Real-Time Energy Management of Parallel ...
Type de document :
Article dans une revue scientifique: Article original
DOI :
URL permanente :
Titre :
Real-Time Energy Management of Parallel Hybrid Electric Vehicles Using Linear Quadratic Regulation
Auteur(s) :
Nguyễn, Bảo-Huy [Auteur]
Trovão, João Pedro F. [Auteur]
German, Ronan [Auteur]
Laboratoire d'Électrotechnique et d'Électronique de Puissance (L2EP) - ULR 2697
Bouscayrol, Alain [Auteur]
Laboratoire d'Électrotechnique et d'Électronique de Puissance (L2EP) - ULR 2697
Trovão, João Pedro F. [Auteur]
German, Ronan [Auteur]
![refId](/themes/Mirage2//images/idref.png)
Laboratoire d'Électrotechnique et d'Électronique de Puissance (L2EP) - ULR 2697
Bouscayrol, Alain [Auteur]
![refId](/themes/Mirage2//images/idref.png)
Laboratoire d'Électrotechnique et d'Électronique de Puissance (L2EP) - ULR 2697
Titre de la revue :
Energies
Nom court de la revue :
Energies
Numéro :
13
Pagination :
5538
Éditeur :
MDPI AG
Date de publication :
2020-10-22
ISSN :
1996-1073
Mot(s)-clé(s) en anglais :
energy management strategy (EMS)
parallel hybrid electric vehicle (HEV)
energetic macroscopic representation (EMR)
hardware-in-the-loop (HIL)
parallel hybrid electric vehicle (HEV)
energetic macroscopic representation (EMR)
hardware-in-the-loop (HIL)
Discipline(s) HAL :
Sciences de l'ingénieur [physics]
Résumé en anglais : [en]
Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong ...
Lire la suite >Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.Lire moins >
Lire la suite >Optimization-based methods are of interest for developing energy management strategies due to their high performance for hybrid electric vehicles. However, these methods are often complicated and may require strong computational efforts, which can prevent them from real-world applications. This paper proposes a novel real-time optimization-based torque distribution strategy for a parallel hybrid truck. The strategy aims to minimize the engine fuel consumption while ensuring battery charge-sustaining by using linear quadratic regulation in a closed-loop control scheme. Furthermore, by reformulating the problem, the obtained strategy does not require the information of the engine efficiency map like the previous works in literature. The obtained strategy is simple, straightforward, and therefore easy to be implemented in real-time platforms. The proposed method is evaluated via simulation by comparison to dynamic programming as a benchmark. Furthermore, the real-time ability of the proposed strategy is experimentally validated by using power hardware-in-the-loop simulation.Lire moins >
Langue :
Anglais
Audience :
Internationale
Vulgarisation :
Non
Établissement(s) :
Université de Lille
Centrale Lille
Arts et Métiers Sciences et Technologies
Junia HEI
Centrale Lille
Arts et Métiers Sciences et Technologies
Junia HEI
Équipe(s) de recherche :
Équipe Commande
Date de dépôt :
2023-02-02T14:28:08Z
2023-02-07T15:20:36Z
2024-01-04T19:38:51Z
2023-02-07T15:20:36Z
2024-01-04T19:38:51Z
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