The global need to solve pollution problems has conducted automotive engineers to promote the development and the use of electric vehicle technologies. This paper focuses on the fuel cell hybrid electric vehicle which uses a proton exchange membrane fuel cell as a main source associated to hybrid storage device: lithium ion battery and ultracapacitors. A common interest in such technology is to spread out the energy flow between its different sources in order to satisfy the power demand for any requested mission. However, the challenging task stills the optimization of this split to reduce hydrogen consumption and respect, at the same time, the system limitations such as admissible limits of storage system capacities and battery current variation. An adaptive filtering-based energy management strategy is proposed in this paper to ensure an optimum distribution of the energy between the sources taking into account dynamic and energetic constraints of each device. For more performance, a fuzzy logic system is used to adapt the frequency of separation with the system state evolution. A sliding mode control is applied to control electric characteristics (voltage and currents) in the considered hybrid power supply. Simulation results, obtained under MATLAB^®/SimPowerSystems^® for four driving cycles are presented. The proposed strategy achieved good performances by respecting the ultracapacitors state of charge while preserving the battery lifetime under various driving missions.

This paper aims to improve the induction motor performances using a modified Direct Torque Control (DTC). The DTC is featured by its simple structure and fast dynamic response. Also, it does not require a speed sensor and it is less dependent on the motor parameters. However, the basic handicaps of this method are the torque ripples and the current distortions due to the presence of the hysteresis controllers. This paper aims; firstly, to replace the hysteresis controllers and the switching table by a fuzzy logic system in order to overcome these handicaps. Furthermore, the sampling frequency is another parameter which must be investigated to reduce the commutation losses and the harmonic stator current waves. The second purpose of this paper is to reduce the execution time using a Field Programmable Gate Array (FPGA). The FPGA is able to execute the Fuzzy DTC (FDTC) with a higher sampling frequency, thanks to its parallel processing relative to the Digital Signal Processor (DSP). The FDTC model is verified by simulation using system generator tool and validated by experimentation utilizing an FPGA Virtex 5. Thus, excellent performances at low processing time are obtained using the Xilinx FPGA Virtex 5.

The installed energy production capacity of wind turbines is growing intensely on a global scale, making the reliability of wind turbine subsystems of greater significance. However, many faults like Inter-Turn Short-Circuit (ITSC) may affect the turbine generator and quickly lead to a decline in supplied power quality. In this framework, this paper proposes a Sliding Mode Observer (SMO)-based Fault Tolerant Control (FTC) scheme for Induction Generator (IG)-based variable-speed grid-connected wind turbines. First, the dynamic models of the wind turbine subsystems were developed. The control schemes were elaborated based on the Maximum Power Point Tracking (MPPT) method and Indirect Rotor Flux Oriented Control (IRFOC) method. The grid control was also established by regulating the active and reactive powers. The performance of the wind turbine system and the stability of injected power to the grid were hence analyzed under both healthy and faulty conditions. The robust developed SMO-based Fault Detection and Isolation (FDI) scheme was proved to be fast and efficient for ITSC detection and localization.Afterwards, SMO were involved in scheming the FTC technique. Accordingly, simulation results assert the efficacy of the proposed ITSC FTC method for variable-speed wind turbines with faulty IG in protecting the subsystems from damage and ensuring continuous connection of the wind turbine to the grid during ITSC faults, hence maintaining power quality.

This paper aims to search for a high-performance low-cost standalone photovoltaic water pumping system (PVWPS) based on a three-phase induction motor (IM). In order to control the IM, a fuzzy direct torque control (FDTC) is proposed in this paper for overcoming the limitations of the conventional direct torque control (CDTC). In fact, the CDTC suffers from several problems such as torque ripples, current distortion, and switching frequency variations. These problems can be solved with the proposed FDTC. To ensure high performance of the PVWPS, the reference torque is generated using a fuzzy speed controller (FSC) instead of a conventional proportional integral speed controller. In order to extract the maximum amount of power, the proposed maximum power point tracking controller is based on variable step size perturb and observe to surmount the weakness of the conventional perturb and observe technique. The performance of the proposed FDTC based on the FSC under variable climatic conditions is demonstrated by digital simulation using Matlab/Simulink. The obtained results show the effectiveness of the suggested FDTC based on the FSC compared with the CDTC in terms of pumped water, reduction in flux and torque ripple, diminution of losses, and decrease in the stator current harmonic.