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In earlier work it has been shown that a nearly ideal solution to the problem of accurate estimation of the air mass flow to a central fuel injection (CFI) (or throttle body (TBI)) or EFI (or multi-point (MPI)) equipped engine is provided by using a closed loop nonlinear observer for the engine. With proper design this observer was shown to be both accurate and robust with respect to modelling end measurement errors. It is based on a Constant Gain Extended Kalman Filter (CGEKF). Since the publication of this work, another type of observer has emerged in the literature for which claims of great robustness have been made. This observer is based on new developments in the area of nonlinear control theory and is called a Sliding Mode Observer (SMO). In this paper these two types of observers are compared theoretically and experimentally on an engine mounted on a dynamometer. A very aggressive driving scenario is assumed for these tests.

In an earlier paper, some of the authors of this paper pointed out some of the difficulties involved in event based engine control. In particular it was shown that event based (or constant crank angle) sampling is very difficult to carry out without running into aliasing and sensor signal averaging problems. This leads to errors in reading the air mass flow related sensors and hence inaccurate air/fuel ratio control. The purpose of this paper is first to demonstrate that the conjectures about the operator input spectrum in a vehicle do actually obtain during vehicle operation in realistic road situations. A second purpose is to extend earlier modelling work and to present an approximate physical method of predicting the level of engine pumping fluctuations at any given operating point. The physical method given is based on a modification of the Mean Value Engine Model (MVEM) of a Spark Ignition (SI) engine presented previously.

Mean Value Engine Models (MVEMs) are dynamic models which describe dynamic engine variable (or state) responses as mean rather than instantaneous values on time scales slightly longer than an engine event. Such engine variables are the independent variables in nonlinear differential (or state) equations which can be quite compact but nevertheless quite accurate. One of the most important of the differential equations for a spark ignition (SI) engine is the intake manifold filling (often manifold pressure) state equation. This equation is commonly used to estimate the air mass flow to an SI engine during fast throttle angle transients to insure proper engine fueling. The purpose of this paper is to derive a modified manifold pressure state equation which is simpler and more physical than those currently found in the literature. This new formulation makes it easier to calibrate a MVEM for different engines and provides new insights into dynamic SI engine operation.

A very important component of an accurate steady state and transient air/fuel (A/F) ratio control strategy is the transient fuel compensation (TFC) substrategy. This is the part of an engine control algorithm which cancels the fuel film dynamics and makes it possible to place injected fuel into the intake manifold (or close to the intake ports or valves) of a spark ignition (SI) engine at the correct time and location. This paper presents the results of a very large series of experiments conducted with the same engine with either a throttle body (TBI) (or central fuel injection (CFI)) manifold or with a multi-point port injection (MPI) (or electronic fuel injection (EFI)) manifold. These experiments have shown that in some practical applications it may be necessary to model the intake manifold as a two time constant dynamic system rather than as a single differential equation system.