A LPV modeling of turbocharged spark-ignition automotive engine oriented to fault detection and isolation purposes

作者：Gagliardi Gianfranco^*; Tedesco Francesco; Casavola Alessandro

来源：Journal of the Franklin Institute, 2018, 355(14): 6710-6745.

DOI：10.1016/j.jfranklin.2018.06.038

This paper illustrates the derivation of a linear parameter varying (LPV) model approximation of a turbocharged Spark-Ignition (SI) automotive engine and its usage in designing a model-based fault detection and isolation (FDI) scheme. The LPV approximation is derived from a detailed nonlinear mathematical model of the engine on the basis of the well known Jacobian approach. The resulting LPV representation is then exploited for synthesizing a bank of LPV-FDI H-infinity/H_ Luenberger observers. Each observer is in charge of detecting a particular class of fault and is designed for having low sensitivity to all other exogenous inputs so as to allow an effective fault isolation. The adopted FDI scheme is gain-scheduled and exploits a set of engine variables, assumed to be measurable on-line, as a scheduling parameters. The goodness of the LPV approximation of the engine model and the effectiveness of the LPV-FDI architecture are demonstrated by several numerical simulations.

• 出版日期2018-9