Elkhatib Kamal

Maximum power control of hybrid wind-diesel-storage system

Optimum wind energy extraction is a very important economical target. This paper is concerned with the development of a robust controller for the wind turbines in hybrid wind-diesel storage system (HWDSS). The proposed algorithm, which is based on fuzzy linear matrix equalities (FLME), maximizes the power coefficient for a fixed pitch. Moreover, it reduces the voltage ripple and stabilizes the system over a wide range of wind speed variations. The control scheme is tested for different profiles of wind speed pattern and provides satisfactory results.

Telemetry microcomputer application in satellites OBC

An on-board computer (OBC) is the brain of any satellite. In this paper we discuss the design of an on-board computer system for micro satellite; the design technologies for large commercial satellites cannot be directly used for the micro satellite due to the compactness of OBC. This equipment monitors and auto control pressure, temperature, direction, all the telemetry equipments, the communication channel transmission and receiving between satellite and terrestrial stations. It is generally a very expensive device, with cost amounting to hundreds of thousands of dollars. Our design for general purpose and adaptable OBC, for use in general as low-earth-orbit (LEO) microsatellites. Our system is economical system and compatible with a small size satellite the hardware and software design of this OBC is based upon open and flexible design architecture. The idea is that the design can be used in or adapted for a variety of small LEO micro-satellites with minimal modifications. Keeping these goals in view, a complete architecture of the OBC has been discussed and developed. The design is based on the Intel X86 microprocessor technology. Instructions set, addressing modes, interrupts, in and out and digital and analog interfaces. In addition, the features of on-board computer hardware and operating system are presented. Also the memory subsystem error log is discussed.

Hierarchical Energy Optimization Strategy and Its Integrated Reliable Battery Fault Management for Hybrid Hydraulic-Electric Vehicle

Reduction of fuel consumption is an indispensable part of automotive industry in recent years. This induces several developments of hybrid vehicles with different structures. This paper deals with reliable and robust energy management strategy for a hybrid hydraulic-electric intelligent vehicle. The main objective of this paper is the development of a suboptimal control strategy based on fuzzy logic and neural network for minimizing total energy consumption while ensuring a better battery life. For this purpose, fuzzy supervisory fault management, which can detect and compensate the battery faults, regulates all of the possible vehicles operation modes. Then, control strategy based on fuzzy logic controller (FLC) is developed. The FLC membership function parameters are tuned by employing neural network to manage power distribution between electric motor and internal combustion engine (ICE). Control strategy is switched between optimized FLCs to enhance the suboptimal power split between the different energy sources and manage the ICE to work always in the vicinity of its optimal condition. Finally, a robust fuzzy tuning controllers are investigated to give a good torque set point tracking. Simulation results, while using TruckMaker/MATLAB software, confirm that the proposed approach leads to suboptimal energy consumption of the vehicle for any unknown driving cycles and compensate battery faults effects.

Intelligent Energy Management Strategy Based on Artificial Neural Fuzzy for Hybrid Vehicle

This paper proposes an intelligent energy management strategy for a hybrid hydraulic–electric vehicle in order to minimize its total energy consumption. It proposes first to model the vehicle total energy consumption and investigates the minimization of an expended energy function, formulated as the sum of electrical energy provided by the on-board batteries and consumed fuel. More precisely, it is proposed in this paper an intelligent controller that shows its capabilities of increasing the overall vehicle energy efficiency and, therefore, minimizing total energy consumption. The proposed strategy consists of an advanced supervisory controller at the highest level (third), which corresponds to a fuzzy system deciding the most appropriate operating mode of the system. In the second level, an intelligent optimal control strategy is developed based on neuro-fuzzy logic. Then, in the first level, there are local fuzzy controllers to regulate vehicle subsystems set points to reach the best operational performance. The advantage of the proposed strategy could be summarized as follows: first, it can be implemented online and second, reduces total energy consumption compared with several traditional methods. The proposed strategy validations are performed using a mix of automotive TruckMaker and MATLAB/Simulink developed software on several (standard or not) driving cycles.

Robust Takagi-Sugeno fuzzy control of PV system

This paper concentrates on the development of robust maximum power control for variable speed wind turbines with a double feed induction generator in the presence of wind disturbance and parameter uncertainties. To increment the actual manner for the wind turbine system, the effects of the mechanical and electrical part are taken in consideration. The algorithm is based on Takagi-Sugeno fuzzy model to increases the efficiency of the wind power generation systems and guarantees almost convergence. Conditions for the stability of fuzzy control systems are proved using a fuzzy Lyapunov function and formulated by Linear Matrix Inequalities. A Parallel Distributed Compensation scheme of fuzzy controllers is stated for closing the feedback loop. The advantages of the proposed strategy are: i) Enough stability conditions in the LMI is given for uncertain nonlinear system; ii) stabilizes the system over a wide range of wind speed variations and parameter uncertainties; iii) maximize output power from the system; iv) improving the system efficiency than other techniques. The influence of the proposed controller is finally proved through numerical simulations and compared with different strategies.

Maximum power from wind energy system using fuzzy controller

This paper illuminates how to maximize the power extraction from wind energy system. This paper compare between two techniques for maximization the power. A method is presented based upon on power signal feedback using fuzzy controller. The performance of the controllers design methodology is finally presented through a wind energy conversion system to maximize the extraction of power from wind energy (WE) system.