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   Improved performance of Kalman filter for junction temperature estimation with Autocovariance Least-Squares method   [View] 
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 Author(s)   Diego VELAZCO, Maxime VALLE, François WALLART, Guy CLERC, Emmanuel BOUTLEUX 
 Abstract   Junction temperature estimation is a crucial topic for assessing the state-of-health of semiconductors. In this work a measurement board provides an initial estimation of the temperature. Afterwards, a Kalman filter improves this estimation. The ALS method is used for obtaining an optimal performance of the Kalman filter. Finally, the proposed methodology is deployed in an experimental setup and the temperature estimation is validated with the help of a real measurement through fiber optics sensors. 
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Filename:0412-epe2023-full-11074544.pdf
Filesize:1015 KB
 Type   Members Only 
 Date   Last modified 2023-09-24 by System