Methods to Estimate the Confidence Level of the Experimentally Derived Statistical Energy Analysis Model: Application to Vehicles

The effectiveness of vehicle design' modifications based on an experimental SEA model will strongly depend on the confidence one can have in the identified model. This paper deals with the estimation of the variances of the experimentally derived internal and coupling loss factors, allowing to assess the confidence levels of the SEA predictions. The theory concerning the statistical aspects of the Power Injection Method (PIM) is outlined and the derived analytical expressions are validated based on a Monte-Carlo variability analysis. The statistical formulas are then applied to a railway carriage of a high-speed train, illustrating that the calculation of confidence levels is a very useful tool to assess the accuracy of the experimental SEA model.