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