Automated Model Generation for Hybrid Vehicles Optimization and Control - IFPEN - IFP Energies nouvelles Access content directly
Journal Articles Oil & Gas Science and Technology - Revue d'IFP Energies nouvelles Year : 2010

Automated Model Generation for Hybrid Vehicles Optimization and Control

N. Verdonck
  • Function : Author
A. Chasse
  • Function : Author
A. Sciarretta
  • Function : Correspondent author

Abstract

Systematic optimization of modern powertrains, and hybrids in particular, requires the representation of the system by means of Backward Quasistatic Models (BQM). In contrast, the models used in realistic powertrain simulators are often of the Forward Dynamic Model (FDM) type. The paper presents a methodology to derive BQM’s of modern powertrain components, as parametric, steady-state limits of their FDM counterparts. The parametric nature of this procedure implies that changing the system modeled does not imply relaunching a simulation campaign, but only adjusting the corresponding parameters in the BQM. The approach is illustrated with examples concerning turbocharged engines, electric motors, and electrochemical batteries, and the influence of a change in parameters on the supervisory control of an hybrid vehicle is then studied offline, in co-simulation and on an HiL test bench adapted to hybrid vehicles (HyHiL).
Fichier principal
Vignette du fichier
ogst09044.pdf (3.16 Mo) Télécharger le fichier
Origin : Publication funded by an institution
Loading...

Dates and versions

hal-01937494 , version 1 (28-11-2018)

Identifiers

Cite

N. Verdonck, A. Chasse, P. Pognant-Gros, A. Sciarretta. Automated Model Generation for Hybrid Vehicles Optimization and Control. Oil & Gas Science and Technology - Revue d'IFP Energies nouvelles, 2010, 65 (1), pp.115-132. ⟨10.2516/ogst/2009064⟩. ⟨hal-01937494⟩

Collections

IFP OGST
9 View
71 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More