Abstract:

Electric

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.

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.

Keywords:

nonlinear,

optimal, classical PID controller, BLDC motor, PSO Algorithm

1. Introduction

Motor

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:

Where:

?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

force.

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.

Proportional-integral-differential

(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