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LCL Filter Startup Diagnostics for an Active Front End Converter

Agrawal, Neeraj and John, Vinod (2017) LCL Filter Startup Diagnostics for an Active Front End Converter. In: 2016 IEEE INTERNATIONAL CONFERENCE ON POWER ELECTRONICS, DRIVES AND ENERGY SYSTEMS (PEDES) , DEC 14-17, 2016, Trivandrum, INDIA.

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Official URL: http://doi.org/10.1109/PEDES.2016.7914471

Abstract

Reliability of Active Front End (AFE) converter can be improved if converter faults can be identified before startup. Startup diagnostics of the LCL filter can be an useful tool to accomplish this. An algorithm based on Fast Fourier Transform (FFT) of the filter step response is shown to be able to detect variation of filter components. This is extended to consider conditions of short circuit and open circuit of filter components. This method can identify failed components in a LCL filter before operating the converter, which otherwise may lead to undesirable operation. Analytical expressions are derived for the frequency spectrum of the LCL filter during step excitation using continuous Fourier Transform and Discrete Fourier Transform (DFT). A finite state machine Finite State Machine (FSM) based algorithm is use to sequence the startup diagnostics before commencing normal operation of the power converter. It is shown that the additional computational resource required to perform the diagnostic algorithm is small when compared with the overall inverter control program. The diagnostic functions can be readily implemented in advanced digital controllers that are available today. The spectral analysis is supported by simulations and experimental results which validate the proposed method.

Item Type: Conference Proceedings
Additional Information: Copy right for this article belongs to the IEEE International Conference on Power Electronics, Drives and Energy Systems (PEDES), Trivandrum, INDIA, DEC 14-17, 2016
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Depositing User: Id for Latest eprints
Date Deposited: 23 Sep 2017 05:01
Last Modified: 23 Sep 2017 05:01
URI: http://eprints.iisc.ac.in/id/eprint/57882

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