Predictive Energy Management for Hybrid Vehicles based on Driving Cycle Recognition
| Affiliation auteurs | !!!! Error affiliation !!!! |
| Titre | Predictive Energy Management for Hybrid Vehicles based on Driving Cycle Recognition |
| Type de publication | Conference Paper |
| Year of Publication | 2017 |
| Auteurs | Joud L, Chrenko D, Keromnes A, Da Silva R, Le Moyne L |
| Conference Name | 2017 IEEE VEHICLE POWER AND PROPULSION CONFERENCE (VPPC) |
| Publisher | IEEE; Alstom; Sonceboz; Femto st Sci & Technologies; FC Lab Res; IEEE VTS; Megevh; Univ Bourgogne Franche Comte; Univ Franche Comte; Univ Technologie Belfort Montbeliard; IUT Belfort Montbeliard; UFR STGI; Univ Technologie Belfort Montbeliard, Departement |
| Conference Location | 345 E 47TH ST, NEW YORK, NY 10017 USA |
| ISBN Number | 978-1-5386-1317-7 |
| Mots-clés | cycle recognitions, Dynamic programming, Energy management, plug-in hybrid vehicle, series hybrid vehicle |
| Résumé | This article presents a novel approach to design an optimum energy management for a series plug-in hybrid electric vehicle based on driving cycle recognition. Thanks to an intensive study of driver habits, an important part of cycles is predictable. Optimized energy management can be developed for representative cycles via DP. Those results can be applied to the same cycle with slight adaptations thereafter with quality factors above 98%. |