My Account | Careers | Downloads | Blog

PROJECT TITLE :

Novel Topologies for Symmetric, Asymmetric, and Cascade Switched-Diode Multilevel Converter With Minimum Number of Power Electronic Components (2014)

ABSTRACT :

In this paper, novel topologies for symmetric, asymmetric, and cascade switched-diode multilevel converter are proposed, which can produce many levels with minimum number of Power Electronic switches, gate driver circuits, power diodes, and dc voltage sources. The number of required Power Electronic switches against required voltage levels is a very important factor in designing of multilevel converter, because switches define the reliability, circuit size, cost, installation area, and control complexity. For asymmetric and cascade converter, new algorithms for determination of dc voltage sources values are presented. To produce maximum number of levels at the output voltage, the proposed cascade topology is optimized for different goals, such as the minimization of the number of Power Electronic switches, gate driver circuits, power diodes, dc voltage sources, and blocking voltage on switches. Comparison of the results of various multilevel converters will be investigated to reflect the merits of the presented topologies. The operations of the proposed multilevel converters have been analyzed with the experimental and simulation results for different topologies. Verification of the analytical results is done using MATLAB simulation.


Did you like this research project?

To get this research project Guidelines, Training and Code... Click Here

PROJECT TITLE : Novel Secure Outsourcing of Modular Inversion for Arbitrary and Variable Modulus ABSTRACT: In the fields of cryptography and algorithmic number theory, modular inversion is regarded as one of the operations that
PROJECT TITLE : A Novel Blockchain Based Secured and QoS Aware IoT Vehicular Network in Edge Cloud Computing ABSTRACT: An IoT (Internet of Things)-based vehicular ad-hoc network and a software-defined network are the two components
PROJECT TITLE : Progressive Self-Supervised Clustering With Novel Category Discovery ABSTRACT: Clustering is one of the most classical methods used to analyze data structures in machine learning and pattern recognition at the
PROJECT TITLE : Large-Scale Affine Matrix Rank Minimization With a Novel Nonconvex Regularizer ABSTRACT: The goal of low-rank minimization is to recover a matrix with the lowest possible rank while still satisfying the constraints
PROJECT TITLE : A Novel Discriminative Dictionary Pair Learning Constrained by Ordinal Locality for Mixed Frequency Data Classification ABSTRACT: One of the challenges that classification must overcome is the fact that the data

Ready to Complete Your Academic MTech Project Work In Affordable Price ?

Project Enquiry