Back to Search Start Over

LED junction temperature prediction using machine learning techniques

Authors :
Carlo Porcaro
Francesco G. Della Corte
Massimo Merenda
Merenda, M.
Porcaro, C.
Della Corte, F. G.
Source :
2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON).
Publication Year :
2020
Publisher :
IEEE, 2020.

Abstract

Light Emitting Diodes (LEDs) are the longest lasting source of artificial illumination whose duration can exceed 50.000 continuous working hours. Nevertheless, they show a gradual reduction of the luminous flux due to the increase of the device temperature. In this work, a Machine Learning algorithm will be introduced and discussed, able to predict the junction temperature value of a LED in real-time while connected in the end-user circuit, taking into account current and voltage flowing in the device and, further, the actual model and aging of the LED. The algorithm was implemented on a microcontroller, showing the feasibility of performing edge machine learning on tiny yet powerful devices.

Details

Database :
OpenAIRE
Journal :
2020 IEEE 20th Mediterranean Electrotechnical Conference ( MELECON)
Accession number :
edsair.doi.dedup.....244b0c3e29864ab411315912b8b4966b
Full Text :
https://doi.org/10.1109/melecon48756.2020.9140539