An Online Identification based Energy Management Strategy for a Fuel Cell Hybrid Electric Vehicle
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | An Online Identification based Energy Management Strategy for a Fuel Cell Hybrid Electric Vehicle |
| Type de publication | Conference Paper |
| Year of Publication | 2019 |
| Auteurs | Noura N, Boulon L, Jemei S |
| Conference Name | 2019 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC) |
| Publisher | IEEE; Bach Khoa; CTI; Univ Tokyo; IEEE VTS |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-7281-1249-7 |
| Mots-clés | battery, EMR, Recursive Least Square, state of charge, State of Health |
| Résumé | This paper aims to present an accurate Energy Management Strategy (EMS) for a Fuel Cell Hybrid Electric Vehicle (FC-HEV). Batteries and FC performances are constantly changing with aging, temperature and so on. In order to ensure the accuracy of the EMS the parameters of those models are constantly updated thanks to an online identification. Adaptive filtering, based on Recursive Least Square (RLS) algorithm, is used to estimate the State of Health (SOH) and the State of Charge (SOC) of the battery in one hand. On the other hand The RLS algorithm estimates the polarization curve of the Fuel Cell. The impact of those estimated parameters on the EMS is shown through simulation. |