An improved particle swarm optimization algorithm used in brushless DC motor
SUN Yu-sheng
XUE He-jie
Abstract：Aiming at overcoming the weak anti-jamming capability when brushless DC motor of electric vehicle runs under the base speed range,an improved particle swarm optimization (PSO)algorithm was designed,that is,by changing the learning factor and inertia weight to optimize quantitative factors,scale factor and control rules of the fuzzy controller.The simulation results verifid that the algorithm had features of short control time,small overshoot,high anti-interference,so it could made the brushless DC motor achieve stable operation state over a wide speed range.
Keywords：brushless DC motorparticle swarm optimization algorithmfuzzy controllearning factorinertia weight
Publication Date：2014-01-01
Online Publishing Date：2025-08-15(First online date of this platform, not the publication date of the document)
Pages：4( 48-51 )