Abstract: maintenance, long operating life, and elimination of



vehicles have become a hot topic today because of their pollution-free and
cost-effectiveness. Brushless DC (BLDC) motor units play a crucial role in
electric vehicles. It has been progressively replacing conventional DC drives
in various applications due to its no brush and commutator erosion and has more
advantages , including high efficiency and reliability, smaller size , low
noise, less weight, less maintenance, long operating life, and elimination of
ionizing sparks from the commutator, and other benefits.

In order to
improve the performance of the BLDC control loop, a conventional PI controller
can control the speed of the BLDC. However, the stability of the machine cannot
be guaranteed when the load changes. The parameters of the controller are used
to improve the step response, as well as the performance characteristics of
BLDC motor. Effective optimization parameters of the PID controller is the main
criterion for improving performance. The traditional methods require manual
adjustment of parameters of PID.

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The main objective
was to obtain a stable, robust, and controlled system by tuning the PID
controller by using Particle Swarm Optimization (PSO) algorithm. The modeling
results show a significant increase in BLDC motor performance compared to
existing methods.


optimal, classical PID controller, BLDC motor, PSO Algorithm


1.    Introduction


BLDC now widely used for many industrial uses and vehicles due to a long
duration of life, response high dynamic, high efficiency, and the good
characteristics of speed vs torque. Because it is less noisy than other options
therefore thanks to the brushless motor. The proposed optimization technique
could be employed for a higher system order, as well as providing improved
system performance with minimal errors. The main plan is to be the applicable
technical PSO for the design and tuning of the parameters of the PID controller
to acquire an improved performance1-3. The PSO request to the PID controller
imparts the ability to repeatedly tune to an online procedure, while the
optimization algorithm request for the PID controller allows it to provide
optimal output by searching for the most Excellent set of solution for the PID
parameters. The BLDC motor has simple structure and more economic than other
engines so it is used in the variable speed control of the engine drives4-5.
They have improved the speed against the torque, greater efficiency and a
dynamic response improved in comparison with the other motors and offers a
higher torque to the engine, which make it useful in which space and weight are
critical factors. Also for the production of torque BLDC motor is required information
about the position can obtained with Hall sensors .The machine has three-phase
stator, three-phase distribution of windings; the brushless DC motor torque
depends on the inverse electric potential of a specific location. Usually a
brushless DC motor has a trapezoidal back EMF waveform and the stator consists
of conventional rectangular stator feed, assuming it has a stable torque, but
due to EMF waveform imperfections, current ripple and phase current
commutation, the torque ripple exist6-10. The permanent magnet DC motor uses
the mechanical commutator and the electric brush to realize the commutation.
However, the BLDC Motor uses Hall effect sensors instead of mechanical
commutator and brushes. The stator of the BLDC motor are the coils and the rotors
are the permanent magnet. The stator generates a magnetic field to rotate the
rotor. The Hall effect sensor detects the rotor position as a reversing
signal11-13. Therefore, the BLDC motor uses a permanent magnet instead of a
coil in the armature and therefore does not require a brush. In this paper,
three-phase and half-bridge pulse width modulation (PWM) inverter control
brushless DC motor speed. The dynamic characteristics of brushless DC motors
are similar to those of permanent magnet DC motors. The characteristic equation
of brushless DC motor can be expressed as 15:




?app (t) is the applied
voltage, ? (t) t is the motor speed, L is the inductance of the
stator, i (t) is the circuit current, R is the stator resistance,
?emf (t) t is the inverse electromotive force, T is
the torque engine, D-viscous coefficient, J-moment of inertia, Kt
-constant of engine torque, and Kb-constant electromotive

In this work,
the brushless DC motor is driven by PWM, controlled by the voltage of the source
inverter. By adjusting the motor stator voltage to control the speed of
brushless DC motor. Figure 1 shows a block diagram of a brushless DC motor.

2.    Conventional PI Controller


The control
design process begins by specifying performance requirements. The performance
of the control system often measured by applying the step function as a command
point variable, and then measuring the variable response process. The response
typically measured by measuring the properties of the specific waveform. Rise
Time is the time required the system to go from 10% to 90% of the value in
steady-state or final. The override percentage is the amount that the process
variable exceeds the final value, expressed as a percentage of the final value.
Settling time is the time required for the process variable within a certain
percentage (usually 5%) of the final value. The error of steady state is the
difference in finish between the process variable and the set-point. After
using one or all of these quantities to determine the performance requirements
of the control system, it is useful to identify the worst cases in which the
control system expected to meet these design requirements. Often, there is a
disturbance in the system that affects the process variable or variable process
measurement. It is important to design a surveillance system that performs
satisfactorily at worst. Measuring the control system’s ability to overcome the
effects of disturbances indicated by the rejection of the disturbance of the
control system. Once the performance requirements have been determined, it is
time to study the system and choose the appropriate control system.

(PID) control is the most commonly used control algorithm in industry, which is
widely accepted in industrial control. The popularity of PID controllers can be
attributed to allowing engineers to operate them in a straightforward, simple
manner. The control system works poorly, and it becomes unstable if the
improper values of the constant controller and tuning used. Thus, it becomes
necessary for the tuning of the parameters of the controller to obtain good
control performance with the correct choice of the constants.

The traditional
additive proportional integral controller is the simplest way to control and
widely apply to industry. The PI controller increases the rate of the reaction.
It produces very low stable state errors. Errors in this paper speed are due to
as input, PI controllers and outputs are brought into the system 15 16. PI
Controller for general equations



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