Artificial neural networks applied on double squirrel cage induction motor for an electric vehicle motorisation

摘要

Double squirrel cage induction motor had proved to be an appropriate solution for most driving loads, which require high starting torque and a low starting current. It presents the future of sustainable automotive industry due to the strategies of control and command of which it can be equipped. This paper presents a speed control comparison between the PI controller and the advanced techniques of control based on the artificial neural networks in order to be applied for an electric vehicle motorization. The results of various simulation tests highlight the robustness properties of the different control strategies based on orientation of the rotor flux.