Online Identification of Battery Internal Resistance under extreme Temperatures
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Online Identification of Battery Internal Resistance under extreme Temperatures |
| Type de publication | Conference Paper |
| Year of Publication | 2020 |
| Auteurs | Noura N, Cos K, Boulon L, Jemei S |
| Conference Name | 2020 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC) |
| Publisher | IEEE; Ayuntamiento Gijon; Gijon Convent Bur; Univ Oviedo; IEEE SBC; Mg Lab; Univ Oviedo; IEEE VTS Spanish Chapter |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-7281-8959-8 |
| Mots-clés | Battery model, Internal Resistance, Recursive Least Square, State of Health |
| Résumé | Lithium ion batteries are the key component in electric vehicles and hybrid electric vehicles. Monitoring adequately this component can he very challenging due to its nonlinear electrochemical behavior. Several factors, such as the temperature and the aging, impact the battery's performances and its models' parameters. In order to make a good use of this component and to ensure its safety it is necessary to keep track of its models' parameters in real time. This paper provides an accurate online identification process to estimate the battery internal resistance under extreme temperatures. This online identification process is validated through experimental testing. |
| DOI | 10.1109/VPPC49601.2020.9330928 |