Brushless doubly fed induction machine has acquired relevance as a wind electric generator because of its relative merits over doubly fed induction generator. However, the main drawback of brushless doubly fed induction machine is the presence of torque ripples due to spatial and time harmonics caused by two stator windings and complex rotor structure. In this article, a special design of brushless doubly fed induction machine using delta-star connection in one of the two stator windings is proposed to reduce the torque ripples. Simulation of the new brushless doubly fed induction machine design is performed in ANSYS Maxwell software, and the results when compared with the conventional winding design validated the effectiveness of the new design in minimizing the torque ripples. Prototype of the new brushless doubly fed induction machine has been fabricated and tested in laboratory. Tests have been conducted in both synchronous and asynchronous modes of brushless doubly fed induction machine. Simple induction and cascade connections have been tested in asynchronous motoring mode. Motoring as well as generating conditions have been tested in synchronous mode. Test results show that the new brushless doubly fed induction machine has not only the desired characteristics for wind turbine generator but also capabilities suited for variable torque–variable speed motor applications as well as constant speed applications.

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In order to reduce the greenhouse gas emission and limit the rise in global temperature, the trend in automotive industry is changing rapidly and most of the manufacturers are moving towards the electrification of vehicles. Computational intelligence and machine learning play a very important role in the field of electric vehicles (EVs) due to the necessity of automatic control in battery charging and port accessibility. Due to the limited ranges

Integration of maximum power point tracking (MPPT) with photovoltaic (PV) systems is a necessity to track and deliver maximum power available. This paper focuses on comparing the tracking efficiencies of Perturb and Observation method (P&O), Incremental Conductance (IC) and Fuzzy-Logic System based MPPT technique. Change in atmospheric condition such as varying irradiance causes the output power to continuously vary over time. IC as well as P&O based MPPT techniques exhibit poor dynamic responses and so operating points keeps fluctuating. Variation in solar irradiance over a day at constant temperature is given as input to the solar PV module. The algorithm used here implements tracking over the period of a day. All the simulation study are implemented with the use of MATLAB/SIMULINK.