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This paper presents a comprehensive Matlab/Simulink-based framework that affords a rapid, systematic, and efficient engine control system development process including automated code generation. The proposed framework hinges on three essential pillars: 1 ) an accurate model for the target engine, 2) a toolset for systematic control design, and 3) a modular system architecture that enhances feature reusability and rapid algorithm deployment. The proposed framework promotes systematic model-based algorithm development and validation in virtual reality. Within this context, the framework affords integration and evaluation of the entire control system at an early development stage, seamless transitions across inherently incompatible product development stages, and rapid code generation for production target hardware.

The fierce competition and shifting consumer demands require automotive companies to be more efficient in all aspects of vehicle development and specifically in the area of embedded engine control system development. In order to reduce development cost, shorten time-to-market, and meet more stringent emission regulations without sacrificing quality, the increasingly complex control algorithms must be transportable and reusable. Within an efficient development process it is necessary that the algorithms can be seamlessly moved throughout different development stages and that they can be easily reused for different applications. In this paper, we propose a flexible engine control architecture that greatly boosts development efficiency.

This paper outlines the derivation of an analytical volumetric efficiency model that can be used in mean-value engine models or in air estimation algorithms for variable cam phasing and two step valve lift applications. The model is the product of a physics-based modeling approach. It accounts for the most prominent effects that occur during the gas exchange phase of a four cycle combustion process. Variable valve lift and valve timing are intrinsically modeled in terms of their geometric nature. The gas pressure trajectory, which has a crucial impact on the volumetric efficiency, is modeled via piece-wise linear approximation functions. The proposed model has a total of 16 regression parameters that need to be adjusted on the basis of experimental data. The model validation is based on four sets of engine mapping data, each set pertaining to one particular valve lift mode but otherwise spanning the entire engine operating envelope in terms of speed, load and cam-phasing positions.