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An increasing demand for reducing cost and time effort of the design process via improved CAE (Computer-Aided Engineer) tools and methods has characterized the automotive industry over the past two decades. One of the main challenges involves the effective simulation of a vehicle’s propulsion system dealing with different physical domains: several examples have been proposed in the literature mainly based on co-simulation approach which involves a specific tool for each propulsion system part modeling. Nevertheless, these solutions are not fully suitable and effective to perform statistical analysis including all physical parameters. In this respect, this paper presents the definition and implementation of a new simulation methodology applied to a propulsion subsystem.

This paper describes how distributive computing along with statistical subsystem simulation can be applied to produce near production ready embedded vehicle software and calibrations. Coupling distributive computing and statistical simulation was first employed over a decade ago at General Motors to design and analyze propulsion subsystem hardware. Recently this method of simulation has been enhanced extending its capabilities to both test embedded vehicle code as well as develop calibrations. A primary advantage of this simulation technique is its ability to generate data from a statistically significant population of subsystems. The result is the acquisition of an optimal data set enabling the development of a robust design now including both embedded code and calibrations. Additionally it has been shown that there are significant economic advantages in terms of time and cost associated with this type of development when compared to traditional method.