Artificial Neural Network based DC-link capacitance estimation in a diode-bridge front-end inverter system

Hammam Soliman, Ibrahim Abdelsalam, Huai Wang, Frede Blaabjerg

    Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

    35 Scopus citations

    Abstract

    In modern design of power electronic converters, reliability of DC-link capacitors is an essential aspect to be considered. The industrial field have been attracted to the monitoring of their health condition and the estimation of their ageing process status. The existing condition monitoring methods suffer from shortcomings such as, low estimation accuracy, extra hardware, and increased cost. Therefore, development of new condition monitoring methodologies that are based on advanced software algorithms could be the way out of the aforementioned challenges and shortcomings. In this paper, a proposed software condition monitoring methodology based on Artificial Neural Network (ANN) algorithm is presented. Matlab software is used to train and generate the proposed ANN. The proposed methodology estimates the capacitance of the DC-link capacitor in a three phase front-end diode bridge AC/DC/AC converter. The estimation is based on the usage of single phase output current and dc-link voltage ripple. The impact of training data type, source and amount are also investigated for estimation accuracy analysis. Experimental validation of the proposed method is also conducted.

    Original languageBritish English
    Title of host publication2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia, IFEEC - ECCE Asia 2017
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages196-201
    Number of pages6
    ISBN (Electronic)9781509051571
    DOIs
    StatePublished - 25 Jul 2017
    Event3rd IEEE International Future Energy Electronics Conference and ECCE Asia, IFEEC - ECCE Asia 2017 - Kaohsiung, Taiwan, Province of China
    Duration: 3 Jun 20177 Jun 2017

    Publication series

    Name2017 IEEE 3rd International Future Energy Electronics Conference and ECCE Asia, IFEEC - ECCE Asia 2017

    Conference

    Conference3rd IEEE International Future Energy Electronics Conference and ECCE Asia, IFEEC - ECCE Asia 2017
    Country/TerritoryTaiwan, Province of China
    CityKaohsiung
    Period3/06/177/06/17

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