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An accurate air flow rate model is critical for high-quality air-fuel ratio control in Spark-Ignition engines using a Three-Way-Catalyst. Emerging Variable Valve Timing technology complicates cylinder air charge estimation by increasing the number of independent variables. In our previous study (SAE 2004-01-3054), an Artificial Neural Network (ANN) has been used successfully to represent the air flow rate as a function of four independent variables: intake camshaft position, exhaust camshaft position, engine speed and intake manifold pressure. However, in more general terms the air flow rate also depends on ambient temperature and pressure, the latter being largely a function of altitude. With arbitrary cam phasing combinations, the ambient pressure effects in particular can be very complex. In this study, we propose using a separate neural network to compensate the effects of altitude on the air flow rate.

Mercedes-Benz at DaimlerChrysler has been developing and applying Life-Cycle-Engineering (LCE) and Life-Cycle-Assessment (LCA) since almost 10 years. Extensive experience and know-how has been gained by two complete car LCAs and more than 100 LCAs for parts. According to our experience LCA/LCE is most effectively and efficiently used to support the development of new products. One of DaimlerChrysler's Environmental Guidelines includes a statement, that our approach to environmentally acceptable design covers the entire product spectrum of the DaimlerChrysler Group, taking into account the product life cycle from design through disposal or recycling. The organisation of environmental management at DaimlerChrysler has a distinct structure of tasks: the central Environmental Protection Division coordinates all organisation/ plant related aspects, while all product related aspects are the responsibility of the divisonal business units.