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This paper presents an improved maximum power point tracking (MPPT) algorithm using a fuzzy logic controller (FLC) in order to extract potential maximum power from photovoltaic cells. The objectives of the proposed algorithm are to improve the tracking speed, and to simultaneously solve the inherent drawbacks such as slow tracking in the conventional perturb and observe (P and O) algorithm. The performances of the conventional P and O algorithm and the proposed algorithm are compared by using MATLAB/Simulink in terms of the tracking speed and steady-state oscillations. Additionally, both algorithms were experimentally validated through a digital signal processor (DSP)-based controlled-boost DC-DC converter. The experimental results show that the proposed algorithm performs with a shorter tracking time, smaller output power oscillation, and higher efficiency, compared with the conventional P and O algorithm.

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In this paper, a sliding mode control based multifunctional power converter is presented for electric vehicles and renewable energy applications. The proposed power converter is a multi-functional converter, which has capabilities of buckboost, bidirectional functions and even fault tolerance. Each mode of operation of the proposed system were analyzed and to validate the system, a prototype test-bed is built and tested using a Digital Signal Processor (DSP). The results show that the proposed system could be applicable for energy(fuel cell/wind/solar) and electric vehicle application. Index Termss-Fault Tolerance, Multi-Functional and Sliding Mode Control

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