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This paper describes a method to estimate the engine stop position using any production style crank position sensor, while accounting for possible engine rock-back. The approach is based on modeling the engine speed state, achieving robustness and ease of calibration by adapting the rubbing friction model component during the first part of engine coast-down, followed by open-loop modeling when the engine speed has dropped below the sensor signal validity threshold.

Signal processing incorporating Artificial Neural Networks (ANN) has been shown to be well suited for modeling engine-related performance indicators [ 1 , 2 , 3 ] that require multi-dimensional parametric calibration space. However, to obtain acceptable accuracy, traditional ANN implementation may require processing resources beyond the capability of current engine controllers. This paper explores the practicality of implementing an ANN-based algorithm performing real-time calculations of the volumetric efficiency (VE) for an engine with variable valve actuation (phasing and lift variation). This alternative approach was considered attractive since the additional degree of freedom introduced by variable lift would be cumbersome to add to the traditional multi-dimensional table-based representation of VE.

Many exhaust gas analyzers only calculate the Air Fuel Ratio (AF) based on equations derived for the special case of combustion without exhaust gas recirculation (EGR), and therefore do not represent the combustion AF during lean operation with EGR. Equations that are not subject to this limitation will be presented. Using these equations to provide measurements of the combustion AF and total inert EGR is encouraged as they relate more directly to what governs the combustion process.

This paper presents three sub-models of production Engine Management Systems software for turbocharged engines; 1) new load variable for volumetric efficiency modelling, 2) new pumping torque model, where 1) and 2) both solve non-monotonic behavior of traditional techniques for active boost controlled engines, 3) Compressor Recirculation Control requiring only the compressor surge-line for calibration.

This paper presents production Engine Management System algorithms for Estimation and Control of Turbocharged engines with the following qualities; 1) Model based ensuring applicability at all ambient conditions, 2) Does not require Turbine data for calibration 3) Estimation logic form allows reuse for control applying predictive values for response and stability 4) Applies to all Waste-Gate types; passive and active, pneumatic and electrical, 5) Does not require Waste-Gate position measurement 5) Applies to engines with Variable Geometry Turbine.

A dynamic EGR State Estimator (ESE) intended for production engine management systems (EMS) implementation is presented. It better describes the development of external exhaust gas recirculation (EGR) concentration at the engine intake ports during EGR transients than traditional models. The dynamics of EGR concentration time and spatial development in the intake manifold are described as a perfect mixing model in the intake manifold plenum volume and non-mixing plug flow in the intake manifold runners. The time scale of EGR transients precludes the use of traditional EGR measurement techniques for model verification. Instead a wide range air fuel (WRAF) sensor is used. Results are shown for a large variation in operating conditions and compared to the performance of a traditional model.

Because there are no production-type sensors which are able to measure the flow directly at the intake port, it is becoming common practice to use models of varying complexity to infer the port air mass flow from other measurements. Given the tight requirements of modern air/fuel ratio (AFR) control strategies, the accuracy of these models needs to be better than ever, during steady-state of course (though λ feedback strategies are by design very robust), but mainly during transient operation. This paper describes why conventional models might be inaccurate during engine transients.