Identification of Internal Loss Factors During Statistical Energy Analysis of Automotive Vehicles

Statistical Energy Analysis (SEA) is a useful tool for predicting the transmission of noise and vibration through the structures of automotive vehicles. This work discusses the identification of SEA internal loss factor parameters from experimental measurements of vehicle sound pressure levels and structural accelerations. A simple automotive vehicle SEA model can be constructed from elements idealized as uniform beams, flat plates and acoustic volumes. Such an SEA automotive vehicle model can accurately predict the vibro-acoustic response of an automotive vehicles when appropriate equivalent SEA parameters are identified from in situ experimental data. This paper will present an algorithm for identifying internal loss factors for SEA models. The paper will include an example of the application of the algorithm to identification of automotive vehicle internal loss factors from measured vehicle response data. The spectral characteristics of these identified internal loss factors will be compared to those typically employed in Statistical Energy Analysis.