000			01561nab a2200205 4500
005			20260520002832.0
008			260224s2010 xxu
245	0	0	_aAutomated model generation for hybrid vehicles optimization and control
260			_a _b _cene./feb. 2010
270			_a05/07/2010 ; 05/07/2010
300			_a18 p. ; 115-132
520			_aTranscripción 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).
581			_a1
773	0		_tOil and Gas Science and Technology _g65
942			_cARTICULO
100	1		_aVerdonck, N. _943452
100	1		_aChasse, A. _941726
100	1		_aPognant-Gros, P. _943453
999			_c171729 _d171729