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A computational design study, performed in conjunction with experiments, to reduce the howl noise caused by the roof rack crossbars of a production automobile is presented. This goals were to obtain insight into the flow phenomenon causing the noise, and to do a design iteration study that would lead to a small number of cross-section recommendations for crossbars that would be tested in the wind tunnel. The flow condition for this study is 0 yaw at 30 mph inlet speed, which experimentally gives the strongest roof rack howl for the vehicle considered for this study. The numerical results have been obtained using the commercial CFD/CAA software PowerFLOW. The simulation kernel of this software is based on the numerical scheme known as the Lattice Boltzmann Method (LBM), combined with a two-equation RNG turbulence model.

This paper reports on a case study involving the use of SEA methods in the acoustic design of an advanced design luxury sedan. The power of the analytical method was used to advantage in a case of a vehicle with very challenging NVH targets. Three practical issues are highlighted; review of a method to handle adding components that contribute acoustic absorption, presentation of data to aid vehicle content decisions, and design sensitivity analysis. This effort demonstrates an example in which SEA modeling provided relevant and timely input to the vehicle design team to aid decision making for sound package content.

Statistical energy analysis (SEA) has recently emerged as an effective tool for design assessment in the automotive industry. Automotive OEM companies develop vehicle models to aid design of body and chassis systems. The tire and wheel suppliers develop and supply component models to OEM companies in the engineering stage. In the model development process, some information on the vehicle side or component side is necessary for model development and correlation. A suitable termination representation of the vehicle characteristics on the tire/wheel model is required. This termination should account for the dissipation of energy on vehicle body and chassis side, otherwise the component model will overestimate the vibration responses and energy levels. On the vehicle model side, a representative simplified tire/wheel model may be sufficient for full vehicle road noise simulation.

Statistical Energy Analysis (SEA) models of passenger vehicles may involve 400-500 subsystems to characterize the vehicle structure and sound package. Full sized models are often difficult to describe and some results may be awkward to present. A more intuitively comprehensible model size would involve 30-50 subsystems, which is typical of an experimental SEA approach. A methodology is described for processing full SEA model results in condensed form including major structural components and acoustic spaces. The approach is based on the experimental SEA methodology in which power injection and response predictions are carried out for 30-50 condensed subsystems. Full matrix inversion and weak coupling assumptions were investigated. Differences between condensed and full SEA model predictions are observed when the subsystem connectivity is limited.