Chapter

Permanent-Magnet Synchronous
Machine Drives
Adhavan Balashanmugham and Mockaisamy Maheswaran

Abstract

The permanent-magnet synchronous machine (PMSM) drive is one of best

choices for a full range of motion control applications. For example, the PMSM is
widely used in robotics, machine tools, actuators, and it is being considered in high-
power applications such as industrial drives and vehicular propulsion. It is also used
for residential/commercial applications. The PMSM is known for having low torque
ripple, superior dynamic performance, high efficiency and high power density. Sec-
tion 1 deals with the introduction of PMSM and how it is evolved from synchronous
motors. Section 2 briefly discusses about the types of PMSM. Section 3 tells about the
assumptions in PMSM for modeling of PMSM and it derives the equivalent circuit of
PMSM. In Section 4, permanent magnet synchronous motor drive system is briefly
discussed with explanation of each blocks in the systems. Section 5 reveals about the
control techniques of PMSM like scalar control, vector control and simulation of
PMSM driven by field-oriented control using fuzzy logic control with space vector
modulation for minimizing torque ripples. PMSM control with and without rotor
position sensors along with different control techniques for controlling various
parameters of PMSM for different applications is presented in Section 6.

Keywords: types of PMSM, modelling of PMSM, construction of PMSM drive

systems, control techniques of PMSM, advanced topics in PMSM drives sensored
control and sensorless control

1. Introduction

The electric motors are electromechanical machines, which are used for the
conversion of electrical energy into mechanical energy. The foremost categories of
AC motors are asynchronous and synchronous motors. The asynchronous motors
are called singly excited machines, that is, the stator windings are connected to AC
supply whereas the rotor has no connection from the stator or to any other source of
supply. The power is transferred from the stator to the rotor only by mutual
induction, owing to which the asynchronous motors are called as induction
machines.
The synchronous motors require AC supply for the stator windings and DC
supply for the rotor windings. The motor speed is determined by the AC supply
frequency and the number of poles of the synchronous motor, the rotor rotates at
the speed of the stator revolving field at synchronous speed, which is constant. The
variations in mechanical load within the machine’s rating will not affect the motor’s
synchronous speed [1].

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One of the types of synchronous motor is the PMSM. The PMSM consists of
conventional three phase windings in the stator and permanent magnets in the
rotor. The purpose of the field windings in the conventional synchronous machine
is done by permanent magnets in PMSM. The conventional synchronous machine
requires AC and DC supply, whereas the PMSM requires only AC supply for its
operation. One of the greatest advantages of PMSM over its counterpart is the
removal of dc supply for field excitation as discussed in [2].
The development of PMSM has happened due to the invention of novel mag-
netic materials and rare earth materials. PMSM give numerous advantages in
scheming recent motion management systems. Energy efficient PMSM are designed
due to the availability of permanent magnet materials of high magnetic flux density.
In synchronous motors the rotor rotates at the speed of stator revolving field.
The speed of the revolving stator field is called as synchronous speed. The synchro-
nous speed (ωs) can be found by the frequency of the stator input supply (fs), and
the number of stator pole pairs (p). The stator of a three phase synchronous motor
consists of distributed sine three phase winding, whereas the rotor consists of the
same number of p-pole pairs as stator, excited by permanent magnets or a separate
DC supply source as given in [3].
When the synchronous machine is excited with a three phase AC supply, a
magnetic field rotates at synchronous speed develops in the stator. The synchronous
speed of this rotating magnetic field is shown by the Eq. (1).


N ¼ 120 f s =P rpm (1)

where N, synchronous speed, fs, frequency of AC supply in Hz; P, number of

poles; p, pole pairs and it is given by (P/2).

2. Types of PMSM

The PMSM are classified based on the direction of field flux are as follows,

1. Radial field

2. Axial field

In radial field, the flux direction is along the radius of the machine. The radial
field permanent magnet motors are the most commonly used. In axial field, the flux
direction is parallel to the rotor shaft. The axial field permanent magnet motors are
presently used in a variety of numerous applications because of their higher power
density and quick acceleration.
The permanent magnets can be placed in many different ways on the rotor of
PMSM as discussed in [3, 4]. Figures 1 and 2 show the permanent magnets
mounted on the surface of the outer periphery of rotor laminations. This type of
arrangement provides the highest air gap flux density, but it has the drawback of
lower structural integrity and mechanical robustness. Machines with this arrange-
ment of magnets are known as Surface mount PMSMs.
One other types of placing the permanent magnets in the rotor, is embedding the
permanent magnets inside the rotor laminations. This type of machine construction
is generally referred to as Interior PMSM and it is shown in Figures 3 and 4.
The development of this arrangement is more difficult than the surface mount
or inset magnet permanent magnet rotors. The inset permanent magnet rotor con-
struction has the advantages of both the surface and interior permanent magnet

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Figure 1.
Surface permanent magnet.

Figure 2.
Surface inset permanent magnet.

rotor arrangements by easier construction and mechanical robustness, with a high

ratio between the quadrature and direct-axis inductances, respectively.
The surface PMSM with radial flux are generally applied for applications which
require low speed operations. These machines have the advantage of high power
density than the other types of PMSM. The interior PMSM are used for applications
which require high speed.
The principle of operation is identical for all the types of PMSM, in spite of the
types of mounting the permanent magnets in the rotor.

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Figure 3.
Interior permanent magnet.

Figure 4.
Interior permanent magnet with circumferential orientation.

The important significance of the type of mounting the permanent magnets on

the rotor is the variation in direct axes and quadrature axes inductance values,
which is explained below. The primary path of the flux through the permanent
magnets rotor is the direct axis. The stator inductance when measured in the
position of permanent magnets aligned with stator winding is called as direct axis
inductance. The quadrature axis inductance is measured by rotating the magnets
from the already aligned position (direct axis) by 90°, in this position the iron (inter
polar area of the rotor) sees the stator flux. The flux density of the permanent
magnet materials is presently high and its permeability is almost equal to that of the

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air, such that the air gap between the rotor and stator of PMSM can be treated as an
extension of permanent magnet thickness. The reluctance of direct axis is always
greater than the quadrature axis reluctance, since the effectual air gap of the direct
axis is several times that of the real air gap looked by the quadrature axis.
The significance of such an uneven reluctance is that the direct axis inductance
is greater than the quadrature axis inductance and it is shown in Eq. (2).

Ld > Lq (2)

where Ld is the inductance along the direct to the magnet axis and Lq is the
inductance along the axis in quadrature to the magnet axis.

3. Modeling of PMSM

For proper simulation and analysis of the system, a complete modelling of the
drive model is essential. The motor axis has been developed using d-q rotor refer-
ence frame theory as shown in Figure 5, as given [5]. At any particular time t, the
rotor reference axis makes an angle θr with the fixed stator axis and the rotating
stator mmf creates an angle α with the rotor d axis. It is viewed that at any time t,
the stator mmf rotates at the same speed as that of the rotor axis.
The required assumptions are obtained for the modelling of the PMSM without
damper windings.

1. Saturation is neglected.

2. Induced EMF is sinusoidal in nature.

3. Hysteresis losses and Eddy current losses are negligible.

4. No field current dynamics.

Figure 5.
Motor axis.

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Voltage equations from the model are given by,

Vq ¼ Rs iq þ ωr λd þ ρλq (3)
Vd ¼ Rs id  ωr λq þ ρλd (4)

Flux linkages are given by,

λq ¼ Lq iq (5)
λq ¼ L q i q þ λf (6)

Substituting Eq. (5) and Eq. (6) into Eq. (3) and Eq. (4)

Vq ¼ Rs iq þ ωr ðLd id þ λf Þ þ ρLd id (7)

Vd ¼ Rs id  ωr Lq iq þ ρðLd id þ λf Þ (8)

Arranging Eq. (7) and Eq. (8) in matrix form,

      
Vq Rs þ ρLq ωr Ld iq ωr λf
¼ þ (9)
Vd ωr Lq Rs þ ρLd id ρλf

The developed torque motor is being given by,

 
3 P

Te ¼ λd iq  λq id (10)
2 2

The mechanical torque equation is,

dωm
Te ¼ TL þ Bωm þ J (11)
dt

Solving for the rotor mechanical speed form Eq. (11)

ð 
Te  TL  Bωm
ωm ¼ dt (12)
J

and
 
2
ωm ¼ ωr (13)
P

In the above equations ωr is the rotor electrical speed, ωm is the rotor mechanical
speed.

3.1 Parks transformation and dynamic d-q modeling

The dynamic d-q modelling of the system is used for the study of motor during
transient state and as well as in the steady state conditions. It is achieved by
converting the three phase voltages and currents to dqo axis variables by using the
Parks transformation [4].
Converting the phase voltages variables Vabc to Vdqo variables in rotor reference
frame axis are illustrated in the equations,

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Figure 6.
Equivalent circuit of PMSM without damper windings.

2 3
2 3 cos ð θ  120 Þ cos ðθr þ 120Þ 2 3
Vq 6 cos θ r r
7 Va
6 7 26 76 7
4 Vd 5 ¼ 6 sin θr sin ðθr  120Þ sin ðθr þ 120Þ 74 Vb 5 (14)
34 5
Vo 1=2 1=2 Vc
1=2

Convert Vdqo to Vabc

2 3
2 3 sin θr 1 2 3
Va 6 cos θr 7 Vq
6 7 26 76 7
4 b5¼ 6
V cos ðθr  120Þ sin ðθr  120Þ 1 74 Vd 5 (15)
34 5
Vc cos ðθr þ 120Þ sin ðθr þ 120Þ Vo
1

3.2 Equivalent circuit of PMSM

Equivalent circuit is essential for the proper simulation and designing of the
motor. It is achieved and derived from the d-q modelling of the motor using the
voltage equations of the stator. From the assumption, rotor d axis flux is
represented by a constant current source which is described through the following
equation,

λf ¼ Ldm if (16)

where λf, field flux linkage; Ldm, d-axis magnetizing inductance; if, equivalent
permanent magnet field current.
Figure 6 shows the equivalent circuit of PMSM without damper windings.

4. Permanent magnet synchronous motor drive system

The motor drive essentially consists of four main components such as the
PMSM, the inverter, the main control unit and the position sensor. Interconnections
of the components are shown in Figure 7.

4.1 Inverter

For variable frequency and magnitude, voltage source inverters are devices
which convert the constant DC voltage level to variable AC voltage. As specified in
the function, these inverters are commonly used in adjustable speed drives.

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Figure 7.
Components permanent magnet synchronous motor drive.

Figure 8.
Voltage source inverter with DC supply and load (PMSM).

Figure 8 shows a voltage source inverter with a supply voltage Vdc and with six
switches. The frequency of the AC voltage can be variable or constant based on the
applications [2, 6].
Three phase inverters consist of a DC voltage source and six power ON/OFF
switches connected to the PMSM as shown in Figure 8. Selection of the inverter
switches must be carefully done based on the necessities of operation, ratings and
the application. There are several devices available in the market and these are
thyristors, bipolar junction transistors (BJTs), MOS field effect transistors
(MOSFETs), insulated gate bipolar transistors (IGBTs) and gate turn off thyristors
(GTOs). It has been inferred that MOSFETs and IGBTs are preferred in the industry
because of its advantages that the MOS gating permits high power gain and control
advantages. MOSFET is considered to be universal power ON/OFF device for low
power and low voltage applications, whereas IGBT has wide acceptance in the
motor drive applications and other application in the low and medium power range.
The power devices when used in motor drives applications require an inductive
motor current path provided by antiparallel diodes when the switch is turned off.

5. Control techniques of PMSM

Many techniques based on both motor designs and control techniques that have
been proposed in literature to diminish the torque ripples in the PMSM (Figure 9).

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Figure 9.
Classification of the various control techniques.

5.1 Scalar control

One way of controlling AC motors for variable speed applications is through the
open loop scalar control, which represents the most popular control strategy of squirrel
cage AC motors. It is presently used in applications where information about the
angular speed need not be known. It is suitable for a wide range of drives as it ensures
robustness at the cost of reduced dynamic performance. Typical applications are pump
and fan drives and low-cost drives. The main idea of this method is the variation of the
supply voltage frequency inattentively from the shaft response (position, angular
speed). The magnitude of the supply voltage is changed according to the frequency in a
constant ratio. The motor is then in the condition where the magnetic flux represents
the nominal value and the motor is neither over excited nor under excited. The major
advantage of this simple method is running in a sensorless mode because the control
algorithm does not need information about the angular speed or actual rotor position.
On the contrary, the significant disadvantages are the speed dependence on the exter-
nal load torque, mainly for PMSM, and the reduced dynamic performances.

5.2 Vector control

The vector control of PMSM allows separate closed loop control of both the flux
and torque, thereby achieving a similar control structure to that of a separately
excited DC machine, as discussed in [7].

5.2.1 Direct torque control (DTC)

The DTC is one of the high performance control strategies for the control of AC
machine. In a DTC drive applications, flux linkage and electromagnetic torque are
controlled directly and independently by the selection of optimum inverter switching
modes of operation. To acquire a faster torque output, low inverter switching fre-
quency and low harmonic losses in the model, the selection is made to restrict the flux

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linkages and electromagnetic torque errors within the respective flux and torque
hysteresis bands. The required optimal switching vectors can be selected by using the
optimum switching voltage vector look-up table. This can be obtained by simple
physical considerations involving the position of the stator-flux linkage space vector,
the available switching vectors, and the required torque flux linkage.

5.2.2 Field oriented control (FOC) of PMSM

For the control of PM motors, FOC technique is used for synchronous motor to
evaluate as a DC motor. The stator windings of the motor are fed by an inverter that
generates a variable frequency variable voltage scheme. Instead of controlling the
inverter frequency independently, the frequency and phase of the output wave are
controlled using a position sensor.
FOC was invented in the beginning of 1970s and it demonstrates that an induction
motor or synchronous motor could be controlled like a separately excited DC motor
by the orientation of the stator mmf or current vector in relation to the rotor flux to
achieve a desired objective. For the motor to behave like a DC motor, the control
needs knowledge of the position of the instantaneous rotor flux or rotor position of
permanent magnet motor. This needs a resolver or an absolute optical encoder.
Knowing the position, the three phase currents can be calculated. Its calculation using
the current matrix depends on the control desired. Some control options are constant
torque and flux weakening. These options are based in the physical limitation of the
motor and the inverter. The limit is established by the rated speed of the motor, at
which speed the constant torque operation finishes and the flux weakening starts as
shown in Figure 10 as shown in [7]. From the literature it has been found that the best
control for PMSM to make it to behave like a DC motor using decoupling control is
known as vector control or field oriented control. The torque components of flux and
currents in the motor are separated by the vector control through its stator excitation.
From the dynamic model of the PMSM, the vector control is derived.
Assuming the line currents as input signals,

ia ¼ Im sin ðωr t þ αÞ (17)

 
2π
ib ¼ Im sin ωr t þ α  (18)
3
 
2π
ic ¼ Im sin ωr t þ α þ (19)
3

Figure 10.
Steady state torque versus speed.

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Writing the above Eq. (17) to Eq. (19) in the matrix form,
0 1
cos ðωr t þ αÞ
0 1  C
ia B
B cos ω t þ α  2π C
B C B r C
@ ib A ¼ B 3 CðImÞ (20)
B  C
ic @ 2π A
cos ωr t þ α þ
3

where α is the angle between the rotor field and stator current phasor, ωr is the
electrical rotor speed.
Using the Park’s transformation, the currents obtained in the previous cycle are
transformed to the rotor reference frame axis with the rotor speed ωr. Since α is
fixed for a given load torque, the q and d axis currents are fixed in the rotor
reference frames. These constant values are made similar to the armature and field
currents in the separately excited DC machine. The q axis current is distinctly
equivalent to the armature current of the DC machine. The d axis current is field
current, but not in its entirety. It is only a partial field current; the other part is
contributed by the equivalent current source representing the permanent magnet
field. Thus, the q axis current is known as the torque producing component and the
d axis current is called the flux producing component of the stator currents.
Substituting Eq. (20) in Eq. (14) and obtaining id and iq in terms of Im as follows,
   
iq sin α
¼ Im (21)
id cos α

Using Eq. (3), Eq. (4), Eq. (10) and Eq. (21) the electromagnetic torque equa-
tion is obtained as given below,
 
3 P 1
2
Te ¼ : Ld  Lq Im sin 2α þ λf Im sin α (22)
2 2 2

where Ld and Lq are the d and q axis synchronous inductances. Each of the two
terms in the equation has a useful physical interpretation. The first “magnet” torque
term is independent of id but is directly proportional to the stator current compo-
nent iq. In contrast, the second reluctance torque term is proportional to the id and iq
current component product and to the difference of the inductance values.
As Eq. (22) shows that the torque depends on the rotor type and its inductances
Ld, Lq and on permanent magnets mounted on the rotor. The non-salient PMSM
have surface mounted magnets on the rotor and the reluctance term disappears
since Lq equals Ld. On the contrary, the electromagnetic torque is more dominated
by the reluctance component when permanent magnets are interior mounted and
the rotor’s saliency causes a difference in Lq and Ld.

5.2.3 Simulation of permanent magnet synchronous motor driven by field oriented control
using fuzzy logic control with space vector modulation for minimizing torque ripples

One of the major disadvantages of the PMSM drive is the torque ripple produced
which can be attributed to the following sources:

1. mutual torque, due to the interaction of the rotor field and stator currents;

2. reluctance torque, due to rotor saliency;

3. cogging torque, due to the existence of stator slots.

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In this section presents an application of fuzzy logic control to denigrate the

torque ripple associated with the field oriented control when used in control of a
PMSM. a SVPWM based FOC with fuzzy logic control is proposed to produce an
effective selection of the stator voltage vector to obtain smooth torque performance.
The significant advantages of space vector modulation are the ease of microproces-
sor implementation. Also, one advantage of FOC is that it increases efficiency,
letting smaller motors replace larger ones without sacrificing torque and speed.
Another advantage is that it offers higher, more dynamic performance in the case of
speed and torque controlled ac drives.
The block diagram of proposed FOC with the fuzzy logic based controller for the
PMSM drive is shown in Figure 11.
The fuzzy logic controller (FLC) executes the rule based taking the inputs and
gives the output by defuzzification. The inputs are torque error (e) and change in
torque error (ce) and the output is torque limit (T*) which is equivalent to isqref. The
dq projections of the stator currents are then compared to their reference values
isqref and isdref = 0 (to get maximum torque, set to zero if there is no field weaken-
ing) and corrected by means of PI current controllers. The outputs of the current
controller are passed through the inverse Park transform and a new stator voltage
vector is impressed to the motor using the SVPWM technique.

Figure 11.
Block diagram of PMSM driven by FOC using FLC with SVPWM.

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5.2.3.1 Space vector pulse width modulation

Space vector PWM (SVPWM) refers to a special technique of determining the

switching sequence of the upper three power transistors of a three-phase voltage
source inverter (VSI). There are eight possible combinations of on and off states for
the three upper power transistors which determine eight phase voltage configura-
tions. This PWM technique controls the motor based on the switching of space
voltage vectors, by which an approximate circular rotary magnetic field is obtained.
It approximates the reference voltage Vref by a combination of the eight switching
patterns (V0–V7). The vectors (V1–V6) divide the plane into six sectors (each sector:
60°). Vref is generated by two adjacent non-zero vectors and two zero vectors. The
switching sector is shown in Figure 12 and Table 1 shows the switching vector for
inverter.

5.2.3.2 PI controller tuning

The current loop PI controllers compare the actual current with reference cur-
rent and produce iq and id current, respectively. PI tuning is done by trial and error
method.

5.2.3.3 Fuzzy logic controller

The basic concept behind FLC is to utilize the expert knowledge and experience
of a human operator for designing a controller an application process whose input-
output relationship is given by a collection of fuzzy control rules using linguistic
variables instead of a complicated dynamic model.
The FLC initially converts the crisp error and change in error variables into
fuzzy variables and then are mapped into linguistic labels. Membership functions
are associated with each label as shown in which consists of two inputs and one
output. The inputs are Torque error and change in torque error and the output is
torque limit. Fuzzy Inference System uses “IF... THEN...” statements, and the

Figure 12.
Switching vectors and sectors.

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Vector A+ B+ C+ A- B- C- VAB VBC VCA

V0 = {000} OFF OFF OFF ON ON ON 0 0 0

V1 = {100} ON OFF OFF OFF ON ON +Vdc 0 Vdc

V2 = {110} ON ON OFF OFF OFF ON 0 +Vdc Vdc

V3 = {010} OFF ON OFF ON OFF ON Vdc +Vdc 0

V4 = {011} OFF ON ON ON OFF OFF Vdc 0 +Vdc

V5 = {001} OFF OFF ON ON ON OFF 0 Vdc +Vdc

V6 = {101} ON OFF ON OFF ON OFF +Vdc Vdc 0

V7 = {111} ON ON ON OFF OFF OFF 0 0 0

Table 1.
Switching vectors for inverter.

connectors present in the rule statement are “OR” or “AND” to make the necessary
decision rules.
The linguistic labels are divided into seven groups. They are: NB—negative big;
NM—negative medium; NS—negative small; Z—zero; PS—positive small; PM—
positive medium; PB—positive big. Each of the inputs and the output contain
membership functions with all these seven linguistics.
Figure 13 shows the speed error, Figure 14 shows the change in speed error and
Figure 15 shows the torque limit.
The mapping of the fuzzy inputs into the required output is derived with the
help of a rule base as given in Table 2.

Figure 13.
Torque error input to FLC.

Figure 14.
Change in torque error input to FLC.

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Figure 15.
Torque limit output of FLC.

e Δe NB NM NS Z PS PM PB

NB NB NB NB NM NM NS Z

NM NB NB NB NM NS Z PS

NS NB NM NS NS Z PS PM

Z NM NM NS Z PS PM PM

PS NM NS Z PS PS PM PB

PM NS Z PS PM PM PB PB

PB Z PS PM PM PB PB PB

Table 2.
Rules for FLC.

5.2.3.4 Simulation results and discussion

The simulink model of FLC with SVPWM based FOC of PMSM is shown in
Figure 16 and that of SVPWM pulse production is shown in Figure 17.
The FOC of PMSM is done using conventional PI controller and FLC using
SVPWM techniques using MATLAB version R2009a and the results are compared
with other reported results in Table 3. The parameters of PMSM used in the
simulation are given in the appendix.

Figure 16.
Simulink model of FLC with SVPWM based FOC of PMSM.

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Figure 17.
Simulink model of SVPWM pulse production.

Control strategies Torque ripple factor (%)

Proposed FLC with SVPWM 1.75

Mattavelli et al. [8] 3.8

Qian et al. [9] 3.9

Tarnik and Murgas [10] 4

Hasanien [11] 12

Table 3.
Comparison of control strategies in PMSM.

The torque ripple can be calculated by using the relation.

Peak to peak torque

Torque ripple factor ¼ (23)
Rated torque

The simulation results are shown in Figures 18–20.

From Figure 19 (Torque waveform) it is inferred that the torque ripples oscil-
lates from 7.91 Nm (minimum) to 8.05 Nm (maximum) for the given reference
torque of 8 Nm.

Figure 18.
Torque output for FOC based PMSM using FLC and SVPWM.

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Figure 19.
Torque ripples in FOC based PMSM using FLC and SVPWM.

Figure 20.
Dynamic torque using FLC with SVPWM based field controlled PMSM.

Torque ripple factor (%) as per Eq. 23 is given by = ((8.05–7.91)/8) 

100 = 0.14/8  100 = 1.75.
It is clear that variation in torque shown in Table 3 is less in case of fuzzy logic
controllers and they can achieve a minimum torque ripple than other control tech-
niques. It has been viewed that the discussed control strategy has helped in reducing
the torque ripples to 1.75%. Thus by using FLC based controller, ripples are reduced
completely.

6. Advanced topics in PMSM drives

6.1 PMSM control with rotor position sensors

The encoders, resolvers, eddy current sensors are used for rotor position sensing
of PMSM control. Absolute encoder has the advantages that it could retain the
position information in power outage conditions and for long inactive periods of
devices. It is suitable for the applications such as flow control, crane movement, and
astronomical telescopes. The position resolvers are the rotary transformers where
primary winding is placed on rotor. The induced voltage at secondary winding is
shifted by 90 would be different which is based on the rotor shaft angle [12].

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The PMSM control with speed, torque controller, where rotor angular position
sensor is used to get the feedback. The general block diagram is given in Figure 21.
The PMSM control with speed, torque controller, where rotor angular position
sensor is used to get the feedback. The general block diagram is given in Figure 22.

6.2 PMSM control without position sensors

The control scheme for sensorless PMSM where the rotor position information is
used as feedback to controllers is given in Figure 23.
The estimation of stator flux is used to find the stator current at a predicted rotor
position. The error in the predicted rotor position is corrected by finding the
difference between the estimated stator current and measured current [13].

6.2.1 Sensorless control schemes for PMSM

The difficulties in estimating the rotor position due the reasons: 1. scalar speed
estimation and 2. initial position of rotor is not known. The non-measurable vari-
ables of PMSM are estimated by the observers. For zero-speed application, salience
tracking technique is considered as appropriate, where back-Emf technique fails at
low speed. The methods generally used to estimate the rotor position are tracking
observer, tracking state filter and arctangent calculation [14].

Figure 21.
The general block diagram for PMSM control with rotor position sensor.

Figure 22.
PMSM control scheme with angular position sensor [13].

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Figure 23.
Sensorless control scheme for PMSM.

The sliding mode observer having sigmoid switching function, effectively

suppressed the oscillation of system. The cut-off frequency of LPF is tuned to rotor
speed, so that the rotor speed becomes real-time and tunable [15].
In PMSM vector control system with space vector PWM voltage source inverter
(SVPVM-VSI), the single shunt current sensing with model reference adaptive
system (MRAS) for rotor position sensorless control method is implemented [16].
To estimate the position variable of PMSM: 1. Linear Luenberger observer is
constructed 2. PI-type controller which is based on LMI is suggested [17].
To estimate the rotor position: 1. The delta-sigma modulation 2. CIC extraction filter
method are used. It is found that signal-to-noise ratio is high in this technique [18].
The neural network observer used for estimating speed/position of rotor in
PMSM, where the observer can do the tracking of the rotor speed at low speed range
with greater accuracy [19].
A linearized IPMSM model which is using FOC is created. The rotor speed and
phase current of the model is estimated by extended Kalman filter (EKF) [20].
A novel SMO is proposed to achieve greater degree of accuracy in estimating the
position and speed of PMSM. Further, the observer reduced the filter links and
phase compensation links that achieved a simplification in traditional SMO [21].
A simplified vector control model of PMSM with NNPID controller is created.
Automatic tuning of variables could be achieved by using BP NNPID. The
overswing phenomenon is eliminated to the maximum extent possible [22].
The feasibility of feedback linearization of PMSM model is shown by MIMO
nonlinear system example and then it was combined with vector control method.
For handling the nonlinear system, it is showed that feedback linearization is a
better method and has better control capability [23].
To estimate the initial position of rotor, a start-up strategy is proposed to over-
come the drawback of back emf based control at zero and low speed ranges. The NN
based controller is employed to control the current and speed of back emf based FOC
of PMSM. The dynamic response of surface mounted type PMSM is improved [24].
A model of IPMSM is developed based on intelligent control method maximum
torque per ampere (MTPA) principle in order to achieve the dynamic response
characteristics for high precision position servo systems. The shakeless fuzzy con-
troller is proposed with a new control method which is based on single neuron that
tunes the output scaling factor of the controller [25].

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Applied Electromechanical Devices and Machines for Electric Mobility Solutions

To estimate the rotor position, speed and stator resistance, an interconnected

higher order sliding mode observer (HOSMO) for IPMSM is developed [26].
The traditional backstepping control is improved by adding integral control at
each step of the tracking and regulation strategies. This permits to reject uncer-
tainties and disturbances.
The stator resistance is influenced by temperature variation that varies ran-
domly. An improved method based on variable parameter PI to compensate the
stator resistance is proposed. By constructing the stator flux observer mathematical
model of direct torque control (DTC), the problem of error existing in stator flux is
solved [27].

6.2.2 Speed-torque ripple-suppression

An ILC controller is implemented along with a PI speed controller to minimize

the periodic ripples in speed. When the learning algorithm is implemented in
frequency domain, it showed better performance in minimizing the ripples in speed
than time domain implementation. This is due to the elimination of forgetting
factor (FF), in time domain learning method [28].
A new novel method “Intelligent sensor bearing” is implemented by modifying
the feedback information that comes from sensor. An Iterative Learning Control
(ILC) is used to deal with the periodical errors for reducing ripples in speed [29].
A novel technique “Instantaneous torque control” based on fuzzy logic control-
ler (FLC) with SVPWM is proposed to reduce the torque ripples in PMSM. The
simulation results are presented in Section 5.2.3 [30].
To minimize the torque ripples of PMSM, the instantaneous field oriented
torque control schemes (a) ILC with hysteresis pulse width modulation (HPWM),
(b) ILC with SVPWM are proposed. The simulation results showed that ILC with
SVPWM has better control over torque ripples [31].
The speed torque ripple minimization of PMSM is achieved by using neural
networks (NN). The conventional PI-controller based vector control method was
compared with feed forward NN (FFNN). The simulation showed that NN con-
troller has better control than PI controller [32].

6.2.3 Application specific PMSM controls

In high speed traction applications, the motor speed range of IPMSM is extended
by single current regulator flux-weakening control strategy which results in steady
operation of motor with high speed [29].

Acknowledgements

We thankful to the management and School of Electrical and Mechanical Engi-

neering of Addiss Ababa Science and Technology University, Addiss Ababa, Ethio-
pia for their encouragement, support and facilities provided for our book chapter
work.

Nomenclature

fc crossover frequency
id d-axis current
Ldm d-axis magnetizing inductance

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Permanent-Magnet Synchronous Machine Drives
DOI: http://dx.doi.org/10.5772/intechopen.88597

Ld d-axis self-inductance
Vd d-axis voltage
ρ derivative operator
Te develop electromagnetic torque
d direct or polar axis
DTC direct torque control
ωr electrical speed
if equivalent permanent magnet field current
Ls equivalent self-inductance per phase
λd flux linkage due d axis
λq flux linkage due q axis
λdm flux linkage due to rotor magnets linking the stator
B friction
FLC fuzzy logic controller
J inertia
ki integral control gain
TL load torque
ωrated motor rated speed
Tm motor torque
P number of poles
Im peak value of supply current
λf PM flux linkage or field flux linkage
kp proportional control gain
iq q-axis current
Lqm q-axis magnetizing inductance
Lq q-axis self-inductance
Vq q-axis voltage
q quadrature or interpolar axis
Tref reference motor torque
θr rotor position
ωm rotor speed
L self-inductance
Lls stator leakage inductance
Rs stator resistance
ia, ib, ic three phase currents
Va, Vb, Vc three phase voltage

Appendix 1: parameters of PMSM

Rated power 1 HP

Rated torque 8 Nm

Rated voltage 300 V

Rated current 2.5 A

Stator resistance 0.9585 Ω

Inductance Ld 0.00525 H

Inductance Lq 0.00525 H

Magnetic flux 0.1827 weber

No. of poles 8

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Applied Electromechanical Devices and Machines for Electric Mobility Solutions

Moment of inertia 0.0006329 kg m2

Friction factor 0.0003035 Nm/(rad/s)

Appendix 2: block parameters

kp 10

ki 1

Author details

Adhavan Balashanmugham1* and Mockaisamy Maheswaran2

1 Department of Electrical and Computer Engineering, Addis Ababa Science and

Technology University, Addis Ababa, Ethiopia

2 Department of Electromechanical Engineering, Addis Ababa Science and

Technology University, Addis Ababa, Ethiopia

*Address all correspondence to: adhav14@gmail.com

© 2019 The Author(s). Licensee IntechOpen. This chapter is distributed under the terms
of the Creative Commons Attribution License (http://creativecommons.org/licenses/
by/3.0), which permits unrestricted use, distribution, and reproduction in any medium,
provided the original work is properly cited.

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Permanent-Magnet Synchronous Machine Drives
DOI: http://dx.doi.org/10.5772/intechopen.88597

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