Francesco Pirozzi

Realization of a Virtual Lambda Sensor on a Fixed Precision System

The paper studies the implementation feasibility of a VLS (virtual lambda sensor) by a TSK (Takagi, Sugeno, Kang) singleton FIS (fuzzy inference system). Such a sensor could be used in a model based EMS (engine management system) for trade gasoline engines. The FIS design target is to obtain a system with a fixed data representation (i.e., 10 bit) and a limited number of inputs, outputs, rules and membership.

Modelling on-off virtual lambda sensors based on multi-spread probabilistic neural networks

In this work, we have explored a novel model of learning machine which seems to be able to emulate effectively the way of functioning of the traditional on-off lambda sensors (i.e. O2 sensor). These sensors are a low cost solution used in the SI (spark ignition) engines to monitor the air-fuel ratio and so to maintain a strict control of the air-fuel mixture close the stoichiometric condition. The idea behind this work is to suggest a scheme of air/fuel control system for SI engines in which there is not need of a lambda sensor. The last is replaced by a model, named as virtual lambda sensor (VLS), trained in order to predict the air-fuel ratio values in function of features suitably selected by the in-cylinder pressure sensor signal