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All Journal International Journal of Power Electronics and Drive Systems (IJPEDS)
Ndoumbé Matéké Max
University of Douala
Control & Systems Engineering Electrical & Electronics Engineering

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DTC with fuzzy logic for multi-machine systems: traction applications Ndoumbé Matéké Max; Nyobe Yomé Jean Maurice; Eke Samuel; Mouné Cédric Jordan; Alain Biboum; Bitjoka Laurent
International Journal of Power Electronics and Drive Systems (IJPEDS) Vol 12, No 4: December 2021
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijpeds.v12.i4.pp2044-2058

Abstract

In this work, a direct torque control (DTC) method for multi-machine systems is applied to electric vehicles (EVs). Initially, the DTC control method associated with the model reference adaptive system (MRAS) is used for speed control, and management of the magnetic quantities is ensured by the variable master-slave control (VMSC). In order to increase the technical performance of the studied system, a DTC method has been associated with a fuzzy logic approach. These two control methods are applied to the traction chain of an electric vehicle to highlight its speed, precision, stability, and robustness metric during particular stress tests imposed on the wheel motor. The results obtained in MATLAB/Simulink software made feasible a comparison of two proposed methods based on their technical performances. It should be noted that the direct fuzzy logic torque control (DFTC) has better performance than the DTC associated with the MRAS system as a rise time reduction of 1.4%, an oscillation of torque, and flux amplitude of less than 9%, static steady-state error near zero. The DTFC control method responds favorably to electric vehicle traction chain systems by the nature of the comfort and safety provided.
Co-Authors Alain Biboum Bitjoka Laurent Eke Samuel Mouné Cédric Jordan Nyobe Yomé Jean Maurice