Analysis of machine learning techniques for the intelligent diagnosis of Ni-MH battery cells

Juan P. Ortiz, Juan D. Valladolid, Cristian L. Garcia, Gina Novillo, Felipe Berrezueta

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Scopus citations
Original languageEnglish
Title of host publication2018 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538659359
ISBN (Print)9781538659359
DOIs
StatePublished - 5 Mar 2019
Event2018 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2018 - Ixtapa, Guerrero, Mexico
Duration: 14 Nov 201816 Nov 2018

Publication series

Name2018 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2018

Conference

Conference2018 IEEE International Autumn Meeting on Power, Electronics and Computing, ROPEC 2018
CountryMexico
CityIxtapa, Guerrero
Period14/11/1816/11/18

Bibliographical note

Funding Information:
This study has been supported by “Grupo de Investi-gación en Ingeniería del Transporte (GIIT)” in the “Reacondi-cionamiento de Baterías para Movilidad Alternativa” research proyect of Universidad Politecnica Salesiana.

Publisher Copyright:
© 2018 IEEE.

Copyright:
Copyright 2019 Elsevier B.V., All rights reserved.

Keywords

  • Classifier
  • Hybrid electric vehicle
  • Machine learning
  • Ni-MH

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