This paper presents high step-up DC to DC converter for low voltage sources like solar PV, fuel cells and battery banks. To achieve high voltage gain without large duty cycle operation, combination of coupled inductor and switched capacitor voltage doubler cells are used. By incorporating active clamp circuit, voltage spike due to the leakage inductance of the coupled inductor is alleviated and ZVS turn ON of the main and auxiliary switch is obtained. Due to the use of MOSFETs of low voltage rating and soft turn ON of the switches, conduction loss and switching losses are reduced. This improves the efficiency and power density of the converter. The proposed converter can achieve high voltage gain with reduced voltage stress on MOSFET switches and output diodes. Design and analysis of the proposed converter is carried out and finally a 500W experimental prototype is built to verify theoretical analysis.

A non-isolated soft switched integrated boost converter having high voltage gain is proposed for the module integrated PV systems, fuel cells and other low voltage energy sources. Here a bidirectional boost converter is integrated with a resonant voltage quadrupler cell to obtain higher voltage gain. The auxiliary switch of the converter, which is connected to the output port acts as an active clamp circuit. Hence ZVS (zero voltage switching) turn on of the MOSFET switches are achieved. Coupled inductor's leakage energy is recycled to the output port through this auxiliary switch. In the proposed converter, all the diodes of the quadrupler cell are turned off with ZCS (zero current switching). This considerably reduces the high frequency turn off losses and reverse recovery losses of the diodes. ZCS turn off of the diodes also remove the diode voltage ringing caused due to the interaction of the parasitic capacitance of the diodes and the leakage inductance of the coupled inductor. Hence to protect the diodes from the voltage spikes, snubbers are not required. The voltage stress on all the MOSFETs and diodes are lower. This helps to choose switches of low voltage rating (low RDS(ON )) and thus improve the efficiency. Design and mathematical analysis of the proposed converter are made. A 250W prototype of the converter is built to verify the performance.

The positive features of neural networks and fuzzy logic are combined together for the detection of stator inter-turn insulation and bearing wear faults in single-phase induction motor. The adaptive neural fuzzy inference systems (ANFISs) are developed for the detection of these two faults. These faults are created experimentally on a single-phase induction motor in the laboratory. The experimental data is generated for the five measurable parameters, viz, motor intakes current, speed, winding temperature, bearing temperature, and the noise of the machine. Earlier, the ANFIS fault detectors are trained for the two input parameters, i.e., speed and current, and the performance is tested. Later, the three remaining parameters are added and the five input ANFIS fault detector is trained and tested. It observed from the simulation results that the five input parameter system predicts more accurate results.Index Terms-Adaptive neural fuzzy inference systems (ANFISs), bearing wear, induction motor, winding insulation.

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