• Energy control • optimal vector control induction motor • dynamic modeling and simulation • chaotic stability Reducing air pollution in the transport sector is becoming a necessity for multiple environmental problems. This article highlights an optimal vector control strategy for an induction motor intended for electric vehicles., as a sustainable and less polluting alternative, aiming to solve the problem of adaptability to the varying dynamics of vehicle operation. The scientific contribution of this article proposes a model of the induction motor associated with an inverter controlled by pulse width modulation (PWM), then an optimal vector control with Proportional Integral (PI) and Artificial Neural Network (ANN) controllers. Four simulation scenarios are developed to better highlight the impact of the proposed strategy. The results obtained show a significant improvement in the adaptability of the system with a rise time of 0.08s, a response time of 0.97s and an overshoot of 9.1% for the PI controller. Also, show a rise time of 0.043s, a response time of 0.17s and an overshoot of 2.1% for the Artificial Neural Network controller. Its results presented in this work, confirm that this approach does not just improve the simple control of the motor, but opens the way to a fine and adaptive control of the dynamic behaviors of the system, thanks to the optimal vector control.
Mouodo et al. (Sun,) studied this question.