Performance analysis of ANFIS based SVPWM-DTC for Electric Vehicle application

Direct Torque Control (DTC) is the most often utilized technique in Electric Vehicles because of its various advantages. Nonetheless, torque pulsations lessen the framework's efficacy because of the hysteresis regulators. This outcomes in factor frequency activity, whereas the limited frequency examining produces an overshoot of the hysteresis band. In this way, activity at low speeds, chiefly when resistances of motor fluctuate, influences the machine's way of behaving. In this paper, a switching plan for speed control of the induction motor driven EV is surveyed considering Adaptive Neural Fuzzy Inference System (ANFIS) to work on the presentation. The discoveries of the study address a decrease in flux as well as torque ripple. A relative investigation of the suggested strategy with the Space Vector Pulse Width Modulation(SVM)-DTC shows further developed execution.