Optimizing the performance of six-phase induction motor-powered electric vehicles with fuzzy-PID and DTC

Abstract

Abstract Automotive manufacturers are working on electric vehicles in response to regulations aimed at lowering emissions and increasing fuel efficiency. The purpose of this article is to build and simulate an electric vehicle (EV) application that drives an electric car with a modified six-phase induction motor (MPPIM). The effects of a voltage vector modulation on stator flux and torque changes are illustrated through an investigation of the fundamentals of direct torque control (DTC) for induction machines. Rewinding the stator to function as an MPPIM enhances torque pulsation and dependability of the three-phase asynchronous motor. The proposed DTC scheme is designed to enhance dynamic response and efficiency, making it suitable for the demanding requirements of EV propulsion systems. It is advised to use a fuzzy control strategy to modify the PID controller’s settings to maintain the EV speed at the desired reference speed. The EVs are driven by an FPID that optimizes a DTC linked with a space vector modulation using MATLAB/SIMULINK software to control the speed of the Electric Vehicle. According to simulation results, the suggested control strategy successfully lowers voltage and current total harmonic distortion, enhances the system’s ability to detect changes in the reference speed, and lowers errors in electric flux and Electric Vehicle speed. Overall, the results show that DTC control of six-phase induction motors offers an effective and practical solution for contemporary electric vehicles, opening the door for developments in electric drive technology and helping to create more environmentally friendly transportation networks.