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This paper presents the modeling, control and simulation of an electric vehicle with four in-wheel 15 kw induction motors drive 4WDEV controlled by a direct torque control DTC strategy, where two control techniques are presented and compared for controlling the electric vehicle speed: the first one is based on a classical PI controller while the second one is based on a fuzzy logic controller (FLC). The aim is to evaluate the impact of the proposed FLC controller on the efficiency of the 4WDEV taking into account vehicle dynamics performances, autonomy and battery power consumption. When the classical controller can't ensure the electric vehicle stability in several road topology situations. To show the efficiency of the proposed new control technique on the traction system by 4WDEV. The vehicle has been tested in different road constraints: straight road, sloping road and curved road to the right and left using the Matlab / Simulink environment. The analysis and comparison of the simulation results of FLC and PI controllers clearly show that the FLC ensures better performances and gives a good response without overshoot, zero steady state error and high load robustness rejection, compared to the PI controller which is present an overshoot equal 7.3980% and a rise time quite important (0.2157 s with PI controller and 0.1153 s with FLC). As well as the vehicle range has been increased by about 10.82 m throughout the driving cycle and that the energy consumption of the battery has been reduced by about 1.17% with FLC.

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The current paper presents a new, Direct Torque and Flux Control strategy based on sliding mode control (SMC) and space-Vector Modulation (SVM) is proposed for induction motor Sensorless drives in order to solve existing problems in conventional control by Direct Torque Control (C-DTC); such as, high flux, torque and current ripple, and variable switching frequency. The presence of hysteresis comparators is the major reason for high torque and flux ripples in C-DTC. In SM-DTC, the hysteresis comparators and switching Table are replaced by sliding mode controller. The stability and robustness of the controller are proven analytically using the Lyapunov theory. To avoid the use of a mechanical sensor, the rotor speed estimation is made by a sliding mode observer (SMO) based model reference adaptive system (MRAS). The reference model is a Sensorless sliding mode observer and the adaptive model is a typical current model. Finally, the proposed schemes are simulated under Matlab / Simulink environment, and the simulation results show the effectiveness of the proposed Sensorless control.