@article{MAKHILLJEAS201914817661,
    title = {Optimal Control of Brushless DC Motor for Electric Vehicle Based on
Particle Swarm Optimization},
    journal = {Journal of Engineering and Applied Sciences},
    volume = {14},
    number = {8},
    pages = {2655-2660},
    year = {2019},
    issn = {1816-949x},
    doi = {jeasci.2019.2655.2660},
    url = {https://makhillpublications.co/view-article.php?issn=1816-949x&doi=jeasci.2019.2655.2660},
    author = {Ali Hadi},
    keywords = {Optimal control,particle swarm optimization,PID controller,brushless DC motor,DC (BLDC),parameters},
    abstract = {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.}
    }