Title: | Identification of thermal model of power module using expectation-maximization algorithm |
Authors: | Ševčík, Jakub Šmídl, Václav Votava, Martin |
Citation: | ŠEVČÍK, J., ŠMÍDL, V., VOTAVA, M. Identification of thermal model of power module using expectation-maximization algorithm. In: Proceedings : IECON 2019 : 45th Annual Conference of the IEEE Industrial Electronics Society. Piscataway: IEEE, 2019. s. 1-7. ISBN 978-1-72814-878-6. |
Issue Date: | 2019 |
Publisher: | IEEE |
Document type: | konferenční příspěvek conferenceObject |
URI: | http://hdl.handle.net/11025/36803 |
ISBN: | 978-1-72814-878-6 |
Keywords in different language: | thermal network;state space model;system identification;expectation-maximization algorithm;power semiconductor module |
Abstract: | Prediction of junction temperatures in power semiconductor modules is essential to improve reliability of the device and prevent module failures due to thermal stress. Lumped parameter network is a popular approach for temperature modeling. Calibration of the thermal model is based on thermal measurements of the junction temperatures that are difficult to obtain. We aim to combine the knowledge of internal model structure and as little measurements as possible. Specifically, we use a state space thermal model with structure determined by the module layout, and propose to use the Expectation-Maximization algorithm from that can utilize data from different incomplete experiments. The identification procedure is introduced in detail in this paper and the applicability of the proposed approach is demonstrated on simulated and experimental data. |
Rights: | Plný text je přístupný v rámci univerzity přihlášeným uživatelům. © IEEE |
Appears in Collections: | Konferenční příspěvky / Conference papers (KEV) Konferenční příspěvky / Conference papers (RICE) OBD |
Files in This Item:
File | Size | Format | |
---|---|---|---|
Sevcik_paper_submitted.pdf | 3,49 MB | Adobe PDF | View/Open Request a copy |
Please use this identifier to cite or link to this item:
http://hdl.handle.net/11025/36803
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.