Your Selections

Langthaler, Peter
Show Only


File Formats

Content Types








   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

Virtual Sensor Design of Particulate and Nitric Oxide Emissions in a DI Diesel Engine

Institute for Design and Control of Mechatronical Systems, Johannes Kepler University Linz-Daniel Alberer, Luigi del Re, Stephan Winkler, Peter Langthaler
Published 2005-09-11 by Consiglio Nazionale delle Ricerche in Italy
As a physical description of the emissions of a specific engine is seldom possible, we present here a method to design an online dynamic estimator for PM and NOx based on data. The design method is based on a systematic search of function candidates performed using genetic programming after data have been pre-treated in an adequate fashion. While data and a simple data pretreatment prove enough for NOx, some basic physical understanding is necessary to preset the method and obtain the required precision in the case of PM. The method has been applied for raw emissions of a production DI diesel engine and shows a remarkable prediction performance. While the method is not able to replace the insight in the design process given by physical understanding, the authors expect substantial advantages in all those cases in which the prediction of overall behavior is required, as virtual sensors, and also expect that the suitable introduction of additional physical knowledge can strongly improve the results.
Annotation ability available
   This content is not included in your SAE MOBILUS subscription, or you are not logged in.

NOx Virtual Sensor Based on Structure Identification and Global Optimization

Institute for Formal Models and Verification, Johannes Kepler University Linz-Stephan Winkler, Michael Affenzeller
Institute of Design and Control of Mechatronic Systems, Johannes Kepler University Linz-Luigi del Re, Peter Langthaler, Christian Furtmueller
Published 2005-04-11 by SAE International in United States
On-line measurement of engine NOx emissions is the object of a substantial effort, as it would strongly improve the control of CI engines. Many efforts have been directed towards hardware solutions, in particular to physical sensors, which have already reached a certain degree of maturity.In this paper, we are concerned with an alternative approach, a virtual sensor, which is essentially a software code able to estimate the correct value of an unmeasured variable, thus including in some sense an input/output model of the process. Most virtual sensors are either derived by fitting data to a generic structure (like an artificial neural network, ANN) or by physical principles. In both cases, the quality of the sensor tends to be poor outside the measured values. In this paper, we present a new approach: the data are screened for hidden analytical structures, combining structure identification and evolutionary algorithms, and these structures are then used to develop the sensor presented. While the computational time for the sensor design can be significant (e.g. 1 or more hours), the resulting formula…
Annotation ability available

LPV Dynamical Models of Diesel Engine NOx Emission

Johannes Kepler Univ.-Xiukun Wei, Luigi Del Re, Peter Langthaler
  • Technical Paper
  • 2004-35-0099
Published 2004-04-19 by University of Salerno in Italy
In this paper, the use of LPV models for the dynamic model of nitrogen oxides (NOx) produced by DI diesel engine based on measurement data is investigated. Engine emission control is an essential aspect to reduce the vehicle pollution and is usually achieved mostly by static maps, which are incapable to fulfill the rising demand of new and stricter emission standards in the future. LPV models can be seen as the natural dynamic extension of static maps. In this paper, the LPV local model of nitrogen oxides (NOx) is presented as well as the global model based on the fuzzy weighting approach.