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Summary: Bootstrap capacitor in FET gate driver plays an important role in the transient performance of the half bridge configured synchronous buck DC‐DC converter especially in the top switch. In this paper, a new bootstrap capacitor based GaN‐FET driver is proposed. This new GaN‐FET driver is tested in a synchronous buck converter for performance verification like dvdt immunity, transient response, and voltage ringing. A comparison study with the existing LM5113 (Texas Instrument)–based driver for GaN‐FET and IR2110‐based Si‐MOSFET driver on a DC‐DC converter is carried out to show the performance improvement using the proposed GaN‐FET driver. The simulation study is performed on spice‐based NI‐Multisim 14.1. Finally, the designed GaN‐FET driver is tested on a 60‐W synchronous buck DC‐DC converter in open‐loop and closed‐loop configuration. [ABSTRACT FROM AUTHOR]

This paper deals with the selection of dc-dc converter and control variable required to track the maximum power of photovoltaic (PV) array, to optimize the utilization of solar power. To reduce the maintenance cost and to simplify the model, the battery has not been used in the proposed PV system mainly used for cooking and heating applications. Since the battery has not been used, selection of dc-dc converter is an important consideration of the PV system in standalone applications. In the proposed system converter is selected based on maximum power transfer theorem which is dependent on load resistance. Different load resistance is considered for maximum power point tracking (MPPT) with different converter topologies, and it has been observed that buck-boost converter is suitable for any load resistance connected in the PV system. An effort has been taken to suitably choosing the control variable which is the output signal of the maximum power point (MPP) tracker. Control variable which is dependent on inputs of MPP tracker is decided based on the stability of the system. Two MPP trackers are designed based on neural-network (NN) controller and perturb and observe (P&O) algorithm. The tracking capabilities of both NN controller and the P&O algorithm is compared with the variation of irradiation and found that tracking capability of NN controller is better than P&O method. The system is simulated using MATLAB/Simulink environment, and the results show that NN controller tracks MPP at a faster rate with reduced oscillation. [ABSTRACT FROM AUTHOR]