Robustness of Fuzzy Logic Based DTC for DFIM in Electric Vehicle Traction under Road Slope and Wind Speed Disturbances

Abstract

The transportation sector is one of the main sources of greenhouse gas emissions. This has prompted countries around the world to promote the decarbonization of this sector. This goal will be achieved by replacing internal combustion vehicles with electric vehicles (EV). To contribute to this transition, improvements to the powertrain of EV are necessary. In this context, this article presents a comparison between two control strategies used for Doubly-Fed Induction Machine (DFIM) control: conventional DTC and fuzzy logicbased DTC (FL-DTC). DFIM is used in the powertrain of EVs. This study examines DFIM operation in the face of challenges such as slope and wind variations, as well as sudden changes in EV speed (acceleration and deceleration to simulate realistic DFIM operation in EVs. The results indicate that FL-DTC offers high tracking accuracy and faster dynamic response, as well as a significant reduction in torque and power ripple compared to conventional DTC. These improvements ensure significant optimization of operational stability and efficient energy management within the traction system of EVs, confirming the relevance of FL-DTC as a robust control strategy for the propulsion of DFIM-based EVs.