Precise Induction Motor Parameters Identification for Robust Electric Vehicle Cruise Control Using dSPACE 1104

Abstract

Electric vehicles are one of the most effective solutions for reducing greenhouse gas emissions and mitigating global warming. Improving their performance and efficiency is therefore a fundamental priority. This research focuses on optimizing the speed control of motors used in electric vehicles, particularly asynchronous motors, using advanced control techniques based on artificial intelligence. To experimentally validate these control strategies and techniques, a test bench was set up comprising an induction motor, an alternator and a variable load connected to the alternator output, in order to simulate a variable resistive torque. This article focuses on the identification of motor parameters using advanced identification methods, and the results are verified using the induction motor model in the MATLAB/Simulink environment. The aim is to validate the parameters obtained with a view to experimentally testing the various control algorithms simulated in MATLAB/Simulink.