The present paper deals with a real time implementation of a new adaptive frequency-based power management strategy of a small-scale hybrid battery-super capacitor system, dedicated to an electric vehicle. The ultimate objective of the strategy is to ensure a smart use of the two sources, improving as a consequence both the autonomy and the system lifetime. To do so, and unlike the conventional power frequency separation technique, the filter adapts its pass band frequency to keep the charge’s state of each source in a tolerable range and provides power amounts to the load demand. The experimental results demonstrate that the system commutates smoothly between the operating modes, which proves the effectiveness of the proposed control techniques.

The problematic is to study the management of a hybrid energy system, depending on demand, dedicated to self-governing houses. Energy can be supplied by a photovoltaic panel, a wind turbine and a diesel generator and it can be stored in batteries. The study of this type of systems requires a good control strategy and an effective management. The main objective of this study is to develop a reliable management model and to simulate the hybrid system of a house located in Monastir-Tunisia, with different domestic loads, such as a washing machine, freezer, refrigerator... A system of energy management that can adjust, optimize and adapt the consumption to the available energy resources while satisfying the request is then examined. Thus, to study the problem of energy management and reduce energy consumption and production of greenhouse gases, the definition off an analysis tool on MATLAB/SIMULINK has allowed the covering of load demand in an optimized manner using the optimal system chosen by HOMER.

This paper deals with robust direct power control of a grid-connected brushless doubly-fed induction generator(BDFIG). Using a nonlinear feedback linearization strategy, an attempt is made to improve the desired performances by controlling the generated stator active and reactive power in a linear and decoupled manner. Therefore, to achieve this objective, the Lyapunov approach is used associated with a sliding mode control to guarantee the global asymptotical stability. Thus, an optimal operation of the BDFIG in sub-synchronous operation is obtained as well as the stator power flows with the possibility of keeping stator power factor at a unity. The proposed method is tested with the Matlab/Simulink software. Simulation results illustrate the performances and the feasibility of the designed control.

A model reference adaptive system (MRAS) based speed estimator for sensorless induction motor (IM) drive is proposed in this paper. The MRAS is formed with flux rotor and the estimated stator current vector. The reference model utilizes measured current vector. On the other hand, the adjustable model uses the estimated stator current vector. The current is estimated through the solution of machine state equations. The performance of the estimator under regeneration is an important aspect, which is studied in this paper through the small signal analysis. In this paper, the principle and method of speed estimation and control set-up are described, as well as the results of an experiment that verified the effectiveness of the proposed method.