Lithium-ion battery remaining useful life prediction

dc.contributor.advisor	Ceberio Uribe, Josu
dc.contributor.advisor	Ayerbe Olano, Elixabete
dc.contributor.author	Larrarte Lizarralde, Beñat
dc.contributor.other	Máster Universitario en Ingeniería Computacional y Sistemas Inteligentes
dc.contributor.other	Konputazio Ingeniaritza eta Sistema Adimentsuak Unibertsitate Masterra
dc.date.accessioned	2022-12-23T10:09:45Z
dc.date.available	2022-12-23T10:09:45Z
dc.date.issued	2022-12-23
dc.identifier.uri	http://hdl.handle.net/10810/58982
dc.description.abstract	Lithium-Ion Battery Remaining Useful Life Prediction work consists of an initial approach to battery life prediction using Severson dataset and data-driven LSTM-based RUL predictive methods. Although the memory is written in English, the presentation will be presented in Spanish.	es_ES
dc.language.iso	eng	es_ES
dc.rights	info:eu-repo/semantics/openAccess
dc.subject	time series forecasting	es_ES
dc.subject	lithium-ion batteries
dc.subject	remaining useful life
dc.title	Lithium-ion battery remaining useful life prediction	es_ES
dc.type	info:eu-repo/semantics/masterThesis
dc.date.updated	2021-06-14T13:07:33Z
dc.language.rfc3066	es
dc.rights.holder	© 2022, el autor
dc.contributor.degree	Máster Universitario en Ingeniería Computacional y Sistemas Inteligentes
dc.contributor.degree	Konputazio Ingeniaritza eta Sistema Adimentsuak Unibertsitate Masterra
dc.identifier.gaurregister	114083-836230-09	es_ES
dc.identifier.gaurassign	116838-836230	es_ES