Design of speed control for brushless DC motor used for electric vehicle based on adaptive neuro-fuzzy inference system

Abstract

This paper presents a study for control the brushless DC motor speed applied in an electric vehicle. The configuration of the proposed method is an Adaptive Neuro-fuzzy inference controller applied to an electric vehicle's dynamics model. Matlab Simulink was used to build the configuration based on an accurate mathematical model for electric vehicle and the motor. Results proved that ANFIS has rapid robustness efficiency, also in the domain of the motor response characteristics. ANFIS expressed superior proficiency. Moreover, the controller shows good speed tracking and anti-interference ability in a typical city driving environment.