Simulation of Indirect Field Oriented Control of Induction Machine in
Hybrid Electrical Vehicle with MATLAB Simulink
Kohan Sal Lotf Abad S., Hew W. P.
Department of Electrical Engineering, Faculty of Engineering, University of Malaya, 50603, Kuala Lumpur,
Malaysia
Email: kohansal@ieee.org
Abstract
This paper applies the Pulse Width Modulation to indirect Field Oriented Control of an induction machine in parallel
Hybrid Electrical Vehicle to enhance the performance and the stability of the system.
To control the rotor speed of the induction machine, a PI controller is employed. A hysteresis current controller is
applied for controlling the output voltage of the PWM inverter which is fed the induction machine.
To justify the correctness of the system and its feasibility, the simulation method is selected. The model of the
system is implemented in MATLAB Simulink software, which is suitable for testing the dynamic simulation of a
system. By this simulation, the various working conditions of an induction machine are studied.
In conclusion, as a consequence of very quick and precise responses of induction machine to torque changes, this
paper shows that the indirect field oriented control is a good approach for controlling the induction machine in
Hybrid Electrical Vehicle. However, the simulation result in various rotor speeds shows that the machine responses
reach their steady-state condition slower than the various torque conditions. Nevertheless, this paper is the control of
the induction machine in a parallel Hybrid Electrical Vehicle which only has a torque coupling.
Key words: Hybrid Electric Vehicle, Field Oriented Control, MATLAB Simulink, Induction Machine, Bidirectional
Buck-Boost Converter.
1. Introduction
Nowadays, managing the consumption of energy is critical, especially the consumption of fossil energy, which has
limited source. Furthermore, using fossil fuel causes different disturbance in our environment such as air pollution,
noise, global warming and, etc. As a consequence to reduce the fossil fuel consumption, scientists have begun to use
different type of energy source and/or engine for replacing the ordinary Combustion Engine (CE). As a result, the
Electrical Vehicle (EV) and Hybrid Electrical Vehicle (HEV) have been produced.
Different electrical motor can be employed to operate in Electrical or Hybrid Electrical Vehicle such as various
types of DC Machine, Induction Machine (IM), and Permanent Magnet Synchronous Machine (PMSM). Compare to
IM and PMSM, the control of DC Machine is very simple and effective. However DC Machine’s maintenance cost
and price are high.
As a consequence of low maintenance cost, low price, high starting torque, simple construction, good acceleration,
and its robustness, the squirrel cage Induction Machine is a good choice to employ in EVs and HEVs [1].
In this project, the simulation and control of an induction machine with indirect vector control technique, which is
more suitable for HEVs, will be done by using MATLAB Simulink software.
2. Data and Material
There are various types of HEVs which each of them has employed different applications such as, electrical
machine, DC-DC converter, inverter and, etc.
In parallel HEVs, both CE and Electrical Motor (EM) contribute the propulsion force to the wheels of the vehicle
[2], Fig. 1. However, conventional control of IM such as the constant voltage/frequency ratio is not accurate enough
to use in HEVs, because HEVs application needs more precise torque tracking compare to other industrial drive
systems. Furthermore, this torque tracking is sensitive to change of electrical machine’s parameters.
Figure 1: The parallel HEV schematic
Therefore, in HEVs, an EM with a rapid and accurate torque tracking over different speed range is needed. Some
reasons make the squirrel cage Induction Machine (IM) a good choice for employing in HEVs, such as its low price,
low maintenance cost, high starting torque, high reliability, simple construction, good acceleration, and robustness.
2.1. The Field Oriented Control (FOC) of induction machine
The principle of FOC is to make a condition that AC motor work similar to DC motor and produces optimal torque.
In DC motor, the mmf which is produced by the armature current ia is remained at a right angle to the field flux is
produced by the stator by employing the commutator and brushes. In contrast with AC machine, both these fields in
DC machine are stationary. The electromagnetic torque Te which is developed in DC machine is related to the
armature current ia is
(1)
Where K is a constant. Therefore, if it is wanted that the torque change as a step, it is simply needed to change the
armature current by a step. So, the goal in FOC is to cause the angle between the armature mmf and the field mmf
remained 90 degree for producing optimal torque. Thus, in vector control of induction motor, the stator current
space vector is(t) is divided to two d and q rotating axis, which shown in Fig. 2. Hence, the stator phase currents are
controlled in such manner that iqs delivers the desired torque while ids maintain the rotor flux density at the rated
value.
The iqse or iT which is known as torque producing component and the idse or if which is known as flux producing
component have only dc components in steady state condition. Thus, they are ideal to be used as control variables.
Furthermore, the rotor flux linkage λr is moving at a speed equal to the synchronous speed. Therefore, the speed
error which is obtained from the difference between the reference speed ωm* and the actual rotor speed ωm, is used to
generate the reference torque T* [3]. The idse and the iqse are expressed as below:
[
]
[
][
]
Figure 2: Phasor diagram of the vector controller
(2)
Where θf is flux angle and ias, ibs, and ics are 3 phase stator currents. It will be realized from Fig. 3 that
(3)
Thus
(4)
Where λQRe and λDRe are the components of the vector of rotor flux in the excitation reference frame.
Figure 2: Orientation of the excitation reference frame along the rotor flux vector
The torque is determined by the following equation
(5)
Where iQSe is the q component of the vector of stator current in the excitation reference frame and KT is the torque
constant and is
(6)
For calculating the torque, step one is exactly same as the step one in rotor flux calculator. In step two, the iQSe is
calculated by using
[
]
[
][
]
(7)
The main strategy in both direct vector control and the indirect vector control is same. In direct vector control the
angular position (phase) of the vector of rotor flux in the stator reference frame (θr) measured directly [4], but in
indirect control, it is determined from the following equation.
∫
∫
∫
∫
(8)
Where ω* is the supply radian frequency command, ωo is the speed of 2-pole motor, θo is the angular position of the
rotor of a 2-pole motor, and ωr* is the slip speed of a 2-pole motor and it is calculated by
⁄
(9)
Where τr is the rotor time constant and is
(10)
And
(11)
In indirect vector control the angular displacement of rotor (θo) is easily measured by employing a shaft position
sensor. The schematic of an indirect vector control is shown in Fig. 4. Moreover, the iDSe* is calculated by the
following equation.
(12)
Fig 3: Vector control system for an induction motor with indirect rotor flux orientation [5]
3. Research Methodology
The main purpose of this study is controlling an induction motor by using field oriented control in a parallel HEV
application. Accordingly, in this project, the controlling of the induction machine in both motor and generator
conditions will be studied. As a result, the EM consumes the battery, or in some cases, charges the battery.
Therefore, the power electronic circuit must work in both directions too.
As mentioned before, a squirrel cage induction motor (IM) has been chosen for simulating in this project. A normal
ICE in conventional vehicles has the power around 130hp. For example, the ICE in the hybrid electrical vehicle such
as Toyota Prius has the power of 98hp with an electric motor by 80hp power output [6]. So, from the preset model
of induction machines in MATLAB Simulink, an IM number 18 with 50hp nominal power is chosen.
For choosing an appropriate FOC for controlling the IM in the HEV, some considerations must be remarked, like the
basic cost, the maintenance cost, the precision of control, the speed of control, the reliability and, etc.
Figure 4: Schematic of the designed indirect FOC of an induction machine with MATLAB Simulink
In vector control with direct rotor flux orientation, two hall sensors are employed for obtaining the rotor flux
directly. Hall sensors are too vulnerable, especially in an application like HEVs. Furthermore, these hall sensors are
placed inside the IM, so changing them becomes more complicated compare with a sensor which is placed outside
the machine. Additionally, the changing takes more time and money, and the reliability of this drive is weakened. In
contrast, in indirect vector control, the rotor flux is calculated from slip speed. And this slip speed is easily
computed by the rotor speed which is obtained by a simple speed sensor that is placed on the electrical machine
shaft. Therefore, the drive becomes simpler and more reliable with less cost. Thus, the indirect vector control for this
project is chosen. From eqns (3) and (4)
However, in normal operation condition, motors are loaded at 60% to 70% of the rating torque and rotor flux, so
As it is shown in Fig. 5 the inverter is fed by a Nickel-Metal Hydride (Ni-MH) with 201.6v output through a
bidirectional buck-boost converter (Fig. 6) which is amplified the output voltage of the battery to 654v while the EM
is working in its motoring mode. In other hand, the converter is weakened the output voltage of the rectifier from
654v to 201.6 for feeding the battery while the EM is working in its generating mode.
The dc voltage that must be applied to the inverter is calculated from the following equation by some contraction.
(13)
Therefore, the required dc voltage for feeding the inverter with that chosen induction machine is 654v. This extra
voltage is needed as a result of voltage drop during the commutation interval [8]. With the following assumption, the
parameters of the converter are estimated and are shown in Table 1.
Figure 5: The bidirectional buck-boost converter [7]
Table 1: Parameters of the Buck-Boost Converter
Parameter
Value
4. Results and Analysis
The results and the diagrams of the models that are described in chapter 3 will be studied in this section. Moreover,
the response of the designed system in various working condition will be demonstrated.
As a consequence that the converter feeds the inverter which means that feeds the whole circuit, initially, the boost
converter that its parameters have been calculated should be simulated. After simulation, the following diagrams that
are displayed in Fig. 7 are achieved. By observing Fig. 7, it is obviously observed that the diagram is reached its
steady state region after 8msec.
4.1. Adjusting the PI Controller and the Hysteresis Current Controller
The manual tuning technique has been used for tuning this PI controller. Initially, set the Kp equal to one and Ki
equal to zero. Then, Kp is increased until the output does not have change anymore. Afterwards, the Ki is changed
until the proper response has obtained or there has been no change in the response. If the response was not good
enough, the Kp will be changed again. Thus, this process will be continued until the proper response has earned.
Therefore, the Kp equal to 20 and the Ki equal to 2 has been estimated. The diagram is shown in Fig. 8.
Figure 6: Diagram of bidirectional buck-boost converter: (a) output voltage (b) input voltage
Figure 7: (Left) Output diagrams of the induction motor: (a) stator currents (b) rotor speed (c) Electromagnetic
torque, (Right) The zoom in on the output diagrams of the induction motor: (a) stator currents (b) rotor speed (c)
Electromagnetic torque
Thus, the speed is controlled; however, the torque is remained uncontrolled. According to Fig. 8 (Right), it is seen
that the stator currents have too many ripples. Moreover, from equation (11) it is known that the torque is directly
related with the stator current. Therefore, it is possible to control the torque by controlling the stator current. For this
reason, the hysteresis current controller is employed. After the hysteresis current controller set to 1 and applied to
the system, the diagram that is illustrated in Fig. 9 is achieved.
Figure 8: (Left) Output diagrams of the induction motor: (a) stator currents (b) rotor speed (c) Electromagnetic
torque, (Right) The zoom in on the output diagrams of the induction motor: (a) stator currents (b) rotor speed (c)
Electromagnetic torque
4.2. Studying the System in Various Conditions
There are two different mechanical coupling between the ICE and the electrical machine in HEVs, speed coupling
and torque coupling. However, in parallel HEV that is chosen for this project, the ICE and the EM have the torque
coupling. In the first step, the induction machine is run with different speed in a constant torque. The speed that is
applied to the IM is 5, 500, 1000, and 1480rpm in time 0, 1, 2, and 3sec respectively, where torque is fixed at zero.
The stator currents, the rotor speed, and the electromagnetic torque are shown in Fig. 10.
In next step, the rotor speed is fixed to its nominal speed (1480rpm) and the torque will be changed every second
with this sequence, 0, 100, -100, and -200N.m. Moreover, when the torque is becoming negative and IM is entered
the generating region, the electric power flow direction is inverted. The stator currents, the rotor speed, and the
electromagnetic torque are shown in Fig. 11.
Figure 9: Output diagrams of the induction motor in various rotor speeds: (a) stator currents (b) rotor speed (c)
Electromagnetic torque
Figure 10: Output diagrams of the induction motor in various load torque: (a) stator currents (b) rotor speed (c)
Electromagnetic torque
5. Conclusions
Initially, this project shows that the indirect field oriented control is a good approach for controlling the induction
machine. As a result, the induction machine responses to torque changes very quickly and precisely. However, the
simulation result in various rotor speeds shows that the torque response is not fair enough. In every step of changing
the rotor speed, it takes 0.2sec that torque reaches it the steady state condition.
However, this project is the control of the IM in a parallel HEV which only has a torque coupling. Therefore, the
speed should be remained constant in different torque, which is achieved and shown in Fig. 11.
Furthermore, a PWM inverter has been used in this project, which gives a good result. However, it is better that the
SVPWM inverter be employed in an application like HEVs. Because the control of electrical motor is more precise
in SVPWM inverter compare to PWM inverter. Accordingly, with a more accurate control, instruments are
tolerating less shock during their transient states, so the maintenance cost drops considerably. But for SVPWM
inverter, three PI controllers needed, which make its adjusting more complicated compare to a simple PWM inverter
that has only one PI controller.
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