Methodology for Design and Calibration of a Drift Compensation Method for Fuel-To-Air Ratio Estimation 2012-01-0717
Observers can be used for combining different information
sources, as fast models with slow but accurate sensors. For that, a
Kalman filter can be used for identifying the bias and cancelling
its variation during time. However, normal calibration procedure is
iterative and ad-hoc and this does not get optimal results.
Furthermore, the lack of enough accurate references make difficult
to estimate the best tuning, and more if the calibration pretends
to be an online procedure. For solving this, the paper presents a
novel calibration method for Kalman filter based on a Monte Carlo
analysis, simulating real conditions by means of statistical
distributions. This makes possible to create actual references for
estimating error metrics of the observer output. A previous
sensitivity study is presented for understanding the performance of
the algorithm under different conditions. And finally, adequacy of
the proposed method is demonstrated for the relative fuel-to-air
ratio estimate λ-₁ obtained from the secondary output of
an exhaust NOx sensor installed in a turbocharged diesel
engine.
Citation: Payri, F., Guardiola, C., Blanco-Rodriguez, D., Mazer, A. et al., "Methodology for Design and Calibration of a Drift Compensation Method for Fuel-To-Air Ratio Estimation," SAE Technical Paper 2012-01-0717, 2012, https://doi.org/10.4271/2012-01-0717. Download Citation
Author(s):
Francisco Payri, Carlos Guardiola, David Blanco-Rodriguez, Alexandre Mazer, Annabelle Cornette
Affiliated:
Universidad Politecnica de Valencia, PSA
Pages: 13
Event:
SAE 2012 World Congress & Exhibition
ISSN:
0148-7191
e-ISSN:
2688-3627
Related Topics:
Diesel / compression ignition engines
Calibration
Mathematical models
Statistical analysis
Sensors and actuators
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