Development and validation of hierarchical models for the design of engine control strategies (Articolo in rivista)

Type
Label
  • Development and validation of hierarchical models for the design of engine control strategies (Articolo in rivista) (literal)
Anno
  • 1997-01-01T00:00:00+01:00 (literal)
Alternative label
  • Arsia I., Gambino M. 1, Pianese C., Rizzo G. (1997)
    Development and validation of hierarchical models for the design of engine control strategies
    (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
  • Arsia I., Gambino M. 1, Pianese C., Rizzo G. (literal)
Pagina inizio
  • 397 (literal)
Pagina fine
  • 408 (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
  • 32 (literal)
Note
  • ISI Web of Science (WOS) (literal)
Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
  • 1) Istituto Motori, CNR, Napoli. (literal)
Titolo
  • Development and validation of hierarchical models for the design of engine control strategies (literal)
Abstract
  • The development of mathematical models for the design of controlstrategies for spark ignition automotive engines is described. The objectiveof the models, used for both simulation and optimization analysis, is theprediction of the effects of control strategies on fuel consumption andemissions of a vehicle over arbitrary driving cycles. In order to achievethe best compromise between precision, experimental costs, computationaltime and flexibility, a mixed modelling approach is used, withphenomenological and input-output models integrated within a hierarchicalsystem. Mean value models have been used to describe the most significant dynamiceffects: (i) air flow. (ii) two phases fuel flow in the intake manifold, and (iii) thermal flow in the cylinder walls. Stochastic effects due to sensorsand actuators can be also predicted. Two-zone and multizone thermodynamic models for the prediction ofpressure cycle sub-models for engine emissions (HC, CO, and NOx) and mechanical losses have been developed. Experimentaldesign techniques are also under development to optimize the interactionsbetween experimental analysis and models. Most of the models have beenintegrated in a computer code, used by a major automotive supplier. (literal)
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