A Review on Matrix Converter Topologies for Adjustable Speed Drives
Maheswari K.T1, Bharanikumar R2, Bhuvaneswari S.3

1Maheswari K.T, Department of EEE, Bannari Amman Institute of Technology, Sthyamangalam (Tamil Nadu), India.
2Bharanikumar R, Department of EEE, Bannari Amman Institute of Technology, Sthyamangalam (Tamil Nadu), India.
3Bhuvaneswari S, Department of EEE, Bannari Amman Institute of Technology, Sthyamangalam (Tamil Nadu), India.
Manuscript received on 07 March 2019 | Revised Manuscript received on 20 March 2019 | Manuscript published on 30 March 2019 | PP: 53-57 | Volume-8 Issue-5, March 2019 | Retrieval Number: D2830028419/19©BEIESP
Open Access | Ethics and Policies | Cite | Mendeley | Indexing and Abstracting
© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: A detailed review on matrix converter circuits for adjustable speed drive applications has been presented in this paper. The power converter that is made up of a group of nine switches used to link three phase ac source to the load is called AC to AC Matrix Converter. Matrix Converter is capable to transform input with constant amplitude and frequency to three phase output with variable amplitude and variable frequency, as it is able to produce any frequency at the output as integer multiple of input. The attractive characteristics of Direct matrix converter are intrinsic four quadrant operation, high power factor at the input side, no intermediate capacitor, high regenerative capability, increased power density, light weight and reliable. However, some of the striking feature of these converters has been under research for the last few decades. The use of various topologies of matrix converter, and its PWM methods to get desired performance in adjustable speed drives have been discussed in this paper.
Keyword: Direct Matrix Converter, Four Quadrant Operation, PWM Methods, Regenerative Capability.
Scope of the Article: Probabilistic Models and Methods