivered by the battery to the
inverter input, which thanks to controlled transistor switches, converts this voltage
to threephase AC voltage signal with widerange variable voltage amplitude and
frequency.
The inverter one leg consists of two transistor switches. A simple transistor
switch consists of feedback diode connected in antiparallel with transistor.
Control
Transmission
PMSM
Software:
DTCSVM
Energy
storage
Two level
inverter
Figure 1.
Components of electric vehicle propulsion system.
Frrol
Fad
Ft
Mvg
Figure 2.
The forces acting on a vehicle.
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Stator Winding Fault Diagnosis of Permanent Magnet Synchronous MotorBased DTCSVM…
DOI: http://dx.doi.org/10.5772/intechopen.88784
Feedback diode conducts current when the load current direction is opposite to the
voltage direction.
Assuming that the power devices are ideal, when they are conducting, the voltage
across them is zero and they present an open circuit in their blocking mode. Therefore,
each inverter leg can be represented as an ideal switch. It gives thepossibility to connect
each of the three motor phase coils to a positive or negative voltage of the DC link (E0).
Considering a twolevel inverter, presented by Figure 3, the voltage vector of
the threephase voltage inverter is represented as follows:
Vs
!¼ﬃﬃﬃ
2
3
rSaþSbej2π
3þScej4π
3
hi (2)
where Sa,Sb, and Scare threephase inverter switching functions, which can
take a logical value of either 0 or 1.
3. Mathematical model of PMSM in (a, b, c) frame
An accurate dynamic model of the PMSM is necessary to study the dynamic
behavior of the machine. Indeed, the dynamic behavior of a PMSM is described in
terms of space variables as follows:
Vabc ¼RsIabc þLs
d
dt Iabc þd
dt Φmabc (3)
considering Vabc ¼vavbvc
½
T,Iabc ¼iaibic
½
T, and
dΦmabc
dt ¼Φmωrcos θr
ðÞcos θr2π
3
cos θrþ2π
3
T
where Vabc,Iabc , and Φmdenote the stator voltages, the stator currents, and the
permanent magnetic flux amplitude, respectively. Rsand Lsdenote the stator resis
tance and inductance matrix, respectively.
Φmabc ¼Φm
sin θr
ðÞ
sin θr2π
3
sin θrþ2π
3
2
6
6
6
6
6
4
3
7
7
7
7
7
5
(4)
SaSbSc
SaSbSc
E0
2
E0
2
Figure 3.
Twolevel threephase voltage inverter.
4
Autonomous Vehicle and Smart Traffic
since ωr=Npωm,ωrand ωmtorque pulsation and mechanical pulsation, respec
tively. θris the angular position of the rotor with respect to the magnetic axis of the
phase (a) of the stator, θr=Npθm,θmdenotes the mechanical angular position of the
rotor, and Npis the pole pair number.
The electromagnetic torque can be expressed as follows:
Tem ¼eaiaþebibþecic
Ωm
(5)
where ea,eb, and ecare the emf of the phases a,b, and cand Φmabcf ¼Φmeaebec
½.
Then referring to Eq. (4), the developed equation of electromagnetic torque becomes
Tem ¼
Φmsin θr
ðÞiaþsin θr2π
3
ibþsin θrþ2π
3
ic
Ωm
(6)
The mechanical part of the machine is described by
Jd
dt Ωm¼Tem Tl(7)
where Jis the motor inertia, Tem is the electromagnetic torque, and Tlis the load
torque.
4. Modeling of the PMSM with interturn fault
An interturn fault represents an insulation failure between two windings in the
same phase of the stator [23].
The representation of a PMSM with stator winding turn fault at phase (a) is
shown in Figure 4;a2and a1represent the shorted turns and the healthy turns,
respectively. The fault is modeled by a small resistance Rfconnected across the
shorted turns. In fact, Rsdenotes the interturn short circuit resistance.
To represent the impact of the defect, a new parameter σis introduced. Param
eter σis defined as the ratio between the number of shorted turns Ncc and the total
number of turns Ns.
The resistances of the subwinding a1and the shorted subwinding a2are noted
by Ra1and Ra2, respectively; they are proportional to the number of turns of the
involved parties. Therefore, we can express them according to the resistance Raand
the coefficient σ. So we have
Ra1¼1σðÞRa,R
a2¼σRa(8)
By defining the electrical quantities of the new circuit with the index “f”,and
refering to Figure 5 the new equations of the motor voltages are reformulated as follows:
Va¼Ra1þRa2
ðÞiaþLa1þLa2þ2Ma1a2
ðÞ
dia
dt þMa1bþMa2b
ðÞ
dib
dt
þMa1cþMa2c
ðÞ
dic
dt þeaþef
Ra2ifLa2þMa1a2
ðÞ
dif
dt
Vb¼RsibþLdib
dt þMa1bþMa2b
ðÞ
dia
dt þMdic
dt þebMa2b
dif
dt
Vc¼RsicþLdic
dt þMa1cþMa2c
ðÞ
dia
dt þMdib
dt þecMa2c
dif
dt
(9)
5
Stator Winding Fault Diagnosis of Permanent Magnet Synchronous MotorBased DTCSVM…
DOI: http://dx.doi.org/10.5772/intechopen.88784
where L and M denote the phase selfinductance and M is the mutual inductance
between phase windings of healthy PMSM, respectively. And considering
La1¼1σðÞ
2La,La2¼σ2Laand Ma1a2¼σ1σðÞLa.
ib
i
c
ia
Rf
a1a2
b
c
Figure 4.
Equivalent circuit of PMSM under interturn fault in phase (a).
if
rf
ea2
eb
ec
Lc
Lb
La1La2
ea1
Ma2b
Ma1b
Ma2c
Ma1c
Va2
Va1
ia
ib
ic
Figure 5.
Schematic representation of an insulation fault between turns on a phase of the stator.
6
Autonomous Vehicle and Smart Traffic
5. Design of a conventional DTCSVM traction system
The disadvantages of basic DTC is obvious: torque and flux ripples, deteriorated
performance at low speed, and uncontrolled switching frequency of the inverter.
For the defects of basic DTC, much works have been made over the past few
decades. DTC combined with space vector modulation (DTCSVM) for PMSM is to
accomplish constant switching frequency of the inverter in addition to obtain the
desired torque and stator flux with little ripples by synthesizing an appropriate
voltage space vector through SVM, which is more accurate than that of basic DTC
to compensate the error of desired and actual stator flux.
5.1 Flux reference coordinate computing
The relationship between the voltage, current, and stator flux vectors of a PMSM
is given by
d
dt Φs¼VsRsIs(10)
where Rsis the stator resistance.
The reference of stator flux amplitude and phase is stated using Concordia
quantities as
∣Φ∗
s∣¼ﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃﬃ
ϕ∗2
αsþϕ∗2
βs
q,θ∗
s¼arctan ϕ∗
βs
ϕ∗
αs
(11)
5.2 Voltage reference coordinate computing
The coordinates of references of voltage vectors v∗
αsand v∗
βsin (α,β) frame are
determined by the following equations:
v∗
αs¼ϕ∗
αsϕαs
Tem þRsiαs
v∗
βs¼ϕ∗
βsϕβs
Tem þRsiβs
8
>
>
>
<
>
>
>
:
(12)
These vectors are introduced to the SVM block, which use them to control the
inverter switches (Sa,S
b,S
c).
5.3 SVM block design
The SVM technique refers to a special switching scheme of the six power tran
sistors of a twolevel threephase voltage inverter. In fact, it uses eight sorts of
different switch modes of the inverter to control the stator flux to advance the
reference flux circle. Eight types of switch modes stand for eight space voltage
vectors that contain six active voltage vectors and two zero voltage vectors as
shown in Figure 6a [30, 31].
Voltage vectors, created by a threephase PWM inverter, divide the space vector
plane into six sectors: i1ðÞ
π
3<Si≤iπ
3,i¼1,…,6. The determination of the sector,
where the reference voltage vector is located, is done according to
7
Stator Winding Fault Diagnosis of Permanent Magnet Synchronous MotorBased DTCSVM…
DOI: http://dx.doi.org/10.5772/intechopen.88784
θ∗
s¼arctan v∗
βs
v∗
αs
(13)
The SVM’s principle is to project the desired stator voltage vector V
!sref on the
two adjacent voltage vectors Vi
!and V
!iþ1corresponding to two switching states of
the inverter. Values of these projections provide the determination of desired com
mutation times Tiand Tiþ1and correspond to two nonzero switching states of the
inverter. To maintain the constant commutation frequency, in the case where
TiþTiþ1≤Tmod, a zero state of the inverter is applied during the rest of the period
Tmod, i.e., T0¼Tmod TiþTiþ1
ðÞ. In what follows, the study will be limited to
sector S1, as presented in Figure 6b. As the reference voltage vector V
!sref is in sector
S1, it can be compounded by the active voltage vectors V1and V2. The projection on
these adjacent vectors gives the following expression:
V
!sref ¼V∗
sαþjV ∗
sβ
¼T1
Tmod
V1
!þT2
Tmod
V2
!(14)
where Tmod ¼T1þT2þT0.D1and D2are duties relative to voltages V1and V2.
In sector S1, expressions of the voltage vectors are
V
!1¼ﬃﬃﬃ
2
3
rE0cos 0 þjsin 0ðÞ¼
ﬃﬃﬃ
2
3
rE0
V
!2¼ﬃﬃﬃ
2
3
rE0cos π
3þjsin π
3
8
>
>
>
>
<
>
>
>
>
:
(15)
Expressions of T1and T2are detailed in the sequel:
T1¼ﬃﬃﬃ
3
2
rV∗
sα1
ﬃﬃﬃ
2
pV∗
sβ
!
Tmod
E0
T2¼ﬃﬃﬃ
2
pV∗
sβ
Tmod
E0
8
>
>
>
>
>
<
>
>
>
>
>
:
(16)
β
α
−→
V
2
(110)
−→
V
3
(010)
−→
V
4
(011)
−→
V
5
(001) −→
V
6
(101)
−→
V
1
(100)
−→
V
0
(000)
−→
V
7
(111)
2
3E0
E0
√2
V
∗
sβ
V
∗
sα
θ
∗
vs
S1
S2
S3
S4
S5
S6
−→
Vsref
(a)
β
α
−→
V2
−→
V1
2
3E0
E0
√2
−→
Vsref
D1−→
V1
D2−→
V2
S1
D1=T1
Tmod
D2=T2
Tmod
(b)
Figure 6.
(a) Basic switching vectors and sectors. (b) Projection of the reference voltage vector on two adjacent vectors.
8
Autonomous Vehicle and Smart Traffic
Consequently, the expressions of the duties are given as follows:
D1¼ﬃﬃﬃ
3
2
rV∗
sα1
ﬃﬃﬃ
2
pV∗
sβ
!
1
E0
D2¼ﬃﬃﬃ
2
pV∗
sβ
1
E0
8
>
>
>
>
<
>
>
>
>
:
(17)
The time duration of each nonzero vector is divided equally into two parts, the
time duration of zero vectors is distributed equally to V
!0and V
!7, and thus the
switching sequence of space vector is V
!0,V
!1,V
!2,V
!7,V
!7,V
!2,V
!1,V
!0during the
modulation period.
The duties of each phase of the inverter are calculated as follows:
Da¼D1þD2þ1
2D0
Db¼D2þ1
2D0
Dc¼1
2D0
8
>
>
>
>
>
<
>
>
>
>
>
:
(18)
As D1þD2þD0¼1, duties, given by the system of Eq. (18), turn to be
Da¼1
21þﬃﬃﬃ
3
2
rV∗
sα
E0þ1
ﬃﬃﬃ
2
pV∗
sβ
E0
!
Db¼1
21ﬃﬃﬃ
3
2
rV∗
sα
E0þ1
ﬃﬃﬃ
2
pV∗
sβ
E0
!
Dc¼1
21ﬃﬃﬃ
3
2
rV∗
sα
E01
ﬃﬃﬃ
2
pV∗
sβ
E0
!
8
>
>
>
>
>
>
>
>
>
>
>
<
>
>
>
>
>
>
>
>
>
>
>
:
(19)
5.4 Block diagram of the DTCSVM
The DTCSVM block diagram retains all the advantages of the conventional
DTC, such as no coordinate transformation, robust to motor parameters, etc.
Moreover, a SVM block is used to generate the pulses for the inverter in order to
promise a fixed commutation frequency.
Figure 7 illustrates the block diagram of the proposed traction control system,
and the overall control scheme is set as follows:
•Including two major loops: the torque control loop and the flux control loop. In
fact, the flux and torque are directly controlled individually. The basic principle
of the direct torque control is to destine the torque error and the flux error in
hysteresis bands by properly choosing the switching states of the inverter.
•The speed command is compared with the estimating speed to compute the
speed error. Then, the speed error is processed by the PI speed controller to
obtain the torque command. On the other hand, the flux command is
compared to the estimated flux.
•The errors ΔTem and ΔΦsgo through the hysteresis controllers and the vector
selection table to generate the required switching states and therefore the
desired voltage vector.
9
Stator Winding Fault Diagnosis of Permanent Magnet Synchronous MotorBased DTCSVM…
DOI: http://dx.doi.org/10.5772/intechopen.88784
•The controllers produce the voltage command vector; an appropriate space
voltage vector can be generated with SVM.
6. Simulation end discussion
Parameters of the PMSM are listed in Table 1. It has the following ratings: 220 V,
10 kW, and 1470 rpm at 50 Hz.
The parameters of the electric vehicle model are given in Table 2.
6.1 Case study
We consider a vehicle traveling along a straight horizontal road. For Fhc ¼0, the
tractive effort is reduced to Fte ¼Frrol þFad, and the load torque can be expressed as
Tr¼RgrF
rrol þFad
ðÞ¼, where Rg¼1
Gand G denotes the gear ratio.
After development the load torque is
Tl¼K1þK2V2
v(20)
Concordia
transform
Stator ﬂux
estimator
Torque φαs
φβs
Φ∗
s
Φs
T∗
em +


+
θs
cφcτ
iαs iβs
Tem
SVM
V∗
αs V∗
βs
estimator
SaSbSc
SaSbSc
Induction
E0
Motor
PI speed
controller
Hysteresis
stator ﬂux
controller
Hysteresis
torque
controller
Vector
selection table
ias ibs ics vas vbsvcs

+
Ωm
Ω∗
m
Ωm
Wheel + Gear
Accelerator
Figure 7.
Block diagram of SVMDTC PMSM drive.
Rs¼0:29ΩLs¼Lr¼50 mH Np¼2
Rr¼0:38ΩM¼47:3mH J¼0:5 Kg.m2
Table 1.
PMSM parameters.
10
Autonomous Vehicle and Smart Traffic
where K1¼RgrμMvgand K2¼1
2RgrρACdV2
v.
The relationship between vehicle speed and motor speed is given by
Vv¼RgrΩm(21)
Simulation tests were performed in healthy and faulty conditions, with the
motor driving a load torque, referring to Eqs. (20) and (21), and can be expressed as
follows:
Tl¼K1þK2Rgr
2Ω2
m(22)
The magnitude of the torque and flux hysteresis bands is 0.01 N.m and
0.001 Wb, respectively.
6.2 Steadystate operation analysis
Figure 8 shows several features of the PMSM drive at steadystate operation
considering a speed Ωm¼750 rpm. Waveforms presented in the left side (subscript
“1”)ofFigure 8 represent results yielded by the PMSM under DTCSVM without
fault. The middle side (subscript “2”)ofFigure 8 represents the results yielded by
the PMSM under DTCSVM considering 5% turns are shorted. The right side
r¼0:3mA¼1m2
Mv¼400 Kg Cd¼0:19
G= 0.9 ρ¼1:2 Kg/m3
Table 2.
The electric vehicle model parameters.
0 1 2
0
500
1000 Ωm(rpm)
t (s)
(a1)
0 1 2
0
50
100
150 Tem(Nm)
t (s)
(b1)
0 1 2
0
0.5
1
1.5 Φs(Wb)
t (s)
(c1)
0 1 2
0
500
1000 Ωm(rpm)
t (s)
(a2)
0 1 2
0
50
100
150 Tem(Nm)
t (s)
(b2)
0 1 2
0
0.5
1
1.5 Φs(Wb)
t (s)
(c2)
0
1 2
0
500
1000 Ωm(rpm)
t (s)
(a3)
0
1 2
0
50
100
150 Tem(Nm)
t (s)
(b3)
0
1 2
0
0.5
1
1.5 Φs(Wb)
t (s)
(c3)
0 1 2
0
500
1000 Ωm(rpm)
t (s)
(a1)
0 1 2
0
50
100
150 Tem(Nm)
t (s)
(b1)
0 1 2
0
0.5
1
1.5 Φs(Wb)
t (s)
(c1)
0 1 2
0
500
1000 Ωm(rpm)
t (s)
(a2)
0 1 2
0
50
100
150 Tem(Nm)
t (s)
(b2)
0 1 2
0
0.5
1
1.5 Φs(Wb)
t (s)
(c2)
0
1 2
0
500
1000 Ωm(rpm)
t (s)
(a3)
0
1 2
0
50
100
150 Tem(Nm)
t (s)
(b3)
0
1 2
0
0.5
1
1.5 Φs(Wb)
t (s)
(c3)
Figure 8.
(subscript “1”) Considering the PMSM under DTCSVM without fault, (subscript “2”) considering the PMSM
under DTCSVM allowing for 5% shorted turns, and (subscript “3”) considering the PMSM under DTCSVM
allowing for 25% shorted turns. Legend: (a) speed and its reference, (b) electromagnetic torque, and (c) stator
phase current.
11
Stator Winding Fault Diagnosis of Permanent Magnet Synchronous MotorBased DTCSVM…
DOI: http://dx.doi.org/10.5772/intechopen.88784
(subscript “3”)ofFigure 8 represents the results yielded by PMSM under
DTCSVM considering 25% turns are shorted.
From the analysis of the previous steadystate simulation results, one can remark
the following:
•The speed follows its reference despite the presence of defect. It is clear that in
the case of machine with short circuit fault, the speed oscillates around its
reference with a ripple amplitude that increases when the percentage of turns
shorted increases.
•It is seen in Figure 8 when 5 and 25% turns are shorted, respectively, in one of
the phase (a) windings, the increase of torque ripples is notable.
•The stator flux shapes, in healthy and faulty conditions, are quite similar.
6.3 Signature extraction based on the analysis of the fault effect
From the analysis of Figure 9, one can notice that a short circuit fault between
turns on phase (a) increases the amplitude of the second harmonic which was too
low in the spectrum of the healthy machine. This harmonic introduced by the defect
presents an amplitude that evolves the rate of defect in the sense that this harmonic
sees its amplitude increases in a proportional way with the increase of the number
of turns short circuited on the phase (a). When we increase the rate of the short
circuit, the amplitude of this harmonic has increased in value.
0 0.01 0.02
−50
0
50 one period of ia
(Ωm=750 rpm)
t (s)
(a1)
0 10 20
0
0.5
1
N
(b1)
0 10 20
0
0.05
0.1
N
(c1)
0 0.01 0.02
−50
0
50 one periode of ia
(Ωm=750 rpm)
t (s)
(a2)
0 10 20
0
0.5
1
N
(b2)
0 10 20
0
0.05
0.1
N
(c2)
0 0
.
0
1
0
.
0
2
−50
0
50 one period of ia
(Ωm=750 rpm)
t (s)
(a3)
0
1
0
2
0
0
0.5
1
N
(b3)
0
1
0
2
0
0
0.05
0.1
N
(c3)
Figure 9.
(a) One period of ias, (b) reduced spectrum of ias with respect to fundamental, and (c) harmonic of ias
(fundamental = 1). (subscript “1”) considering the PMSM under DTCSVM without fault, (subscript “2”)
considering the PMSM under DTCSVM allowing for 5% shorted turns, and (subscript “3”) considering the
PMSM under DTCSVM allowing for 25% shorted turns.
12
Autonomous Vehicle and Smart Traffic
In light of this analysis, it clearly appears that, in general, the harmonic ampli
tude increases in an apparent way when there is a short circuit fault.
7. Conclusion
The chapter focused on a study and diagnosis of the PMSM under DTCSVM
integrated in EV propulsion system without and with stator winding fault. Simula
tion results have been presented in order to demonstrate that in a DTCSVM PMSM
drive, with stator interturn short circuits, the considered defect affects the
dynamics of the motor and introduces a strong second harmonic in the motor
supply currents, which can be used to detect this type of fault. This ascertainment
can be used in the industry for fault detection and diagnosis of stator winding faults
of PMSM.
Author details
Fatma Ben Salem
Control and Energy Management Laboratory (CEMLab), University of Sfax, Sfax
Engineering School, Sfax, Tunisia
*Address all correspondence to: fatma.bensalem@isgis.usf.tn; fatma_bs@yahoo.fr
© 2020 The Author(s). Licensee IntechOpen. Distributed under the terms of the Creative
Commons Attribution  NonCommercial 4.0 License (https://creativecommons.org/
licenses/bync/4.0/), which permits use, distribution and reproduction for
noncommercial purposes, provided the original is properly cited. –NC
13
Stator Winding Fault Diagnosis of Permanent Magnet Synchronous MotorBased DTCSVM…
DOI: http://dx.doi.org/10.5772/intechopen.88784
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