An accurate estimation technique of the state of charge (SOC) of batteries is an essential task of the battery management system. The adaptive Kalman filter (AEKF) has been used as an obsever to investigate the SOC estimation effectiveness. Therefore, The SOC is a reflexion of the chemistry of the cell which it is the key parameter for the battery management system. It is very complex to monitor the SOC and control the internal states of the cell. Three battery models are proposed and their state space models have been established, their parameters were identified by applying the least square method. However, the SOC estimation accuracy of the battery depends on the model and the efficiency of the algorithm. In this paper, AEKF technique is presented to estimate the SOC of Lead acid battery. The experimental data is used to identify the parameters of the three models and used to build different open circuit voltage–state of charge (OCV-SOC) functions relationship. The results shows that the SOC estimation based-model which has been built by hight order RC model can effectively limit the error, hence guaranty the accuracy and robustness.

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A particle-in-cell/Monte Carlo model is developed to study and analyze the electrical characteristics of the nonequilibrium plasma created by radio frequency (RF) discharge in Ar/O2 mixtures in the presence of crossed electric and magnetic fields. The method of collision treatment is based on an optimized estimation of the free time flight. The needed basic data—more specifically, the ion–neutral cross sections—are determined first. The simulation conditions are 50 mTorr for the total gas pressure and 200 V for the peak of the RF voltage at a frequency of 13.56 MHz. The magnetic field is varied from 0 to 50 G. The effect of the partial pressure ratio of O2 in the mixture and the effect of the magnitude of the magnetic field are discussed. In particular, the results show an increase of the plasma density that is ten times higher in the presence of a magnetic field.

Abstract-This paper focuses on a second order sliding mode based direct power controller (SOSM-DPC) of a three-phase grid-connected voltage source converter (VSC). The proposed control scheme combined with fuzzy logic aims at regulating the DC-link voltage of the converter and precisely tracking arbitrary power references, in order to easily control the system's power factor. Therefore measures are proposed to reduce the chattering effects inherent to sliding-mode control (SMC). Simulations performed under Matlab/Simulink validate the feasibility of the designed Fuzzy-SOSM. Simulation results on a 1kVA gridconnected VSC under normal and faulted grid voltage conditions demonstrate good performance of the proposed control law in terms of robustness, stability and precision.

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This paper proposes the design and implementation of a novel direct torque controlled induction machine drive system. The control system enjoys the advantages of stator vector control and conventional direct torque control and avoids some of the implementation difficulties of either of the two control methods. The stator vector control principal is used to keep constant the amplitude of stator flux vector at rated value, and to develop the relationship between the machine torque and the rotating speed of the stator flux vector. Thus, the machine torque can be regulated to generate the stator angular speed, which becomes a command signal and permits to overcome the problem of its estimation. Furthermore, with the combined control methods, the reference stator voltage vector can be generated and proportional-integral controllers and space vector modulation technique can be used to obtain fixed switching frequency and low torque ripple. Simulation experiments results indicate that, with the proposed scheme, a precise control of the stator flux and machine torque can be achieved. Compared to conventional direct torque control, presented method is easily implemented, and the steady performances of ripples of both torque and flux are considerably improved

This paper focuses on wind energy conversion system (WECS) analysis and control for power generation along with problems related to the mitigation of harmonic pollution in the grid using a variable-speed structure control of the doubly fed induction generator (DFIG). A control approach based on the so-called sliding mode control (SMC) that is both efficient and suitable is used for power generation control and harmonic-current compensation. The WECS then behaves as an active power filter (APF). The method aims at improving the overall efficiency, dynamic performance and robustness of the wind power generation system. Simulation results obtained on a 20-kW, 380-V, 50-Hz DFIG confirm the effectiveness of the proposed approach