Browse Publications Technical Papers 2011-01-2241
2011-09-13

Interior Noise Prediction and Analysis of Heavy Commercial Vehicle Cab 2011-01-2241

The basic theory of statistical energy analysis (SEA) is introduced, a commercial heavy duty truck cab is divided into 35 subsystems applying SEA method, and a three dimensional SEA model of the commercial heavy duty truck cab is created. Three basic parameters including modal density, damping loss factor and coupling loss factor are calculated with analytical and experimental methods. The modal density of the regular wall plate of the cab is calculated with traditional formula. The damping loss factors of the regular and complicated plates are obtained using analytical method and steady energy stream method. Meanwhile, the coupling loss factors of structure-structure, structure-sound cavity, and cavity-cavity are also calculated. Four kinds of excitations are in the SEA model, including sound radiation excitation of engine, engine mount vibration excitation, road excitation and wind excitation. The sound radiation excitation of engine, engine vibration mount excitation, and road excitation are obtained through road experiment. A computational fluid dynamics (CFD) model is established, and the wind excitations are simulated and calculated with the CFD model. Then, the interior noise of the truck cab is predicted using SEA model with all the parameters and excitations, and the prediction result is verified by the corresponding experimentation. The influence of acoustic cavity on interior noise is also analyzed. Finally, the prediction and analysis results show that the SEA model has a good prediction precision and can be used to instruct the improvement of interior acoustic performance of a truck cab.

SAE MOBILUS

Subscribers can view annotate, and download all of SAE's content. Learn More »

Access SAE MOBILUS »

Members save up to 43% off list price.
Login to see discount.
Special Offer: With TechSelect, you decide what SAE Technical Papers you need, when you need them, and how much you want to pay.
X