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Battery Capacity Estimation and Health Management of an Electric Vehicle Fleet

Anthony Barré 1, 2 Frédéric Suard 1 Mathias Gerard 2 Delphine Riu 3
1 LADIS - Laboratoire d'analyse des données et d'intelligence des systèmes
DM2I - Département Métrologie Instrumentation & Information : DRT/LIST/DM2I
2 LITEN - Laboratoire d'Innovation pour les Technologies des Energies Nouvelles et les nanomatériaux
3 G2ELab - Laboratoire de Génie Electrique de Grenoble
Abstract : This paper addresses the challenge of monitoring battery in fleets of electric vehicles (EV). The goal is to identify the different EV utilization modes, during real use, and to highlight the constraining conditions to manage battery health evolution. The other part of this study aims to build a battery capacity estimation model, permitting to estimate the remaining capacity of an EV during its real use. Finally, is explained a strategy to improve capacity estimates, based on the identified EV utilization modes.
Keywords : Battery charge measurement Temperature measurement Estimation error Electric vehicles battery management systems battery powered vehicles estimation theory secondary cells battery capacity estimation improvement electric vehicle fleet battery monitoring EV utilization modes constraining conditions battery health evolution management lithium-ion batteries
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Conference papers
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https://hal-cea.archives-ouvertes.fr/cea-01887971
Contributor : Marie-France Robbe <>
Submitted on : Thursday, October 4, 2018 - 3:57:16 PM
Last modification on : Sunday, June 27, 2021 - 3:27:56 AM

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CEA | CNRS | INSMI | TDS-MACS | UNIV-SAVOIE | DRT | LIST | LITEN | CEA-GRE | DM2I | G2ELAB | UGA | GS-COMPUTER-SCIENCE

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Anthony Barré, Frédéric Suard, Mathias Gerard, Delphine Riu. Battery Capacity Estimation and Health Management of an Electric Vehicle Fleet. 2014 IEEE Vehicle Power and Propulsion Conference (VPPC), Oct 2014, Coimbra, Portugal. pp.7007025, ⟨10.1109/VPPC.2014.7007025⟩. ⟨cea-01887971⟩

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