Probabilistic Modelling of the Conceptual Design Phase in Automotive Engineering

Abstract

The multidisciplinary nature of the vehicle design process and the increasing demand for developing environmentally sustainable transport systems present a challenge to the automotive industry. These challenges are associated with uncertainties that are often neglected in the conceptual design phase of road vehicles. To address such uncertainties, a probabilistic approach can be adopted. More precisely, one can make use of the so called Sobol’ indices. These are used within the context of variance-based global sensitivity analysis to quantify the uncertainties of a system’s outputs caused by the uncertainties of its inputs. For this purpose, this paper aims to achieve the following goals: 1. Quantification of output uncertainties in the conceptual design phase based on the Sobol’ indices. Within this context, the research plug-in hybrid electric vehicle “Interurban Vehicle” (IUV), designed at the German Aerospace Centre (DLR1 ), is considered. 2. Probabilistic, digital and parametric modelling of the IUV based on multidisciplinary design analysis (MDA). Overall, this paper concludes that probabilistic modelling does not only enable the quantification of uncertainties, but also helps to understand the underlying complex mechanisms of the considered system and support the decision-making process in the conceptual design phase of road vehicles