According to the Turkish census results of the year 2002, the total number
of the people with disabilities is 1.234.139. The majority of this group
is physically disabled people with the total number of 472.629 (38.2%
of the total). Physically disabled or in other words, orthopedic disabled
people are critically important with 38% of the total (TUIK, 2002).
The wheelchair is a fundamental vehicle for orthopedic disabled and old
people to survive. With the recent technological developments, the wheelchairs,
which are driven by an electrical motor, provide comfort the disabled
person to move easily without a requirement of any extra force. The type
of electric motor used is the basic factor which determines the comfort
and distance without charging. These vehicles have the similar characteristics
with electrical cars.
In the driving motors used for electric vehicles, some important features
such as high instantaneous power, high power intensive, high torque at
low velocities, high power at high velocities, quick response for torque
demands, high efficiency at wide range of velocity and torque and low
cost are desired. The switched reluctance motor has attractive potential,
in view of its robustness, dynamic bandwidth and fault tolerance. An overall
assessment of the approach is made based on bench performance of a prototype
EMB caliper with an SR drive executing typical braking patterns. It is
shown that the SR motor can provide the required overall brake actuator
performance (Omekanda et al., 2006).
Switching Reluctance Motors (SRM) have high torque/size range. This motors
have high torque at low speed like Direct Current (DC) serial motors (Lawrenson
et al., 1980; Lawrenson and et al., 1982; Elmas and De
La Parra, 1992; Miller, 1993). Therefore, these motors have required speed-torque
characteristics for the electric vehicle driving system. These motors
have quiet simple constructions and they are really suitable for variable
speed drives due to their price, efficiency and adjustable speed, current
and torque features (Miller, 1993) shows that this motor useful for industrial
application. In recent years, they have been commonly used especially
for variable speed drives, electric cars, elevators, centrifugal pumps
and aerospace industry (Krishnan et al., 1988; Lim et al.,
These motors are more suitable than asynchronous motors for solar systems
since they are operated with DC. In addition, they do not need brush and
commutator. However they need a good control circuit in order to get high
efficiency and performance (Miller and McGilp, 1990; Bradford and Xin,
1995; Bay and Elmas, 2004; Raulin et al., 2004; Akcayol and Elmas,
2005). As a result these motors become an alternative to other motors
in much application area from home applications to space studies because
of the wide range of speed control abilities. Mininger et al. (2008)
have controlled vibration for SRM and Mir et al. (1999) have studied
about torque-ripple minimization in SRM using adaptive fuzzy control.
There are different models to description and prediction of motor losses
(Raulin et al., 2004). After these study focused on cost-optimized
switched reluctance motor drive with bipolar currents of this motor (Grbo
and Vukosavic, 2007).
In this study, to be different from other type wheelchairs, battery supported
by photovoltaic source and wheelchair has been driven a SRM instead of
classical DC motor. In order to control the speed of SRM, a control circuit,
a drive circuit and a boost converter have been designed. The simulation
and experimental results of the designed system are given.
DYNAMIC MODEL OF SWITCHING RELUCTANCE MOTOR
The electrical motor drives the wheels of the wheelchair. The power for
electrical motor is obtained from the batteries. However, the wheelchair
requires more power when claiming to hill or accelerating. These assistant
power sources are used for short-term power supply during acceleration
or uphill driving. Therefore, an auxiliary power supply is required. A
second battery or a super capacitor in addition to main battery can be
used as an auxiliary power supply source.
Figure 1 shows the half bridge driving circuit of a
SRM with 12/8 poles. When the coil A shown in Fig. 1
is energized, the induced magnetic field pulls the nearest rotor pole
towards itself. Accordingly, the reluctance is gradually minimized because
of the decreasing air gap depending on the rotor position while the inductance
approaches a maximum value.
SRM driver with boost converter: In order to feed SRM, many converter
structures has been suggested and studied in the literature. These converters
differ from each other with their way of energy recovery and strategies
used commutation from one phase to another. Figure 2
shows the block diagram of SRM control circuit while Fig.
3 shows the phase winding driven by boost converter.
Dynamic model of SRM with boost converter: Figure
4 shows schematic step up chopper circuit with SRM. The dynamic performance
of the system is by sets of differential equations. The first set governs
the system performance when the step up chopper MOSFET is off. The off
period of the boost chopper is related frequency, as follows:
where, δ is duty cycle of the chopper, f is switching frequency
of chopper and it is equal to 1/T and the last T is switching period of
Figure 5a and b show the electric circuit diagrams
of the system when the switch is at cut-off mode and at conduction mode
respectively. The dynamic performance of the system has been expressed
by two differential equations for the cutoff and conduction states of
the boost converter switch.
||Three phased SRM with 12/8 poles and half-bridge type
|| Block diagram of SRM control system
|| Designed converter for SRM
|| Circuit of SRM with boost converter
||SRM circuit and the boost converter (a) switch on and
(b) switch off
For the time duration where, 0≤ t≤ Toff the following
set of differential equations will describe the system performance,
where, Vs is the input side voltage of the step up converter,
Rc is the resistance of the chopper inductance, is
is source current, Lc is the inductance of the chopper, Ra
is the resistance of the motor phase, La is the inductance
of the motor phase, Vc is capacitor voltage which is output
side of chopper. Electromagnetic torque inducted by the motor (Te)
and vehicle torque (Tv) calculate following (Bose et al.,
where, kv is the momentum coefficient of the vehicle, ω
is the radial speed of the rotor, J is inertia coefficient, B, kf
is the total friction torque coefficient of motor and vehicle.
For the period when boost chopper is on, the MOSFET places short circuit
across the motor and separation diode Ds is separates the solar
panels and boost chopper from motor circuit at conduction state then the
boost converter is at chopping state. Motor currents freewheels thorough
the freewheeling diode Df. In this case the performance of the system during the period is described by
the following set of differential equations (Akbaba and Akbaba, 2001).
If the output voltage of the solar panel is rewritten together with the
panel variables then;
where, Rs is the inner resistance of the solar panel, Iph
is the current value of the solar panel, Io is the adverse
saturation current(0.0081), ∧ is the voltage coefficient of the solar
panel (0.0042 V-1).
Step up converter parameters: The amplitude will be zero when
the switch is ON and equal to Vo = Vc when it is
OFF, because the diode MOSFET B and Ds will be conducting when
the switch is OFF. The input voltage Vi will be equal to the
DC component of Vs, the AC component being absorbed across
the inductance Lc. Therefore:
So, the output voltage Vo is equal to capacitor voltage Vc
and it is always greater than the input voltage Vi = Vs,
since D is always less than unity. Lc is inductor of boost
converter and VL is voltage of this inductor. It is this inductor,
which receives energy from the input source when the MOSFET switch ON
and then, pumps energy into the output side, during the flyback of the
switch. Energy flows from the input side to the output side when the switch
is turned OFF. Therefore, in boost converter shown in Fig.
4, output voltage depends on only the duty rate t1/T and
input voltage Vin is independent from the load. In continuous
transfer mode, the voltage of the load is also continuous. The mathematical
symbols and input output parameters used in the simulation program are
Vin, Vc, Io and f. By using these parameters,
the value Lc is calculated by the Eq. 13:
where VF = 0.7, diode transfer voltage. By the help of the
Eq. 13 the equation of the current can be found.
where, if ΔIL< 2IL then converter runs
at continuous current mode.
If ΔIL> 2IL then the converter runs at
discontinuous mode and Eq. 14-16 are
THE FUZZY LOGIC CONTROLLER OF SWITCHING RELUCTANCE MOTOR
Figure 6 shows the block diagram of a solar wheelchair
system with SRM. The system is composed of solar panel, battery, boost
converter used for increasing the voltage level, 3 phases classical converters
for driving SRM, SRM, position sensor, 3 items of current sensor and the
PIC18F452 microcontroller (Chappell et al., 1984).
For motor feed, DC source feeds the motor power layer. For each phase
of the 3 phased power layer, 2 transistors are used. Rotor position is
sensed through counting the pulses obtained from the position sensor.
In this circuit, the position sensor produces 1024 pulses at each cycle
of the motor. The position sensors produce a reset signal after each 1024
pulses. Therefore, the exact position of the motor is detected by counting
the pulses after the reset signal and the possible lines of the pulses
are reset. The microcontroller produces the required signal according
to the position information. During producing this signal normally, each
phase begins after the end of the previous one but in order the motor
momentum to be proper the phase begins before the end of the other one
and they run together for a while then the other ends. The currents of
the phases, which are on conduction mode, are compared with the reference
signal. If the current is higher than the reference signal then, the current
of that phase is cut until its value is lower than the reference signal
(Bolognani and Zigliotto, 1996)
In SRM driver, 6 items of MOSFET Switches have been used and in Gate
drive circuits TLP250 integrated has been used as an opto-isolator.
|| Block diagram of solar wheelchair system with SRM
|| View of the completed design of the SRM driver
resistance of 330 Ω has been connected to the input of the integrated.
Two hundred volt and 30 A IRFP 250 N have been used as MOSFET. Figure
7 shows the view of SRM driver`s completed design with the boost converter.
There is one PIC microcontroller in the circuit. Pulses and reset signals
are sensed by using CAP module of the microcontroller. The speed of the
motor can be calculated by finding the time passed after each 24 pulses
with COMPARE order. Each individual output signals are transferred to
2N25 opto-isolator. These signals are applied into the gate input of the
2113 MOSFET driver together with the signals increased up to 15 V.
In the circuit, crystal with 40 MHZ attached PIC18F452 microcontroller
has been used for controlling. Sensation of two phase currents at the
same time is enough for running SRM. While SRM is rotating with the rating
speed of 1000 rpm the frequency of the position information is 17067 Hz.
The period of this signal is 28.44 ° sec. For a stable operation the
rotating speed of the controller should be shorter than this period. A
10 bit A/D conversion has been used in order to prevent missing the signals
from the position sensor of the controller and accordingly instable operation
of the motor.
The switching frequency is 10 kHz IRP250 type MOSFETs have been used
as switching component. Resistance and plastic case roundup diode with
the speed of IXYS120-60 has been used as a protection circuit. In order
to minimize the fluctuation of momentum produced in SRM, a low transitive
LC passive filter has been located on the output of switching component.
The inductance of the filter bobbin is 5 mH and the value of the capacitor
is 250 V, 470 μF. An extra diode with the same value has been added
between the bobbin and the switch in order to avoid damaging the switching
component by the reverse emf while cutting off due to the remnant energy.
In order to measure the phase currents LTA25N type current sensors of
LEM Company have been used by setting them to 2.75 V output voltage with
the current value of 2.5 A. For running SRM a incremental type position
sensor attached to the motor shaft with 1024 pulses cycle-1
option. It gives a reset signal at each cycle.
The speed control of SRM is composed of a switch for changing the transfer
time of the PWM signal, low transitive LC filter and classical converter
for controlling SRM phase currents, SRM, position sensor, current sensors
The speed of SRM was controlled by means of fuzzy logic. The block diagram
of the proposed controller was shown in Fig. 8. The
error between reference speed and actual speed was assigned to be one
of inputs of fuzzy logic controller while the change of error was second
input to controller. The error and change error signal were scaled by
1/GE and 1/GC, respectively. Accordingly, seven linguistic variables,
NB: Negative Big, NM: Negative Medium, NB: Negative Small, Zero, PB: Positive
Small, PM: Positive Medium and PB :Positive Big were created for error
and change of error variable (Chen and Zan, 2006). The membership functions
for error and change were shown in Fig. 9a and b, respectively
(De Azevedo et al., 1995; Huh and Lee, 1995; Vijayan et al.,
From the block diagram, following equations could be written:
where, e(k) is value of error at time k, ce(k) is change of error at
time (k-1), is the reference radial speed at time k, ωr
(k) is actual speed at k and e(k–1) is error at time k-1. Consequently,
the control signal which will be sent to SRM could be stated as follows:
where, u(k -1) is the previous controller output value and
GU is integral constants (Akpolat, 2005). The general flow chart of controller
was shown in Fig. 10.
|| Fuzzy logic controller system
|| Membership functions of linguistic variables
|| Flow chart of fuzzy speed controller
SIMULATION AND EXPERIMENTAL RESULTS
The designed system is composed of PV power supply, boost converter and
SRM. The parameters of SRM are 300 W, 3 phase, 12/8 poles, 2,5 A, 120
V, 1000 rpm nominal speed, β = 0.0012 coefficient of friction, J
= 0.00027 momentum of inertia. The 150 W photovoltaic voltage source was
regulated with a battery charger: 24 V, 15 A.
|| The remote controller of the disabled vehicle
||The general views of the completed disabled vehicle
The DC power supply consists
of two serial connected batteries, which have 12 V capacities. The motor
speed was controlled by adjusting motor voltage with boost converter.
The output terminal of boost converter was connected to three phases classical
converter which controls the phase currents of switched reluctance motor
and friction angle.
In the simulation and the implementation, the common transfer speed and
the transfer angle are set as 0-5° and 15°, respectively. The
speed of SRM is controlled by speed feedback and fuzzy logic method. Figure
11 and 12 show the view of the disabled vehicle.
Figure 12 shows the view of the disabled vehicle in
the field which is wholly installed, operative and working with PV.
The differential expressions in the dynamic equations are presented by
4° Runga Kutta Method and by using the programming language of C.
The obtained data is represented graphically.
|| A phase current in simulation
|| A phase current on oscilloscope
||Motor phase currents at the departure moment of the
The switching angle of the phase currents is arranged on a basis that
no negative torque will be produced. The Torque fluctuation can be prevented
by different control techniques for the charges in which sensitive and
stable torque is needed. In these methods, the torque is a little bit
Figure from 13-17 show the vehicle
on a straight and smooth road; from Fig. 18-21 show
the changes it is moving with an angle of 10°. Figure
22-25 shows its movement on a bumby road. Where, 0,1 Nm load torque
between 0-0.1 sec, 0.3 Nm load torque between 0.1-0.2 sec; 0.2 Nm load
torque between 0.2-0.3 sec, 0.5 Nm load torque between 0.3-0.35 sec; 0.2
Nm load torque between 0.35-0.5 sec.
|| Motor phase currents after the first ovement of the
|| Acceleration curves of the vehicle on smooth floor
|| The fluctuation at motor speed during stable operation
|| The fluctuation at motor torque during stable operation
|| Phase A current at the departure moment of the vehicle
on a 10° slope
|| Motor phase currents after the first movement of the
vehicle on a 10° slope
|| Acceleration curves of the vehicle on a 10° slope
|| The fluctuation at motor torque during stable operation
on a 10° slope
And finally 0.4 Nm load torque between
0.6-0.7 sec has been applied. Figure 25 shows motor
phase currents after the first movement of the vehicle on a bumpy road
and it resembles to Fig. 24.
Figure 14 shows the view of a phase current on a digital
oscilloscope. The saved current views in the simulation and the implementation
is seemed to be very similar. From here, we can say that the motor dynamic
equations and the modelling are almost real.
Figure 26 shows Speed up curves versus to time of
the vehicle on a bumpy road after the first movement of the vehicle on
a bumpy road. Figure 27 shows that the fluctuation
at motor torque during stable operation on a bumpy road. It can be seen
that Fig. 25 and 26 while the vehicle
running on bumpy rood motor torque is good adaptive to rood indirectly
speed is constant.
||Motor phase currents at the start up moment of the vehicle
on a bumpy road
|| Motor phase currents after the first movement of the
vehicle on a bumpy road
||Speed up curves versus to time of the vehicle on a bumpy
Acceleration of a disabled vehicle: In this study, ICP Accelerometer
belonging to Piezotronics Company; DAQ 6036 E Card belonging to National
Instrument Company and BNC2110 Connector and also the 8.2 version of Laboratory
Virtual Instrumentation Engineering Workbench (LabVIEW) graph program
have been used. Figure 28 shows the acceleration of
the vehicle at the speed-up moment. It can be seen from Fig.
28 that 0.6th sec vehicle started to speeding up and acceleration
is about 0.012 m sec-2. After the 1.6th second the speed changing
of vehicle is slower than by than acceleration is decreases to zero.
Figure 29 shows motor speed versus to current, Fig.
30 shows speed-voltage relation and Fig. 31 shows
the power consumed curves versus to the speed at no load.
||The fluctuation at motor torque during stable operation
on a bumpy road
||Acceleration of the vehicle at the speed-up moment
|| Line current changes versus to the speed
|| Voltage change curve versus to the speed
||Power consumed curve according to the start-up
CONCLUSION AND EVALUATION
Destination capacity and overall performance of wheelchairs for disabled people
has been increased by using a photovoltaic source and employing SRM to drive
wheelchair. Accordingly, disabled people will able to use their wheelchair for
long distance without worrying about system batteries. In addition, their traveling
comfort was increased by means of proposed intelligent speed controller and
accelerometer used. It has been shown that all these improvements could be done
by using an low cost PIC18F452 microcontroller. The main drawback of the overall
system is that its performance depends on sun light, which is uncontrollable
variable. As a result, the performance of medical equipment used for disabled
people has been improved.
Many thanks to managers and employees of Gazi University Scientific Research
Project Unit and BELMO Cooperation in Turkey for all their contribution
and support for this study with the Project code of 2006/20.