Open AccessDTC with fuzzy logic for multi-machine systems: traction applications
Author(s) -
Ndoumbé Matéké Max,
Nyobe Yomé Jean Maurice,
Samuel Eke,
Mouné Cédric Jordan,
Alain Biboum,
Laurent Bitjoka
Publication year - 2021
Publication title -
international journal of power electronics and drive systems/international journal of electrical and computer engineering
Language(s) - English
Resource type - Journals
eISSN - 2722-2578
pISSN - 2722-256X
DOI - 10.11591/ijpeds.v12.i4.pp2044-2058
Subject(s) - mras , control theory (sociology) , robustness (evolution) , torque , computer science , fuzzy logic , direct torque control , control engineering , control system , electric vehicle , engineering , induction motor , vector control , voltage , control (management) , artificial intelligence , biochemistry , chemistry , physics , power (physics) , quantum mechanics , electrical engineering , gene , thermodynamics
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.