-Electric vehicles (EVs) require fast torque response and high drive efficiency. This paper describes a control scheme of fuzzy direct torque control of permanent magnet synchronous motor for EVs. This control strategy is extensively used in EV application. With direct torque control (DTC), the electromagnetic torque and stator flux can be estimated using the measured stator voltages and currents. The estimation depends on motor parameters, except for the stator resistance. The variation of stator resistance due to changes in temperature or frequency downgrades the performance of DTC, which is controlled by introducing errors in the estimated flux linkage vector and the electromagnetic torque. Thus, compensation for the effect of stator resistance variation becomes necessary. This work proposes the estimation of the stator resistance and its compensation using a proportional-integral estimation method. An electronic differential has been also used, which has the advantage of replacing loose, heavy, and inefficient mechanical transmission and mechanical differential with a more efficient, light, and small electric motors that are directly coupled to the wheels through a single gear or an in-wheel motor.

This paper presents an original variable gain PI (VGPI) controller for speed control of a direct torque neuro fuzzy controlled (DTNFC) induction motor drive.First, a VGPI speed controller is designed to replace the classical PI controller in a conventional direct torque controlled induction motor drive. Its simulated performances are then compared to those of a classical PI controller.Then, a direct torque neuro fuzzy control (DTNFC) for a voltage source PWM inverter fed induction motor drive is presented. This control scheme uses the stator flux amplitude and the electromagnetic torque errors through an adaptive NF inference system (ANFIS) to generate a voltage space vector (reference voltage) which is used by a space vector modulator to generate the inverter switching states. In this paper a modified ANFIS structure is proposed. This structure generates the desired reference voltage by acting on both the amplitude and the angle of its components.Simulation of the DTNFC induction motor drive using VGPI for speed control shows promising results. The motor reaches the reference speed rapidly and without overshoot, load disturbances are rapidly rejected and variations of some of the motor parameters are fairly well dealt with.

This paper presents a simple method for estimating rotor resistance in an indirect vector-controlled induction motor drive. This is important in vector control, if high-performance torque control is needed. For this purpose, a rotor resistance estimator using fuzzy logic technique is used and analysis, design, and digital simulations are carried out to demonstrate the effectiveness of the proposed estimator.

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In this paper, we are interested in the development of a robust control of active and reactive power for a Doubly Fed Induction Generator for variable speed wind energy using hybrid control by Adaptive Fuzzy logic and Sliding Mode Controller (AFSMC). This type of control is introduced to avoid the major disadvantage of variable structures systems which is the chattering phenomenon. Using the variable structure is to ensure the high dynamic of convergence and the robustness towards parametric variations and disturbances. Whereas the fuzzy control is introduced here in order to remove residual vibrations in high frequencies. Simulation results show that the proposed control strategy gives better results.