01561nab a2200205 4500 20260520002832.0 260224s2010 xxu Automated model generation for hybrid vehicles optimization and control ene./feb. 2010 05/07/2010 ; 05/07/2010 18 p. ; 115-132 Transcripción del resumen del autor. 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). 1 Oil and Gas Science and Technology 65 ARTICULO Verdonck, N. 43452 Chasse, A. 41726 Pognant-Gros, P. 43453 171729 171729 0 0 0 0 239548 BAAB BAAB 2026-03-05 200046597 0 200046597 2026-03-05 15:14:08 2026-03-05 ARTICULO