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Given the rather complicated set of coordinated control inputs which are necessary to control a spark ignition engine, primary control system development and evaluation can be a very difficult task. It is also difficult to develop microprocessor systems which are flexible enough for rapid system reconfiguration. In this paper it is shown that a Personal Computer (PC) provides an excellent solution to this common problem. Possible execution time problems are avoided by the use of a special multitasking environment and simple external hardware. The external hardware takes care of the cycle to cycle fueling and spark advance timing calculations. The PC itself uses its execution time only for calculating new fueling pulse widths and spark advance angles when the operating point of the engine changes. There is also extra computing capacity available for system simulations, condition monitoring, fault detection or perhaps driver information.

Many existing classical electronic control systems (speed-throttle, speed-density, MAF (mass air flow)) are based on quasistatic engine models and static measured engine maps. They are thus time consuming to adapt to new engine types, are sensitive to dynamic sensor errors and in general have undesirable dynamic characteristics. One of the main reasons for the characteristics of these strategies has been the lack of a precise, systems oriented, equation based, dynamic engine model. Recently a compact dynamic mean value engine model (MVEM) has been presented by the authors which displays good global accuracy. A mean value model is one which predicts the mean value of the gross internal and external engine variables. This paper shows how the engine model can be applied to the systematic design and analysis of classical electronic engine control systems. One of the main aims of the paper is to eliminate the use of cut and try methods in designing dynamic engine controls.

Open-source software is growing in popularity and becoming a real alternative to proprietary software. This is not only happening in home and office applications, but in embedded, industrial and engineering applications as well. This paper shows how open-source software can be used to develop and test engine models, both in simulations and in laboratory tests with real engines. It begins by explaining what open-source software is, its advantages and disadvantages compared to proprietary software, and what relevant software for engine modelling is already available. The paper describes the experience of the Engine Control Group (ECG) at the Technical University of Denmark (DTU), using a full open-source Linux solution including some software developed by the group itself. Finally, the paper concludes with the pros and cons of using this approach, suggesting tools and features to be developed in the future.

Conventional electronic engine control systems suffer from poor transient air/fuel ratio control accuracy. This is true of speed-throttle, speed-density, and mass air flow (MAF) control systems with either single point (or central) or port fuel injection. The reason for this is that they fail to 1. compensate for the nonlinear dynamics of the fuel film in the intake manifold or in the vicinity of the intake valves. 2. estimate correctly the air mass flow at the location of the injector(s). This paper presents a nonlinear fuel film compensation network and a nonlinear closed loop observer. The nonlinear fuel film compensator gives improved global cancellation of the fuel film dynamics, while the closed loop observer has improved robustness with respect to modelling error and measurement noise. The closed loop observer is based on a modified constant gain extended Kalman filter.

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.

One of the most important operating modes for SI engines is in the idle speed region. This is because SI engines spend a large part of their time operating in this mode. Moreover, a large measure of operator satisfaction is dependent on an engine operating smoothly and reliably in and around idle. In particular the operator expects that the idle speed will remain constant in spite of the engine loads due to power steering pumps and air conditioning compressors. In the idle speed region an SI engine is thought to be quite nonlinear because the engine loading can be quite significant, thus forcing the engine to be driven through a reasonably large portion of its lower operating range. Many of the earlier studies of idle speed control systems have dealt with linearized models which in principle have limited validity for the problem at hand. In order to improve this situation, it is necessary to deal with the more general nonlinear control problem.

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.

In general most engine models for control applications have been constructed using regressions fitting and measured engine data. Such techniques have also been used to model the dynamic performance of engines. Unfortunately regression equation models are very complex and do not show directly the physical reality from which they emerge. This has for example made it impossible to write down explicitly the dymanic equations for, for example, the air exchange process in an SI engine in any form other than as the manifold pressure state equation. In recent a publication a Mean Value Engine Model (MVEM) has been constructed for an SI engine which is physically based and which has a simple physical form which can be immediately understood and manipulated.

With the tightening of exhaust emission standards, wide bandwidth control of the air/fuel ratio (AFR) of spark ignition engines has attracted increased interest recently. Unfortunately, time delays associated with engine operation (mainly injection delays and transport delays from intake to exhaust) impose serious limitations to the achievable control bandwidth. With a proper choice of sensors and actuators, these limitations can be minimized provided the port air mass flow can be accurately predicted ahead in time. While the main objective of this work is to propose a complete AFR controller, the main focus is on the problems associated with port air mass flow prediction.

Long term stoichiometric Air/Fuel Ratio (AFR) control of an SI engine is at the present mainly maintained by table mapping of the engine's fresh air intake as a function of the engine operating point. In order to reduce a stationary error in the AFR to zero the table based control normally works in conjunction with a PI feedback from a HEGO sensor. The effective bandwidth of this feedback loop is quite small and seldom exceeds 2 Hz. This is altogether too small for accurate transient AFR control. This paper presents a new λ (normalized Air/Fuel Ratio) control methodology (H∞ control) which has a somewhat larger bandwidth and can guarantee robustness with respect to selected engine variable and parameter variations.

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.