TY  - JOUR
T1  - Optimal Control of Brushless DC Motor for Electric Vehicle Based on
Particle Swarm Optimization
AU - Abdulwahid, Ali Hadi 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 8
SP  - 2655
EP  - 2660
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.2655.2660
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.2655.2660
KW  - Optimal control
KW  -particle swarm optimization
KW  -PID controller
KW  -brushless DC motor
KW  -DC (BLDC)
KW  -parameters
AB  - The revolution of electric vehicles is characterized by rapid development. This type of vehicle has
witnessed its greatest growth; the reason for interest in electric vehicles is not only in reducing dependence
on oil but also in preserving the environment. The Brushless DC (BLDC) plays a decisive role in electric
vehicles and has gradually replaced the DC motor in many applications as it has no brush and commutator
erosion and has many advantages including high efficiency, reliability and smaller size, less weight, need-less
maintenance, long operating life and absence of ionized sparks due to the commutator. In this study, the
Optimization algorithm for Particle Swarm (PSO) was used to find the optimal parameters of the PID. The main
goal of this study is to get a stable, reliable and controlled system, the results of the simulation show a
significant increase in the performance of the BLDC motor compared to the existing methods. To be a more
effective way to control the position, torque, speed.
ER  -