Fuzzy Logic Enhanced DTC Control Topologies For A Four-Wheel Drive Electric Vehicle

In this work, a direct torque control (DTC) method for four-wheel drive electric vehicles (EVs) is applied. Each wheel has an induction motor that provides its motion. Firstly, the DTC control method associated with the model-referenced adaptive system (MRAS) is used for speed control, and the management of magnetic quantities is provided by the variable master-slave control (VMSC) to the topology of the vehicle under investigation. In order to increase the technical performance of the studied system, a DTC method has been combined with a fuzzy logic approach. For this scenario, the control and management mechanisms of the dynamic and magnetic parameters are unchanged except for those with a speed that can be regulated via the PI. An electronic differential (ED) is used to control speeds during specific phases such as turning, climbing, and descending. The proposed control method allows highlighting the speed, accuracy, stability, and metric robustness during specific stress tests imposed on the wheel motor. The results obtained in MATLAB/Simulink software allowed us to compare the technical performances obtained against other control methods. The DTFC control method responds favorably to electric vehicle traction chain systems by the nature of the comfort and safety provided

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