A Non-Linear Regression Technique to Estimate from Vibrational Engine Data the Instantaneous In-Cylinder Pressure Peak and Related Angular Position
Academic Article
Publication Date:
2016
abstract:
In this paper, a downsized twin-cylinder turbocharged spark-ignition
engine is experimentally investigated at test-bench in order to verify
the potential to estimate the peak pressure value and the related crank
angle position, based on vibrational data acquired by an accelerometer
sensor. Purpose of the activity is to provide the ECU of additional
information to establish a closed-loop control of the spark timing, on a
cycle-by-cycle basis. In this way, an optimal combustion phasing can
be more properly accomplished in each engine operating condition.
Engine behavior is firstly characterized in terms of average
thermodynamic and performance parameters and cycle-by-cycle
variations (CCVs) at high-load operation. In particular, both a spark
advance and an A/F ratio sweep are actuated. In-cylinder pressure data
are acquired by pressure sensors flush-mounted within the combustion
chamber of both cylinders. The Coefficient of Variation of the net
Indicated Mean Effective Pressure (CoVIMEP) and of in-cylinder peak
pressure (CoVp,max) are utilized to quantify the cyclic dispersion and
identify its dependency on combustion phasing and duration.
Vibrational data are provided by a non-intrusive accelerometer sensor
located on the head of cylinder #1. In particular, a proper processing
of the accelerometer signal is applied to build correlations able to
estimate with a relevant accuracy the cycle-by-cycle scattering of the
crank angle position and amplitude of the in-cylinder pressure peak,
as well as the related CoV. A maximum in-cylinder pressure error
below 2 bar and a maximum crank angle error below 1 degree was
obtained in most of data points
Iris type:
01.01 Articolo in rivista
Keywords:
ARMA (Auto Regressive Moving Average) model; Cyclic dispersion; vibration; downsized spark-ignition engine
List of contributors:
Marchitto, Luca; Bozza, Fabio; Iacobacci, Arturo; Siano, Daniela; Valentino, Gerardo
Published in: