Identification of Stochastic Models for Cyclic Variations from Measured Pressure Data University of Sussex

Format:

Conference/Event

Author/Creator:

Peyton Jones, James C., author.

Conference Name:

International Congress & Exposition (1997-02-24 : Detroit, Michigan, United States)

Language:

English

Physical Description:

1 online resource

Place of Publication:

Warrendale, PA SAE International 1997

Summary:

A stochastic model for the entire pressure-time history of cycle-by-cycle cylinder pressure variations is obtained by fitting simple parametric models of cylinder pressure development to 506 cycles of continuous experimental data taken at four operating conditions. The cyclic variation is therefore encapsulated in a sequence of cyclically varying model parameters whose statistical properties then complete the stochastic description. Different model forms, (including computationally efficient linearised models), are compared for their degree of fit, and for the ease with which the statistics of the identified parameters can be defined. This approach, which typically accounts for 80-90% of the rms cyclic pressure variation, provides a more complete quantification of the phenomena than previously available, and a basis for simulating statistically identical pressure traces

Notes:

Vendor supplied data

Publisher Number:

970060

Access Restriction:

Restricted for use by site license