13

CHAPTER 2

STATE OF THE ART

2.1 INTRODUCTION

The literature on electrical drives, BLDC motor, feedback methods

with and without sensors, the conventional braking methods, the available

PWM techniques that can be adapted for the proposed work are reviewed in

this chapter. The switch selections for the inverter circuit, the control strategy

that can be implemented, selection of appropriate controller for the proposed

research work has also been discussed.

2.2 ELECTRIC DRIVE

The modern electric drives and their future trends were reviewed by

De Doncker (2006).The growing importance of drive technology and the

improvements in the market share have been clearly brought out.

Liaquat Ali Khan et al (2008) discussed the integrity of the system

based on keeping the wheel speed constant. In nullifying the steady state

error, the Proportional Integral (PI) control algorithm was used with root

locus design method to find the PI coefficients. If the system approximate

linear transfer function is developed as per the authors, then coefficients of

Proportional Integral Derivative (PID) can be determined using root locus

technique.

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Xue et al (2008) studied six kinds of the drive train systems of

electric motor drives for electric vehicles. The comparative investigation on

the efficiency, weight, cost, cooling, maximum speed, fault-tolerance, safety,

and reliability were carried out for switched reluctance motor, induction

motor, Permanent Magnet BLDC (PMBLDC) motor, and brushed DC motor

drives.

Narasimham et al (2010) proposed a novel topology for a low cost

converter which drives a spindle motor at high speed with high starting torque

using the bipolar starting and unipolar running algorithm. The topology

presented was simple and used only eight switches in the converter to drive

the spindle motor. The proposed topology was best suited for low power

drives.

2.3 BLDC MOTOR

Lee and Ehsani (2001) proposed an advanced BLDC motor drive

for electric propulsion system. Power converter topologies and a PWM

control strategy were used to produce the desired dynamic and static speed-

torque characteristics. Insulated Gate Bipolar Transistor (IGBT) inverters

with high speed DSP, TI TMS320F243 were designed. The sensorless control

strategies were directly combined into several low cost converter topologies.

Padmaraja Yedamale (2003) in the application note has discussed

in detail the construction, working principle, characteristics and typical

applications of BLDC motors.

Kumar et al (2005) presented the modelling and DSP based

implementation of closed loop control of Permanent Magnet Brushless DC

(PMBLDC) motor with a single current sensor. DC link and two conducting

15

phases form a series circuit. Current control in these phases were achieved by

controlling DC link current.

An innovative four-quadrant Switched Reluctance Motor (SRM)

drive with only one controllable switch was realized by Krishnan et al (2005).

The motor drive having a two-phase machine with a single controllable

switch converter was used. The motor drive was modelled, simulated and

analysed to verify its feasibility for self-starting, speed control and for four-

quadrant operation.

Nisai et al (2005) presented a four-quadrant SRM drive for high

dynamic applications. The drive was designed based on a control strategy

called Direct Instantaneous Torque Control (DITC). A methodology to

generate switching functions directly by the hysteresis torque controllers for

SRMs was also proposed. The proposed controller was prototyped and tested

on a DSP / Field-Programmable Gate Array (FPGA) development platform.

Jiaxin Chen et al (2007) developed a PMBLDC motor for driving

high-speed embroidery machines. In the design of the motor, magnetic field

finite-element analysis the motor parameters such as the air-gap flux, back

EMF, and inductance were calculated. Using the numerical magnetic field

solutions and a modified incremental energy method, the self and mutual

inductances of the stator windings were calculated.

Maity et al (2007) developed a software program for a DC motor to

control all the four quadrants through a Personal Computer (PC) in an

interactive mode. The signals generated were suitable for the triggering

operation of four power electronic switches of the chopper. A user friendly

control room method has been adopted.

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Afjei et al (2007) briefly presented a configuration for BLDC

motor/generator, which did not use a permanent magnet in the rotor. The

proposed machine consists of two magnetically dependent stator and rotor

sets (layers), where each stator set included nine salient poles with windings

wrapped around them while, the rotor comprised of six salient poles. A power

electronic converter which provided bidirectional control of the current for

each motor phase independently was presented. This control scheme

permitted the motor to operate with any number of phases at any time.

Namhun Kim et al (2007) presented a BLDC motor control

algorithm for motor drive applications using general purpose microcontrollers

with one on-chip timer. PWM signals with general input/output (I/O) ports to

control a three-phase permanent magnet BLDC motor using the timer

interrupt on MSP430F1232 was realised. An algorithm that employs the I/O

port for PWM signal generation for BLDC motor control with three Hall

sensors was proposed.

Qingbo Hu Zhengyu Lu and Zhaoming Qian (2007) introduced a

drive mode of BLDC motor that adopts a cascade bidirectional DC-DC with

full-bridge circuit, and motor EMF. Closed-loop was formed by voltage

feedback and current positive feedback compensation to control the speed. To

overcome capacitor voltage ripples during motor commutation process, a

method based on inductor current predictive control was proposed. It controls

the duty cycle and makes inductor current to follow motor phase current

during commutation process.

Qiang Han et al (2008) investigated average-value modelling of

BLDC motor with 120º inverter systems. It demonstrated that neglecting the

commutation interval may lead to degradation of model accuracy, especially

with BLDC motors that have low stator resistance (high electrical time

constant) and operate with a large commutation angle. A new Average Value

17

Modelling (AVM) that appropriately includes both commutation and

conduction subintervals has been presented here. A nonlinear algebraic

function that represents the commutation angle has been obtained

numerically. The proposed model was shown in both the time and frequency

domains and was applicable to motors with large and small electrical time

constants.

A Phase Locked Loop (PLL) assisted Internal Model (IM)

adjustable-speed controller for BLDC motors was detailed by Ching-Tsai Pan

and Emily Fang (2008). With proper integration of the motor current sensing

scheme with PWM control, the hardware implementation of the BLDC motor

drive was made compact and enabled further integration into chips to reduce

the cost and enhance the current regulation performance. The poor transient

response and limited lock-in range was the drawback of PLL control. The

proposed PLL assisted IM controller combined the merits of the previous two

controls. Only three parameters, i.e., KP, KI, and K, are to be determined.

Stability analysis revealed that the first order filter must properly be designed

to achieve the stability condition. Quite-uniform equivalent-armature current

waveforms, which greatly reduced the mechanical vibration noise, were

obtained. The proposed control provides unified smooth control under both

transient and steady-state conditions.

A torque control method was proposed by Haifeng Lu et al (2008)

to attenuate torque ripple of BLDC motors with un-ideal back EMF

waveforms. The action time of pulses, which was used to control the

corresponding switches, was calculated in the torque controller. The influence

of finite DC bus supply voltage was considered in the commutation period.

An instantaneous torque control scheme for four-quadrant

operation of SRM at low speed based on co-energy considerations was

proposed by Wong et al (2009). The co-energy is estimated using online co-

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energy estimator, which requires easily obtainable parameters such as the

machine terminal quantities and the machine characteristics at low current. By

regulating the co-energy while tracking a one-dimensional co-energy profile,

the torque contribution of each phase of the SRM was controlled and

optimised. The requirement of pre-measured data was reduced when

compared to current profiling methods. The excitation sequence and torque

sharing function for four-quadrant operation to produce smooth torque output

were also presented.

Iordanis Kioskeridis and Christos Mademlis (2009) described a

method to unify the optimal control of a switched reluctance machine in a

four-quadrant drive. A smooth transition between the PWM/single-pulse

modes and motoring/braking operations was attained, since the firing angle

conditions of one operating mode were derived from the conditions of the

other operating mode. Knowledge of the machine magnetization curves was

not required to implement this method.

A new low-cost Integrated Circuit Chip for the control of BLDC

motors was developed by Anand Sathyan et al (2009). A digital PWM control

has been implemented for a trapezoidal BLDC motor drive system. The

digital controller can be implemented in Application Specific Integrated

Circuit (ASIC). The controller is modelled and verified using simulations.

BLDC motor drive is treated as a digital system. It is only allowed to operate

at low duty (DL) or high duty (DH). Speed regulation is achieved by

alternating between low duty and high duty.

PMBLDC motors have high efficiency, silent operation, compact

size, high reliability and low maintenance requirements. The operation of

PMBLDC motors requires rotor-position sensing for controlling the winding

currents. These motors were preferred for many applications; however, most

of them require sensorless control. The sensorless control requires estimation

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of rotor position from the voltage and current signals, which were easily

sensed. Bhim Singh and Sanjeev Singh (2009) presented the state of the art

PMBLDC motor drives with an emphasis on sensorless control of these

motors.

Madhusudhana Rao et al (2010) proposed the speed control of

BLDC motor drive employing PWM technique using TMS320F240 DSP. The

Hall signals, phase current sensing signal and the speed command were the

input to the DSP. Both the outer velocity control loop and inner current

control loop used PI controller that has been implemented by programming in

TMS320F240 DSP. The drive performance was studied for starting, speed

reversal and load perturbation. An algorithm was developed to simulate the

drive model with PI speed controller. The fourth order Runge-Kutta

numerical integration method was used to get the solution of first order

differential equations of the model.

A new type quasi-buck topology of converters was proposed by

Zhang Jiasheng and Pan Dawei (2010) whose DC side voltage is reduced by

approaching 50%, thus appropriate for lower voltage applications. The

modelling with the state space averaging method, and steady state theoretical

analyses of the converter were presented.

Jinqi Li et al (2010) proposed a Flywheel Energy Storage System

(FESS) for BLDC motor. A buck circuit was presented to reduce motor

torque ripple in charge section, using constant torque control at low speed and

constant power control at high speed. The constant torque control and

constant power control strategies were first introduced into PAM control,

which is effective to reduce phase current ripple, as a result of reduced torque

ripple.

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Chun-Lung Chiu et al (2010) detailed a method to improve

efficiency and torque performance of the single-phase BLDC motor by

finding out the optimum commutation angle at each different speed. The finite

element method was used to simulate the back-EMF voltage and the coil

current for the single-phase BLDC motor, and then the conduction time of

switches were adjusted by detecting the waveform of coil current. The motor

can improve its efficiency, noise, and vibration when it obtains the optimal

shift angle of each speed. The special design point used in this paper was to

only observe the smooth degree of the motor current that can be used to find

out the optimal shift angle.

Varatharaju et al (2010) described the procedure of obtaining a

model for the BLDC motor with 120º inverter system and validated using the

MATLAB/Simulink platform. The discussion arrived at a closed-loop speed

control, in which PI algorithm was adopted and the position-pulse

determination was done through current control for a standard trapezoidal

BLDC motors.

Rakesh Saxena et al (2010) proposed a soft computing technique

PSIM which can be used for the performance simulation of the BLDC motor.

With the help of its user friendly approach, the corresponding PSIM models

for the BLDC can easily be constructed. PSIM software was designed to

provide a debugging, diagnostic and demonstration tool for the development

of algorithms and applications in electric drives.

Shinn-Ming Sue et al (2010) presented a bi-directional power flow

Interior Permanent Magnet BLDC (IPMBLDC) motor drive for electrical

scooters. A control scheme was proposed for the motoring operation. It had

high energy conversion efficiency in the low speed and high torque region as

well as high speed region. The basic control idea followed the Maximum

Torque Per Ampere (MTPA) control of an Interior Permanent Magnet

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Synchronous Motor (IPMSM). For the regenerative braking operation, a new

switching pattern was presented. It provided a symmetry line current

waveform for smooth regenerative braking. A DSP was used to implement the

control core to reduce the development cost.

Wael Salah et al (2011) discussed about the BLDC motor control

based on rotor position sensing scheme. A PIC microcontroller was used to

generate PWM signals for driving the power inverter bridge. Hardware

implementation and simulation results show the effectiveness of the

developed motor drive. The flexibility offered by the developed motor control

and drive enables the implementation of different control algorithms for

improving the output characteristics of the BLDC motor.

Viswanathan and Jeevanathan (2011) proposed a current controlled

SVPWM technique for BLDC motor drives, with a view to reduce torque

ripple. The current ripple, created due to the stator winding inductance, leads

to generation of ripple in the torque and prevents the usage of BLDC motor in

a precise servo drive system.

Chia-Chang Tong et al (2011) designed and built a dual-axis drive

system for an electric bicycle. The computerized control utilized a firmware-

based system, with the vehicle’s Electronic Control Unit (ECU) and most of

the signal processing circuits implemented using a Programmable SoC

(PSoC). Both wheels drive the vehicle simultaneously, the speed controller

was designed in such a way that it had the ability to compensate for speed

difference that might exist between the front and rear wheels. Both wheels

had breaks and kinetic energy recovery for decelerating or downhill riding.

The vehicle had automatic cruise capabilities and can automatically switch to

single front or rear wheel drive at medium or high speeds.

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Robert et al (2011) presented concepts for extensive diagnosis

implementation for different fault conditions that may appear in the BLDC

motor or its control electronics. The detectable failure conditions by the

methods described were short circuit conditions at the motor, internal,

external power supply voltages and over-temperature failure conditions,

position Hall signals failure conditions. The implementation was done using

hardware circuits which were easily integrated in the BLDC motor control

ASIC.

Feyzi et al (2011) proposed a single current strategy for high

performance BLDC motor drives. It was based on estimation and regulation

of phase currents, using two single sensors for DC link voltage and current.

The phase currents were reconstructed in a two-stage process including

estimation and regulation. Estimation is based on dynamic motor model,

while regulation relied on the inverter switches' states and the measured DC

link current. Besides, to access better dynamic response characteristic of the

motor speed, Particle Swarm Optimization (PSO) was used to regulate the

PID parameters of speed controller.

Axial flux BLDC motors, in general, and ironless axial flux BLDC

motors, in particular, come with very low inductance owing to this; they need

special care to limit the magnitude of ripple current in motor winding. In most

of the electric aircraft applications, BLDC motor needs to be driven from 300

or 600 VDC bus. In such cases, particularly for operation from 600 VDC bus,

IGBT based inverters are used for BLDC motor drive. They have limitation

on increasing the switching frequency, and hence they are not very suitable

for driving BLDC motors with low winding inductance. A three-level neutral

point clamped inverter was proposed by De et al (2012) to drive axial flux

BLDC motors.

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2.4 WITH SENSORS AND WITHOUT SENSORS

Ralph Kennel (2007) reviewed the speed and motion sensing as

well as different encoder technologies available today and their

characteristics, particularly with respect to digitally controlled servo drives.

The author has provided some insight of the impact an encoder has on the

control behaviour of a servo drive, particularly under slow motion operation.

Variable-sampling systems described a class of systems whose

sensor output are available only at some situations not specified by the

sampling mechanism. In BLDC motor drives with low resolution position

sensors, the position measurements were not available at the fixed-sampling

instance. Chung-Wen Hung et al (2007) proposed a variable-sampling

Variable Structure Controller (VSC) for BLDC motor drives. A modification

of the conventional discrete-time VSC control law for BLDC motor drives

with Hall sensors was derived to achieve the robustness of speed control.

Three measurement error-mitigation methods were also presented to reduce

the errors due to low-resolution position feedback.

Cheng-Tsung Lin et al (2008) proposed a position sensorless

control scheme for Four-switch Three-Phase (FSTP) BLDC motor drives

using a FPGA. A sensorless control with six commutation modes were

developed to drive FSTP BLDC motors. The low cost BLDC driver was

achieved by the reduction of switch device count, cost down of control, and

saving of Hall sensors.

Subrata et al (2009) proposed a DC chopper, driven by a PWM

signal that can be utilized for position control of a PMDC motor. Controlling

the duty cycle of the PWM signals has been implemented by microcontroller

as equivalent to controlling the motor terminal voltage, which in turn adjusts

directly the motor rotational movement.

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Prasit Champa et al (2009) presented a method for determining the

initial rotor position of a BLDC machine at standstill without a position

sensor. The key principle of the rotor position estimation was based on the

simple detection and comparison of phase voltage and current responses

relating to the stator inductance varied with the position of the rotor magnet.

In the proposed method, only three voltage-pulse injections were applied, and

a 30 resolution was achieved.

Abolfazl Halvaei Niasar et al (2009) proposed a position sensorless

control scheme for a four-switch, three-phase brushless DC motor drive,

based on the zero crossing point detection of phase back-EMF voltages using

defined error functions (EFs). The commutation instants are 30° after detected

zero crossing points of the EFs. Developed EFs have greater magnitude rather

than phase or line voltages so that the sensorless control can work at a lower

speed range. Moreover, EFs have smooth transitions around zero voltage level

that reduces the commutation errors. EFs are derived from the filtered

terminal voltages vao and vbo of two low-pass filters, which were used to

eliminate high frequency noises for calculation of the average terminal

voltages.

Changliang Xia et al (2009) proposed a control strategy based on

single current sensor for a four-switch three-phase BLDC motor system. To

improve control performance, a single-neuron adaptive PI algorithm was

adopted to realize the speed regulator. The proposed strategy showed good

self-adapted track ability with low current ripple and strong robustness to the

given speed reference model. In the proposed system, commutation torque

ripples are more severe, unless a suitable current control strategy was

adopted. Also, reducing the quantity of current sensor brings maximum

current limitation in certain modes. A special algorithm is necessary as

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compensation on the reduction of current sensor. Consequently, the software

overhead was increased.

A sensorless control algorithm based on a differential back EMF

measurement for BLDC motors, which allows higher dynamic performance

and lower operating speed was proposed by Carlo Concari and Fabrizio Troni

(2010). Flash A/D converters in motion control oriented DSPs were utilized.

Current sensing was not necessary for phase commutation, and a current

control loop can be implemented if required using a single current sensor on

the DC bus. It is rather insensitive of voltage measurement offsets and current

ripple, hence reliable sensorless operation was ensured even at low speed.

Chung-Wen Hung (2010) described a sensorless method for six–

space-vector four Switch three phase BLDC motor. Due to the nature of low

resolution of position sensing, the speed feedback was variable sampling. A

fuzzy gain scheduling PI controller was proposed which was based on three

selected PI controllers in fixed sampling time intervals, high, median and low

speed and was combined by simplified fuzzy logic.

José Carlos Gamazo-Real et al (2010) provided a technical review

of position and speed sensorless methods for controlling BLDC motor drives.

The study included a deep overview of state-of-the-art back EMF sensing

methods, which included terminal voltage sensing, third harmonic voltage

integration, terminal current sensing, back EMF integration and PWM

strategies. Also, the most relevant techniques based on estimation and models

were briefly analysed, such as sliding-mode observer, extended Kalman filter,

model reference adaptive system, adaptive observers and artificial neural

networks.

The application note by Eduardo Viramontes (2010), demonstrated

a BLDC motor control application using Hall sensors as a feedback

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mechanism to measure speed and position of the motor rotor. The advantage

of using Hall sensors in BLDC motor control is that the feedback mechanism

requires minimal Central Processing Unit (CPU) resources as opposed to

sensorless approaches, where more software and hardware resources are used

for the detection of proper commutation and speed. Hall sensors also offer an

advantage of control at a near zero rpm speed range. Sensorless approaches

need the motor to start moving (by moving it without any feedback) to be able

to detect back EMF. Hall sensors always indicate the position of the motor to

easily start running it in a closed loop from zero rpm. An added advantage of

using Hall sensors is that the maximum speed attainable is higher than with a

sensorless approach. Sensorless approaches depend greatly on the Analog to

Digital Converter (ADC) comparator sampling frequency, which is always

slower than the Micro Controller Unit (MCU) capacity to detect changes in

general purpose I/O pins. There is also the matter of calculating when the next

commutation should take place, which also drains CPU resources in addition

to the already lengthy matter of calculating the control output; this also affects

the maximum attainable speed. The application note concluded that using the

Hall sensors to obtain the speed of the BLDC motor will be more

advantageous than going for a sensorless approach.

An approach of filtering the Hall sensor signals has been proposed

by Pooya Alaeinovin and Juri Jatskevich (2011). Digital implementation of

several averaging and extrapolating filters that can be easily included into

various BLDC motor drive systems was presented.

Mohsen Ebadpour et al (2011) developed position sensorless

control strategy for four-switch three-phase BLDC motor drives using single

current sensor. The working of the BLDC motor was divided into six modes.

Phase c involves four modes, including modes 2, 3, 5, and 6. Only one switch

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works in these modes. In modes 1 and 4, two switches will work

simultaneously and current flows through phases a and b. The proposed

position sensorless scheme was based on the detection of zero crossing points

of three voltage function that were derived from the difference of line

voltages measured at the terminals of the motor.

Chen Yongjun et al (2011) in the application note described a

sensorless BLDC motor control algorithm that was implemented using DSC

dsPIC30F2010. The algorithm worked utilizing a majority function for

digitally filtering the back EMF. Each phase of the motor was filtered to

determine when to commutate the motor drive voltages. This control

technique excluded the need for discrete, low-pass filtering hardware and off-

chip comparators.

Qiang Wu et al (2011) analysed the SVPWM control schema of

three-phase inverter employing 120° switch-on mode and proposed a starting

control method that combined the SVPWM control schema with current

regulation. The authors adopted the two-point comparator for a sensorless

three-phase PMBLDC motor and developed the simulation model of the

starting control system in MATLAB / Simulink environment. The proposed

starting control system was implemented through digital simulation.

Tzuen-Lih Chern et al (2011) have proposed position sensorless

BLDC motor driver. The three-phase BLDC fan motors were utilized for

cooling the computer products. The proposed sensorless speed control scheme

was compared with the open loop external PWM and closed loop without

external PWM control. Furthermore, the current feedback was employed to

improve the system performance.

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2.5 BRAKING METHODS

A Four Quadrant (4Q) soft-switching converter for DC motor

drives, namely the 4Q Zero Current transition (4QZCT) was proposed by

Ching (2006). In this converter both the turn-on and turn-off losses of main

switches were reduced, while the auxiliary switches can always operate with

zero current switching. It possesses the advantages of reduced switching

stresses, minimum voltage and current stresses as well as minimum

circulating energy during both the motoring and regenerating modes. The

same resonant tank was used for both forward and backward power flows.

The modelling of BLDC motor was realised using abc phase

variable model by Vinatha et al (2008).The PWM gating signals for firing the

power semiconductor devices in the inverter was injected from a hysteresis

current controller, which was required to maintain the current constant within

the 60 interval of one electrical revolution of the rotor. The hysteresis

controller limits the phase currents within the hysteresis band by switching

ON/OFF the power devices. The model equations were solved by Runge-

Kutta numerical technique and simulated using MATLAB/SIMULINK.

Li Yu-shan et al (2009) proposed a control strategy in which power

was supplied by regenerative braking, when lower braking intensity was

required and proportional combination of regenerative braking and frictional

braking deduced by fuzzy logic control strategy when higher braking intensity

is required. Front wheel with rear wheel frictional braking and unchanged

motor torque were combined by ideal braking force distribution when braking

intensity up to motor's maximum torque.

Phaneendara Babu Bobba and Rajagopal (2010) proposed a

regenerative method of braking of an electric vehicle which helps in

utilization of the battery power to increase the range of the vehicle. A method

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to control the power flow from the motor to the battery by changing the

switching sequence given to the inverter used in the PM BLDC motor drive

was presented. This method gave lower braking time and higher regeneration,

and also does not necessitate any additional converters or ultra-capacitors.

A flywheel and ultra-capacitor with DC-DC converter was

employed to enhance the regenerative performance by Yoong et al (2010).The

working principle and braking controller for the regenerative braking was

studied to promote the efficiency and realization of energy saving in the

electric vehicle.

Juzhong Zhang et al (2010) proposed a BLDC motor with

regenerative braking for wheeled mobile robot. The drive servo system was

converted into a parallel-connected boost circuit to brake and store power

without changing any hardware device, and the chopping frequency of the

stator phase current was twice as high as the traditional methods with same

switch frequency, so the swing range of stator phase current was reduced.

Angel Marinov and Vencislav Valchev (2010) suggested

topologies, namely MOSFET-IGBT combination, SCR-MOSFET

combination for the four quadrant drive of a PMBLDC motor. Comparisons

were presented with respect to losses, efficiency and cost. The suggested

combinations can be used in applications such as grid injecting inverters and

BLDC motor control.

Wei Cui et al (2011) proposed an optimal regenerative braking

control scheme for a PMBLDC motor of an electric motorcycle to achieve

dual goals of the electric brake and the maximal power harvest in two cases of

the road, downhill and flat, without any additional changes on the hardware.

Based on regenerative braking of BLDC motor in half bridge modulation

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mode, the relationship between average regenerative current on the DC bus

and PWM duty cycle under different speeds were studied.

Chih-Chiang Hua and Shih-Jyun Kao (2011) proposed a

regenerative braking system for electric bicycle based on DSP. The proposed

method was used to adjust the switching sequence of the inverter, so that the

braking energy will be returned to charge the battery.

Aravindan (2011) investigated the operation of the separately

excited DC machine in each of the four quadrants, when fed by the

symmetrical multi-pulse modulated, improved power quality, single-phase,

dual buck converter. The armature control of the DC machine with constant

load torque was undertaken in both clockwise and anticlockwise directions in

the motoring and generating modes. The proposed drive fed by the improved

power quality dual converter can be manipulated to enable use of more

economic filters compared to those in the phase controlled one. The

Symmetrical Multi - pulse Modulation (SMM) involves chopping of the

sinusoidal source voltage by several equidistant pulses per half cycle (M). The

THD of the Alternating Current (AC) side current generally decreases with

increase in M for a specific duty cycle for a particular per unit (p.u.) value of

the voltage.

2.6 PWM TECHNIQUES

A microcomputer based prototype for drive and control of electrical

machines using PWM was considered by Da Costa et al (2003). The system

makes the real time implementation of PWM and control techniques, possible

through the use of user friendly supervisory software. Simulation results of

several PWM techniques were discussed. Experimental results were obtained

using the proposed scheme with a robust model reference adaptive controller

to control an induction motor position servo mechanism.

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Yen-Shin Lai et al (2004) proposed a PWM technique for BLDC

motor drives fed by MOSFET inverters, which significantly reduced the

conduction losses, and thereby dramatically reduced the heat dissipation.

Tahri and Draou (2005) investigated several control techniques

applied to the multilevel cascaded inverter in order to ensure an efficient

voltage utilization and better harmonic spectrum. A modelling and control

strategy of a single phase multilevel cascaded inverter was also investigated.

Experimental results were carried out on a scaled down prototype to prove the

effectiveness of the proposed analysis. They have investigated the

performance of various techniques in terms of output voltage spectrum. It is

possible to obtain a satisfactory spectral performance with relatively low

switching frequency. The investigations and experiments have concluded that

the programmed PWM is suitable for applications that need high dynamic

performance in high power applications.

Chelladurai et al (2008) analysed the comparative merits of

Sinusoidal Pulse Width Modulation (SPWM) and Space Vector Pulse Width

Modulation (SVPWM) techniques and the suitability of these techniques in a

Shunt Active Filter (SAF). The objective was to select the scheme that offered

effective utilization of DC bus voltage and also harmonic reduction at the

input side. The effectiveness of the PWM techniques was tested in the SAF

configuration with a nonlinear load. The performance of the SVPWM

techniques was compared with respect to the THD in source current. The

study revealed that in the context of closed loop SAF control with the

SVPWM technique there was only a minor improvement in THD. The

utilization of the DC bus with SVPWM was also not significant compared to

that with SPWM because of the non-sinusoidal modulating signal from the

controller in SAF configuration.

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Wei-Chao Chen and Ying Yu Tzou (2009) proposed a modelling

method for characterization of single-phase BLDC fan motors. The nonlinear

back EMF induced by the rotor flux with stator winding was modelled by a

look-up table. By parameter identification and computer simulation, this

modelling method assists designers in waveform analysis and control loop

design. In order to improve the efficiency of the BLDC fan motor over the

entire speed control range, an efficiency optimization control method based

on a closed-loop current control scheme by using the Hall sensor feedback

was developed. The proposed control scheme has been realized and compared

with the conventional open-loop PWM control scheme.

A PWM control does not have an inherent current control

capability, a current limiter has to be introduced. A controller without any

state observer was explained by Anand Sathyan et al (2009). A proportional

controller provides the reference for the current limit. The current was made

to stay within a maximum and minimum limit. A Spartan 3 family from

Xilinx was used to control the BLDC machine. Reference speed value was set

digitally, and a speed loop was used to compare the actual speed and the

reference speed, based on the error duty cycle for the next period was

determined. The actual speed was easily calculated as a time between two

Hall effect signals.

Pongpit Wipasuramonton and Kowit Sowsuwan (2009) presented a

current controlled PWM technique for BLDC drives with only a single

current sensor, particularly a low-cost shunt resistor. The PWM technique

offered a unipolar modulation which does not produce current in the floating

phase. Therefore the winding currents were sensed directly with the shunt

resistor. The current was controlled with a predictive current control

algorithm, which gave fast response and was executed in every period of the

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PWM interrupt. In addition, the unipolar PWM modulation has low switching

and winding losses.

An ECU for BLDC motors in an electric bicycle was proposed by

Devaneyan (2010). A dynamic model was used to simulate the system

behaviour in a number of different situations. A closed loop control circuit

allows the optimization of the component operation, determining in particular

a proper value of the motor torque with respect to the load and of the

absorbed current. This reduced undesired accelerations. This is also a suitable

regenerative braking system using the super capacitor technology.

A new module structure of PLL speed controller was proposed by

Ting-Yu Chang (2010) for PMBLDC motor drives to achieve both fast

response and high accuracy. The proposed standard module renders the

controller design rather simple and straight forward. In order to reduce the

drive cost, a phase current sensing scheme was adopted to properly integrate

with the PWM control of the PLL controller.

Chuang (2010) presented a comprehensive analysis on the

generated torque ripples of trapezoidal back EMF due to phase commutation

in the six-switch, three-phase inverter BLDC motor drives. The amplitude of

the torque ripples under four kinds of PWM patterns were presented based on

experimental results.

Alphonsa Roslin Paul and Mary George (2011) presented a digital

PWM control technique for trapezoidal BLDC motor drives. This digital

control treats BLDC motor as a digital system and regulates speed with the

help of two predefined state variable techniques.

Wael Salah et al (2011) proposed a PWM switching strategy to

minimize the torque ripples in BLDC motor which was based on sensored

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rotor position control. The scheme was implemented using a PIC

microcontroller to generate a modified PWM signals for driving power

inverter bridge. The modified PWM signals were applied to the next up-

coming phase current such that its current rise was slightly delayed during the

commutation instant. The current waveforms of the modified PWM were

smoother than that in conventional PWM technique.

Nikola Milivojevic et al (2012) discussed digital PWM control for a

BLDC drive in both motoring and generating modes of operation. The

technique can be implemented on FPGA. The potential stability issues due to

the simplicity of this control under various conditions of load disturbances

and also owing to the reduction in processor capability was investigated.

Lyapunov stability criteria have been used to analyse the closed-loop stability

of the system. An approximate discrete model was developed, and the

stability of the system was analysed to ensure closed loop operation under

various sets of loads, speeds, and input voltages.

2.7 INVERTER

Jamie Dunn (2003) in the application note investigated some of the

fundamental concepts needed to obtain the proper MOSFET driver for an

application.

Mauricio Rotella et al (2009) proposed a converter for medium and

high power machine drive applications. The main advantage of the proposed

converter was, the optimization of levels with a minimum number of

semiconductors. However, the system needs six bidirectional and isolated

power supplies and three more for unidirectional, if the machine was not

using regenerative braking. The nine power supplies were reduced to only

four, all of them unidirectional, using three strategies: 1) the utilization of

independent and isolated windings for each phase of the motor; 2) the

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utilization of independent input transformers; and 3) the application of special

PWM strategies on the 27-level converter, to keep positive average power at

the medium power bridges and zero average power at the low-power bridges.

The generation of this PWM and control of this multi converter was

implemented using DSP controllers, which give flexibility to the system.

Berto Luzzo et al (2009) dealt with the operation of a BLDC drive

during the phase commutation. It was demonstrated that the switching

patterns were a combination of two basic commutation modes. For each

mode, the current transients during the phase commutation were determined

as well as two significant commutation related quantities, namely the decay

angle of the current in the outgoing phase and the maximum current excursion

in the non-commuting phase.

2.8 DIGITAL CONTROLLER

The application note by Ward Brown (2002) discussed the steps of

developing several controllers for brushless motors. The sensored, sensorless,

open loop, and closed loop design were considered. The code in this

application note was developed with the Microchip PIC16F877

microcontroller, in conjunction with the In-Circuit Debugger (ICD). This

combination was chosen because the ICD is inexpensive, and code can be

debugged in the prototype hardware without need for an extra programmer or

emulator. As the design develops, the target device can be programmed to

exercise the code directly from the MPLAB environment. The final code was

then ported to one of the smaller, less expensive, PIC microcontrollers. The

porting takes minimal effort because the instruction set was identical for all

PIC micro 14-bit core devices.

The application note detailed by Charlie Elliott and Steve Bowling

(2004) described a fully working and highly flexible software application for

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using the dsPIC30F to control BLDC motors without position sensors. The

software makes extensive use of dsPIC30F peripherals for motor control.

Piyush C. Desai and Ali Emadi (2005) presented a digital control

technique for trapezoidal BLDC motor drives. The technique treated BLDC

motor as a digital system and regulated speed with the help of two predefined

state variables, state-1 designed for high-speed operation and state-2 defined

for low-speed operation. A comparator compared actual speed with set speed

and then switched between appropriate states. Task of the digital control was

to deliver right amount of power to the motor by right numbers of state-1 and

state-2 operations so that average power delivery matches required power.

Leonard Elevich (2005) in the application note described the design

of a 3-phase BLDC motor drive based on Freescale’s 56800/E dedicated

motor control devices. They combined on a single chip the DSP’s calculation

capability with the MCU’s controller features. These devices offer many

peripherals dedicated to motor control, such as PWM modules, A/D

Converter, Timers, communication peripherals, on-board Flash and RAM.

Sankar and Ramareddy (2007) proposed the control of speed

regulation of a separately excited PMDC motor fed from single-phase fully

controlled converter. An efficient controller like PI, PD and PID for PMDC

drive operating in discontinuous mode of the converter was implemented. The

PI controller delivered better performance than other controllers in the

discontinuous mode of the converter, in achieving better speed regulation.

Fernando Rodriguez and Ali Emadi (2007) introduced a concept for

digital control of trapezoidal BLDC motors. The electrical time constants are

at least an order of magnitude faster than those time constants associated with

the mechanical parts. By quickly alternating the produced torque (which is

proportional to the current) an average torque was produced resulting in an

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average speed. The digital controller was implemented via two different

methods, namely conduction-angle control and current-mode control. Motor

operation was allowed only at two operating points or states. Alternating

between two operating points, resulted in an average operating point that

produced an average operating speed. The controller design equations were

derived from Newton’s second law.

Zhongfa Cai et al (2007) demonstrated a four-quadrant drive

control of the DC load motor using a rectifier apparatus for the PM machine

testing. In the proposed approach, the double closed-loop control

implemented the constant speed and constant torque loads for different testing

items. The median filtering and moving average filtering further improved the

reliability and accuracy of the testing system.

Murugan et al (2008) introduced a design and implementation of

electrically assisted power steering using BLDC motor for a vehicle. The

control architecture consists of two layers of control, namely the vehicle

speed associated control and the torque assist control. In the higher level of

control architecture, the vehicle speed controller works as an assistance level

controller for the steering effort. In the lower level, the torque controller gives

the effort level control. This has been realized by torque sensor and vehicle

sensor interfaced in the DSP. For implementing in the system, a DSP-based

BLDC motor controller with three-phase inverter module was designed using

Hall sensor feedback and a single DC-link current sensor. In this

implementation the motor was directly coupled to gearbox without clutch and

all abnormalities were handled by the processor. This was implemented

without modifying the vehicle supply system like changing the existing

alternator or rating of the battery and using the existing sensors. The design

was such a way that the feel of the driver assistance can be varied easily at

any time.

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The modelling and simulation of the BLDC motor was done using

the software package MATLAB/SIMULINK by Atef Saleh Othman Al-

Mashakbeh (2009). A speed controller was designed for closed loop operation

of the BLDC motor so that the motor runs very close to the reference speed.

The simulated system had a fast response with small overshoot and zero

steady state error.

Maher Mohammed and Dahaman Ishak (2009) designed a Low

pass Butterworth Infinite Impulse Response filter, for a back EMF sensorless

control of PMBLDC. The back EMF signal has noise from the driven sector

coupled on to the signal. A PWM signal was used to vary the voltage and

therefore the speed of the motor. So it was difficult to detect the zero crossing

events due to the coupled noise. A filtered back EMF signal was generated

which looks like ideal signal, which helps in the detection of zero crossing

event. The control at various speeds was achieved using dsPIC30F6010a. IIR

filter takes less time to execute and less memory location compared to Finite

Impulse Response Filter.

The BLDC motor with electronic controllers gives user-friendly

control in appliance application, leading to energy savings. The electronic

controller provides the required flexibilities in features which provide smooth

speed control of the motor in wired and wireless mode. The additional

electronic controller makes the 3-phase BLDC motor costlier as compared to

conventional motors. Ekram et al (2009) presented an alternative low cost

single-phase BLDC motor. The work focused on the commutation angle

estimation and adjustment to get adequate starting torque and better efficiency

at all the speed ranges. They also described the effects of Hall sensor position,

its adaptive estimation and dynamic optimization techniques.

Shanmugasundram et al (2009) proposed a digital implementation

of fuzzy logic controller using a ADUC812 microcontroller. Speed control

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achieved in this method was satisfactory. The motor was subjected to

disturbances by changing the load and the transient and steady-state behaviour

of the system was studied. It was found that the system responded faster with

no overshoot and the actual speed matched with the set speed under different

load conditions. It was also found that this drive was less affected by

electromagnetic interference and noise signals.

Shanmugasundram et al (2009) proposed a PWM control strategy

implemented in a versatile Aduc812 micro controller. The duty cycle was

varied and the variation in the speed and torque was measured.

Tan Chee Siong et al (2010) presented the study and analysis of the

fuzzy and PI control system applied to PMBLDC motor. Fuzzy control was

proposed and the performance of fuzzy controller was compared with PI

controller.

Nikola et al (2010) proposed a digital control strategy for BLDC

generators. Implementation was done on an FPGA device instead of signal

processors. The control strategy can be applied to existing generated systems.

The application of this strategy was towards speed regulation, but it can also

be used to regulate output voltage of the generator drive, or generated

electromagnetic torque.

Radu Duma et al (2010) presented a Rapid Control Prototyping

(RCP) toolbox, Target for Renesas M32C87, for MATLAB/Simulink which

can be used to generate real-time C code for the Renesas M32C87

microcontroller. The RCP toolbox contained a digital motor control library

which implemented a BLDC motor control algorithm. A practical application

for closed loop speed control of BLDC motor was presented. The toolbox

generated real-time C code for the Renesas M32C87 microcontroller. The

code can be generated without knowing in detail the architecture and

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peripherals of the microcontroller. For the controller tuning, a robust tuning

method based on the flat phase criteria was used. For real-time data exchange

between the target processor and the PC, the CAN bus was used. A CAN

library which contained blocks for sending/receiving messages over the CAN

bus, and a graphical user interface for control and monitoring of the CAN bus

were implemented.

Albert Rajan and Vasantharathna (2010) developed a

reconfigurable controller for the BLDC motor drive using fuzzy logic

technique to minimize the harmonics by varying the switching frequency and

duty ratio without affecting the voltage to the drive. This technique was

implemented in reconfigurable VERTEX II Pro development board and

observed that there was tangible improvement in performance in terms of

reduction in harmonics.

Chung-Wen Hung et al (2010) discussed the variable sampling

phenomenon in BLDC motor with Hall sensors. The feedback timing was

dependant on motor speed. The calculation method of PI controller was

different from the fixed sampling system. A simulator of variable sampling PI

controller was proposed. To improve dynamic response of torque loading

change, the authors proposed a torque load estimator for feed forward

compensation including an analog mode and variable sampling mode.

Naga Sujatha et al (2010) presented a control scheme combined

with neural network, fuzzy controller and PI controller for the BLDC motor.

The neural network control learnt continuously and gradually becomes the

main effective control. Performances of the proposed neural network were

compared with the corresponding fuzzy PI controller and conventional PI

controller.

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The proposed scheme by Sankar and Ramareddy (2011) improved

the tracking performance of separately excited DC motor by exploring the

features of Artificial Neural Network (ANN) over fuzzy logic controller. The

neural network controller enhanced the performance and dynamics of the DC

motor in comparison to conventional PI and fuzzy logic controller.

Vandana Govindan et al (2011) presented a digital speed control of

PMBLDC motor using TMS320F2812 DSP controller. The DSP controller

used here have the special features for digital motor control. Control

algorithms used for the speed control has been implemented by assembly

language programming in TMS320F2812 DSP controller. According to the

input command, feedback and the control algorithm, the PWM pulses for each

phase was generated by the DSP and was given to the MOSFET driver.

Rizk et al (2011) presented the design and implementation of a

DSP-based BLDC motor controller that was comparable to other more cost

effective motors. A high performance 16-bit DSC was used. Sensorless

control using the back EMF zero crossing technique was utilized, which

eliminated the need for Hall sensors. The speed was varied using the PWM

technique.

Ramesh et al (2011) presented the fuzzy, PI controller for speed

control of BLDC motor. The controller used three fuzzy logic controllers and

three PI controllers. The output of the PI controllers was summed and is given

as the input to the current controller. The current controller used P controller.

The mathematical modelling of BLDC motor was also presented. The BLDC

motor was fed from the inverter where the rotor position and current

controller were the input.

Muhammad Firdaus Zainal Abidin et al (2011) presented a

comparative study between PI, fuzzy and hybrid PI-Fuzzy controller for speed

42

control of BLDC motor. The control structure of the proposed drive system

was described. The simulation results of the drive system for different

operation modes were evaluated and compared. A fuzzy controller offered

better speed response for start-up while PI controller has good compliance

over variation of load torque but has slow settling response. Hybrid controller

had an advantage of integrating a superiority of these two controllers for

better control performances.

Alexandra-Iulia Stinean et al (2011) dealt with applicative aspects

concerning the control of speed and position of a BLDC servo system with

low, but variable in a given range moment of inertia. The adopted control

solutions, PI(D) control (as reference solution) and fuzzy control with

homogenous and non-homogenous dynamics were briefly presented.

Ming-Fa Tsai et al (2011) presented the model construction of a

BLDC motor via MATLAB/SIMULINK and FPGA control to evaluate the

performance of the BLDC motor control with various control schemes. The

constructed model consisted of a BLDC motor dynamics block, a Hall sensor

signals generation block, a back-EMF block, and a PWM generation logic

block. The control and PWM generation logic block were transferred to

digital hardware circuit in VHDL hardware description language for co-

simulation verification in the MATLAB/SIMULINK and ModelSim

environment.

A direct torque control technique for BLDC motors with non-

sinusoidal back electromotive force was presented by Parhizkar et al (2011).

Direct torque control has some benefits such as faster torque response and

reduced torque ripple for driving the BLDC motors. A speed control based on

fuzzy logic controller was proposed to reduce starting current, eliminate

overshoot in the torque and speed responses, simplify designing and

eliminating complex math formulas.

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Quan Jiang et al (2011) developed a direct approach to design the

HDD spinning speed controller. Firstly, the special features of HDD spindle

motors were analysed and a small signal equivalent model of the spindle

BLDC motor was proposed based on HDD’s constant spinning speed. Then a

discrete PI speed controller was introduced and the design of its PI gains was

studied.

2.9 CONCLUSION

Based on the literature survey it has been proposed to choose a

three-phase BLDC motor with built in Hall sensors to attain the objective of

the research work. MOSFETs are selected as switches for the inverter circuit.

A digital signal controller dsPIC30F4011 is opted to achieve precise control

in all the four quadrants.

The development and simulation of the digital controller for the

four quadrant operation of a BLDC motor and the results of simulation will be

presented in the next chapter.