Improved direct torque control of doubly fed induction motor in electric vehicles using fuzzy logic controllers

• Modeling and design of an intelligent control system for electric vehicle applications. • Improvement of direct torque control of DFIM for electric vehicle applications through the use of fuzzy controllers. • Comparative analysis between classical DTC control and DTC based on fuzzy logic of the doubly feed induction motor for electric vehicle applications. Conventional Direct Torque Control (DTC) presents challenges such as significant torque ripples and limited adaptability to load variations. These challenges are exacerbated when applied to electric vehicles (EVs) due to changes in driving speed and the load torque that depends on road conditions. In this context, this work aims to improve the DTC of a Doubly Fed Induction Motor (DFIM) used for electric propulsion. Hysteresis comparators and the control table, responsible for the ripples in conventional DTC, have been replaced by fuzzy logic controllers. Additionally, a fuzzy logic speed controller has been designed to ensure better speed tracking across different ranges (low, medium, and high speed). Simulations performed using Matlab/Simulink allowed for a comparison of the proposed control strategy with conventional DTC. The results show a reduction of 42 % in torque ripples. Furthermore, the proposed control strategy does not show any overshoot compared to the conventional DTC strategy, which shows an overshoot of 1.5 km/h. This improves adaptability to load variations and the precision of dynamic response, optimizing the overall vehicle performance. These improvements result in smoother driving and increased overall efficiency of EVs, demonstrating the practicality and effectiveness of the fuzzy logic control strategy for electric propulsion applications.