Turbocharged spark ignition engine for automotive racing have a long and controversial history. From the times of high torque at all cost, to the actual F1 era of maximum efficiency. However turbocharging and turbocoumpounding basic concepts have not changed. It is surprising that, through the years, the same identical errors are repeated. Turbocharger (TC) unit design is a highly optimized task, that requires good concepts, good mathematical models, lots of experimental data and a very good optimization. Performances vary completely with design choices, with big differences between even close solutions. Present software for mathematical modeling of performances are far from accurate and should be corrected with experimental data to obtain effective results. Genetic Algorithms are to be used as optimization method to evaluate the best design solution. Even minor errors in design choices result in large penalties on performance.

Turbocharging and turbocompounding optimization in automotive racing / L. Piancastelli; L. Frizziero. - In: JOURNAL OF ENGINEERING AND APPLIED SCIENCES. - ISSN 1819-6608. - STAMPA. - 9:11(2014), pp. 2192-2199.

Turbocharging and turbocompounding optimization in automotive racing

PIANCASTELLI, LUCA;FRIZZIERO, LEONARDO
2014

Abstract

Turbocharged spark ignition engine for automotive racing have a long and controversial history. From the times of high torque at all cost, to the actual F1 era of maximum efficiency. However turbocharging and turbocoumpounding basic concepts have not changed. It is surprising that, through the years, the same identical errors are repeated. Turbocharger (TC) unit design is a highly optimized task, that requires good concepts, good mathematical models, lots of experimental data and a very good optimization. Performances vary completely with design choices, with big differences between even close solutions. Present software for mathematical modeling of performances are far from accurate and should be corrected with experimental data to obtain effective results. Genetic Algorithms are to be used as optimization method to evaluate the best design solution. Even minor errors in design choices result in large penalties on performance.
2014
Turbocharging and turbocompounding optimization in automotive racing / L. Piancastelli; L. Frizziero. - In: JOURNAL OF ENGINEERING AND APPLIED SCIENCES. - ISSN 1819-6608. - STAMPA. - 9:11(2014), pp. 2192-2199.
L. Piancastelli; L. Frizziero
File in questo prodotto:
Eventuali allegati, non sono esposti

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/396678
 Attenzione

Attenzione! I dati visualizzati non sono stati sottoposti a validazione da parte dell'ateneo

Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 43
  • ???jsp.display-item.citation.isi??? ND
social impact