Toggle Main Menu Toggle Search

Open Access padlockePrints

Real- Time Parameter Estimation of DC-DC Converters using a Self-tuned Kalman Filter

Lookup NU author(s): Dr Mohamed Ahmeid, Dr Matthew Armstrong, Dr Shady Gadoue, Dr Maher Al-Greer, Dr Petros Missailidis



To achieve high performance control of modern DC-DC converters, using direct digital design techniques, an accurate discrete model of the converter is necessary. In this paper, a new parametric system identification method, based on a Kalman filter (KF) approach is introduced to estimate the discrete model of a synchronous DC-DC buck converter. To improve the tracking performance of the proposed KF, an adaptive tuning technique is proposed. Unlike many other published schemes, this approach offers the unique advantage of updating the parameter vector coefficients at different rates. The proposed KF estimation technique is experimentally verified using a Texas Instruments TMS320F28335 microcontroller platform and synchronous step down DC-DC converter. Results demonstrate a robust and reliable real-time estimator. The proposed method can accurately identify the discrete coefficients of the DC-DC converter. This paper also validates the performance of the identification algorithm with time varying parameters; such as an abrupt load change. The proposed method demonstrates robust estimation with and without an excitation signal, which makes it very well suited for real-time power electronic control applications. Furthermore, the estimator convergence time is significantly shorter compared to many other schemes, such as the classical Exponentially weighted Recursive Least Square (ERLS) method.

Publication metadata

Author(s): Ahmeid M, Armstrong M, Gadoue S, Algreer M, Missailidis P

Publication type: Article

Publication status: Published

Journal: IEEE Transactions on Power Electronics

Year: 2017

Volume: 32

Issue: 7

Pages: 5666-5674

Print publication date: 01/07/2017

Online publication date: 07/09/2016

Acceptance date: 22/08/2016

Date deposited: 10/10/2016

ISSN (print): 0885-8993

ISSN (electronic): 1941-0107

Publisher: IEEE


DOI: 10.1109/TPEL.2016.2606417


Altmetrics provided by Altmetric