Computation of eco-driving cycles for Hybrid Electric Vehicles: Comparative analysis - Université d'Orléans Accéder directement au contenu
Article Dans Une Revue Control Engineering Practice Année : 2018

Computation of eco-driving cycles for Hybrid Electric Vehicles: Comparative analysis

Résumé

In this paper, the calculation of eco-driving cycles for a Hybrid Electric Vehicle (HEV), using Dynamic Programming (DP), is investigated from the solving method complexity viewpoint. The study is based on a comparative analysis of four optimal control problems formulated using distinct levels of modeling. Starting with three state dynamics (vehicle position and speed, battery state-of-charge) and three control variables (engine and electric machine torque, gear-box ratio), the number of state variables is reduced to two in a first simplification. The other two simplifications are based on decou-pling the optimization of the control variables into two steps: an eco-driving cycle is calculated supposing that the vehicle is propelled only by the engine. Then, assuming that the vehicle follows the eco-driving cycle calculated in the first step, an off-line energy management strategy (torque split) for an HEV is calculated to split the requested power at the wheels between the electric source and the engine. As is shown, the decreased complexity and the * Corresponding author. decoupling optimization lead to a sub-optimality in fuel economy while the computation time is noticeably reduced. Quantitative results are provided to assess these observations.
Fichier principal
Vignette du fichier
2018CEP_Maamriagilletcolin.pdf (653.91 Ko) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01826784 , version 1 (29-06-2018)

Identifiants

Citer

Djamaleddine Maamria, Kristan Gillet, Guillaume Colin, Yann Chamaillard, Cédric Nouillant. Computation of eco-driving cycles for Hybrid Electric Vehicles: Comparative analysis. Control Engineering Practice, 2018, 71, pp.44-52. ⟨10.1016/j.conengprac.2017.10.011⟩. ⟨hal-01826784⟩
392 Consultations
488 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More