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Advances on System Identification Techniques for DC-DC Switch Mode Power Converter Applications

Lookup NU author(s): Dr Maher Al-Greer, Dr Matthew Armstrong, Dr Mohamed Ahmeid, Professor Damian Giaouris

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This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2019.

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Abstract

IEEE System identification is fundamental in many recent state-of-the-art developments in power electronic such as modelling, parameter tracking, estimation, self-tuning and adaptive control, health monitoring, and fault detection. Therefore, this paper presents a comprehensive review of parametric, non-parametric, and dual hybrid system identification for DC-DC Switch Mode Power Converter (SMPC) applications. The paper outlines the key challenges inherent with system identification for power electronic applications; speed of estimation, computational complexity, estimation accuracy, tracking capability, and robustness to disturbances and time varying systems. Based on literature in the field, modern solutions to these challenges are discussed in detail. Furthermore, this paper reviews and discusses the various applications of system identification for SMPCs; including health monitoring and fault detection.

Publication metadata

Author(s): Al-Greer M, Armstrong M, Ahmeid M, Giaouris D

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Power Electronics

Year: 2019

Volume: 34

Issue: 7

Pages: 6973 - 6990

Print publication date: 01/07/2019

Online publication date: 10/10/2018

Acceptance date: 02/04/2018

Date deposited: 31/10/2018

ISSN (print): 0885-8993

ISSN (electronic): 1941-0107

Publisher: IEEE

URL: https://doi.org/10.1109/TPEL.2018.2874997

DOI: 10.1109/TPEL.2018.2874997

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