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Electronics now control or drive a large part of automotive system design and development, from audio system enhancements to improvements in engine and drive-train performance, and innovations in passenger safety. Industry estimates suggest that electronic systems account for more than 30% of the cost of a new automobile and represent approximately 90% of the innovations in automotive design. As electronic content increases, so does the possibility of electronic system failure and the potential for compromised vehicle safety. Even when designed properly, electronics can be the weakest link in automotive system performance due to variations in component reliability and environmental conditions. Engineers need to understand worst-case system performance as early in the design process as possible.

Adopting robust design principles is a proven methodology for increasing design reliability. General Motors Powertrain (GMPT) has incorporated robust design principles into their Signal Delivery Subsystem (SDSS) development process by moving traditional prototype manufacturing and test functions from hardware to software. This virtual manufacturing technique, where subsystems are built and tested using simulation software, increases the number of possible prototype iterations while simultaneously decreasing the time required to gather statistically meaningful test results. This paper describes how virtual manufacturing was developed using distributed computing.

In an earlier paper one of the authors of this paper (E. Hendricks and co-authors) treated the question of obtaining correct steady state and transient control of the air/fuel (A/F) ratio of an SI engine. This study was based in part on simulations conducted with a dynamic engine model developed earlier and in part on experimental results. The main conclusions were that conventional control strategies (Speed-Throttle, Speed-Density and Mass Air Flow (MAF)) cannot give proper A/F control because of 1. sensor and anti-aliasing filter time constants and 2. improper or lacking compensation for manifold fuel film and (air) filling dynamics. In this paper, the results of a long series of experiments conducted with the control systems above are to be presented. Both central fuel injection (CFI) (or throttle body (TBI)) and electronic fuel injection (EFI) (or multipoint (MPI)) manifolds have been investigated.

Many existing production engine controllers use event (or constant crank angle increment) based sampling and computation systems. Because the engine events are synchronized to the internal physical processes of an engine, it is widely accepted that this is the most logical approach to engine control. It is the purpose of this paper to deal with this assumption in detail and to illuminate various failures of it in practical systems. The approach of the paper is in terms of overall general control system design. That is to say that the problem of event based engine control is considered as a general control problem with its standard components: 1. modelling (engine plus actuator/sensor), 2. specification of desired performance goals, 3. control system design method selection and 4. experimental testing.

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.

An important element in nearly all engine control systems is the lambda control feedback system and its associated switching exhaust gas oxygen sensor (EGO). This feedback loop is necessary to keep the mean value of the normalized air/fuel ratio close to one. This is a necessary condition for proper operation of the three-way catalyst systems which are a part of nearly all production emissions control systems. Currently many systems are based on using classical proportional-integral (PI) controllers in lambda control feedback loops which are self-oscillating. Proper design of such systems is dependent on knowing the time delay between the injection time and the time when a corresponding signal appears at the engine exhaust EGO sensor. Recently a new method of designing the vital larnbda control loop has emerged which is claimed to be very robust with respect to the injection/exhaust time delay.