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This paper presents a novel bidirectional currentfed dual inductor push-pull DC-DC converter with galvanic isolation. The converter features active voltage doubler rectifier, which is controlled by the switching sequence synchronous to that of the input-side switches. The control algorithm proposed enables full-soft-switching of all switches in a wide range of the input voltage and power without requirement of snubbers or resonant switching to be employed. Operation principle for the energy transfer in the both directions is described. Experimental results as well as basic design guidelines are presented.

This paper provides a performance analysis of a wearable photovoltaic system mounted on the outer surface of a backpack. Three types of photovoltaic materials, commonly used for electricity generation, have been investigated under various conditions including sun irradiance, angle-of-incidence and sun inclination. The results of the investigation have shown that the system equipped with the rigid mono-Si panels performs 3.5 to 4.9 times better than the system equipped with a-Si flexible PV modules. The average power generated by the wearable photovoltaic system is about 30% of the maximum installed power for any photovoltaic type. This paper presents the test data resulting from the evaluation of the daily energy production of a wearable photovoltaic power supply.

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This paper proposes a new artificial neural network-based position controller for a full-electric injection moulding machine. Such a controller improves the dynamic characteristics of the positioning for hot runners, pin valve and the injection motors for varying moulding parameters. Practical experimental data and Matlab's System Identification Toolbox have been used to identify the transfer functions of the motors. The structure of the artificial neural network, which used positioning error and speed of error, was obtained by numerical modelling in Matlab/Simulink. The artificial neural network was trained using back-propagation algorithms to provide control of the motor current thus ensuring the required position and velocity. The efficiency of the proposed ANN-based controller has been estimated and verified in Simulink using real velocity data and the position of the injection moulding machine and pin valve motors.