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Submodule Voltage Estimation Scheme in Modular Multilevel Converters with Reduced Voltage Sensors Based on Kalman Filter Approach

Lookup NU author(s): Dr Osama AbushafaORCiD, Dr Mohamed Dahidah, Dr Shady Gadoue, Dr Dave Atkinson



This is the authors' accepted manuscript of an article that has been published in its final definitive form by IEEE, 2018.

For re-use rights please refer to the publisher's terms and conditions.


This paper presents a new voltage estimation method for the submodule (SM) capacitor in a modular multilevel converter (MMC). The proposed method employs a Kalman filter (KF) algorithm to estimate the SM voltages of the converter. Compared with sensor-based methods, this scheme requires only one voltage sensor to achieve the voltage-balancing of the converter. This sensor is connected to the total arm voltage; the proposed algorithm requires also the switching patterns of each upper SM switch which are provided by the controller used without the need for extra sensors. The substantial reduction in the number of voltage sensors improves the system reliability and decreases its cost and complexity. Extensive simulation and experimental analyses carried out to validate the proposed estimation scheme under different conditions include steady-state analyses, the effect of variations in capacitance and inductance, of the impact of low carrier and effective switching frequency on the accuracy of the estimation, step changes to the load, and a range changes in DC voltage. The results obtained are experimentally verified using a single-phase MMC.

Publication metadata

Author(s): Abushafa O SH M, Dahidah MSA, Gadoue S, Atkinson D

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Industrial Electronics

Year: 2018

Volume: 65

Issue: 9

Pages: 7025-7035

Print publication date: 01/09/2018

Online publication date: 23/01/2018

Acceptance date: 27/12/2017

Date deposited: 06/01/2018

ISSN (print): 0278-0046

ISSN (electronic): 1557-9948

Publisher: IEEE


DOI: 10.1109/TIE.2018.2795519


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