Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries

Kacper Cierpiak; Marta Szczerska; Paweł Wierzba

doi:10.4302/plp.v15i3.1207

Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries

Abstract

Optical fiber sensorsusing low-coherence interferometry require processing ofthe output spectrum or interferogramto quickly and accurately determine the instantaneous value of the measured quantity, such as temperature.Methods based on machine learning are a good candidate for this application. The application of four such methods in an optical fiber temperature sensoris demonstrated.Using aZnO-coated sensing interferometer and spectral detection,the sensor is intended for monitoring lithium-ion rechargeable batteries. While the performance of all methods was good, some of them seem to be better suited for this application

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Articles

Type:

artykuły w czasopismach

Published in:

Photonics Letters of Poland no. 15, pages 36 - 38,
ISSN: 2080-2242

Language:

English

Publication year:

2023

Bibliographic description:

Cierpiak K., Szczerska M., Wierzba P.: Application of fiber optic sensors using Machine Learning algorithms for temperature measurement of lithium-ion batteries// Photonics Letters of Poland -,iss. 3 (2023), s.36-38

DOI: