Identification of Stochastic Models for Cyclic Variations from Measured Pressure Data

Paper #:
  • 970060

Published:
  • 1997-02-24
Citation:
Peyton Jones, J., Landsborough, K., and Roberts, J., "Identification of Stochastic Models for Cyclic Variations from Measured Pressure Data," SAE Technical Paper 970060, 1997, https://doi.org/10.4271/970060.
Pages:
19
Abstract:
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.
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