relation: https://khub.utp.edu.my/scholars/15445/
title: Performance Analysis of High Gain Z-Source DC-DC Boost Converter
creator: Kumar, R.
creator: Kannan, R.
creator: Nor, N.B.M.
description: With the increasing trend in energy demand, researchers are moving towards renewable energy sources (RESs). However, RESs such as, fuel cell or photovoltaic panel offers low output voltage, and it is essential to step-up this low voltage before connecting to the grid or an inverter in two stage power conversion system. The Z-network converter could be used for DC-DC conversion to enhance renewable energy sources voltage. however, boost capabilities of conventional Z-source DC-DC converter (ZSC) are limited, and utilization of higher part count makes it bulky and expensive. In this paper, a new design of ZSC is presented that offers higher gain at smaller duty cycle. Besides, the performance of proposed converter is analyzed with parasitic parameters to validate the proposed design. Moreover, the PI controller is designed for the proposed converter to maintain the constant output voltage to the desired value. The values of proportional and integral (P and I) terms are calculated based on the PID tuning method and the transfer function of the proposed system is achieved using the system identification toolbox (SIT) in MATLAB. Moreover, The performance of proposed converter is compared with recently proposed Hybrid ZSC and conventional ZSC. The simulation studies for the proposed design, conventional ZSC, and Hybrid ZSC are carried out in Simulink software and the outcome verified the superiority of the proposed converter over conventional converters. © 2021 IEEE.
publisher: Institute of Electrical and Electronics Engineers Inc.
date: 2021
type: Conference or Workshop Item
type: PeerReviewed
identifier:   Kumar, R. and Kannan, R. and Nor, N.B.M.  (2021) Performance Analysis of High Gain Z-Source DC-DC Boost Converter.  In: UNSPECIFIED.     
relation: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85124171779&doi=10.1109%2fICIAS49414.2021.9642507&partnerID=40&md5=91993c57e967f3e7a64a1d46710bd5a6
relation: 10.1109/ICIAS49414.2021.9642507
identifier: 10.1109/ICIAS49414.2021.9642507