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An event-based transient fuel compensator (TFC) algorithm was developed for production application on SPFI gasoline engines. The independent parameters of the TFC were related to fundamental mass-transfer principles from the research of Gilliland and Sherwood [1] to simplify cold-driveability and emissions calibration activities. A compact intake valve temperature model was developed to further simplify calibration. Digital Control Theory was applied to the calibration structure of the algorithm to clarify the relationship between compensator stability and parameter settings. In its final production algorithm form on a 2.4L DOHC engine application, the TFC met the required subjective cold-driveability requirements and emission standards with a significant reduction in transient fuel calibration complexity.

A Barometric Pressure Estimator (BPE) algorithm was implemented in a production speed-density Engine Management System (EMS). The BPE is a model-based, easily calibrated algorithm for estimating barometric pressure using a standard set of production sensors, thereby avoiding the need for a barometric pressure sensor. An accurate barometric pressure value is necessary for a variety of engine control functions. By starting with the physics describing the flow through the induction system, an algorithm was developed which is simple to understand and implement. When used in conjunction with the Pneumatic and Thermal State Estimator (PSE and TSE) algorithms [2], the BPE requires only a single additional calibration table, generated with an automated processing routine, directly from measured engine data collected at an arbitrary elevation, in-vehicle or on a dynamometer. The algorithm has been implemented on several different engines.

Pneumatic and Thermal State Estimator (PSE and TSE) algorithms were implemented in a production speed-density Engine Management System (EMS) to provide engine mass flow, pressure, and temperature estimates for general use by other control, diagnostic, and estimator algorithms. A fluid-network architecture (see, for example, [1],[2]) was used to significantly reduce development cycle time associated with iterative calibration work, to increase flexibility to engine hardware changes, and to enable the application of Modern Control Theory. The algorithms and associated development process were applied to a 2.4L DOHC engine. The PSE and TSE met internally-defined performance requirements and, in application, LEV emissions.