Improved direct torque control strategy performances of electric vehicles induction motor

Hassane Bachiri, Brahim Gasbaoui, Abdelkader Ghezouani, Nouria Nair


A three-wheeled electric scooter (3WES) with two control techniques is modeled and simulated in this study. The conventional direct torque control (C-DTC) and the DTC based on a neural network artificial multi layers (ANN-DTC). The objective is to assess the traction system's response to the control approach. by 3WES taking into account the dynamics of the scooter, the range and the energy consumption of the battery. The 3WES was simulated numerically using the MATLAB/Simulink environment, which is powered 1.5 kW by two induction motors integrated into the rear wheels. Where the reference speeds of the rear wheels detected using a differential electronic. This can possibly cause it to synchronize the wheel speed in any curve. Each wheel's speed was controlled by two types of regulators, PI and ANN, to increase stability and reaction time (in terms of set point tracking, disturbance rejection and rise time). The proposed ANN-DTC control technique reduces torque, stator flux, and current ripple by roughly 35%. While the range of 3WES has increased by approximately 8.062 m, the battery power consumption has decreased by nearly 0.25%.


3WES; Artificial neural network ANN; Direct torque control DTC; Induction motor IM; Speed control PI

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