Title :

Rule-Based Energy Management Strategy for a Parallel Hybrid Electric Vehicle Deduced from Dynamic Programming

Author(s) :

Pam, Abdoulaye [Auteur]
Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
Sherpa Engineering
Bouscayrol, Alain [Auteur]
Laboratoire d’Électrotechnique et d’Électronique de Puissance - ULR 2697 [L2EP]
Fiani, Philippe [Auteur]
Sherpa Engineering
Noth, Frederic [Auteur]
Sherpa Engineering

Conference title :

2017 IEEE Vehicle Power and Propulsion Conference (VPPC)

City :

Belfort

Country :

France

Start date of the conference :

2017-12-11

Book title :

2017 IEEE Vehicle Power and Propulsion Conference (VPPC)

Publisher :

IEEE

HAL domain(s) :

Sciences de l'ingénieur [physics]/Energie électrique

English abstract : [en]

To ensure the highest energy efficiency of Hybrid Electric Vehicles, optimizing their Energy Management Strategy (EMS) is required. Unfortunately, most of the methods for optimal EMS like Dynamic Programming (DP) cannot ...
Show more >To ensure the highest energy efficiency of Hybrid Electric Vehicles, optimizing their Energy Management Strategy (EMS) is required. Unfortunately, most of the methods for optimal EMS like Dynamic Programming (DP) cannot be used in real time. Rule-based EMS are well known to be easily usable in real time. The objective of this paper is to achieve a rule-based EMS of a parallel Hybrid Electric Vehicle, deduced from DP. In that aims, Energetic Macroscopic Representation of the powertrain is used to develop a backward model.Show less >

Language :

Anglais

Peer reviewed article :

Oui

Audience :

Internationale

Popular science :

Non

Collections :

• Laboratoire d'Électrotechnique et d'Électronique de Puissance (L2EP) - ULR 2697

Research team(s) :

Équipe Commande

Submission date :

2020-05-15T13:28:32Z
2022-03-10T13:00:18Z