Acoustic Development Differences Between Theoretical And Experimental Process for Automotive Exhaust System 2015-36-0277

Acoustics, in a broad sense, is an essential product attribute in the automotive industry, therefore, it is relevant to study and compare theoretical and numerical predictions to experimental acoustic measurements, key elements of many acoustic development processes. The numerical methods used in the industry for acoustic predictions are widely used for exhaust system optimization. However, the numerical and theoretical predictions very often differ from experimental results, due to modeling simplifications, temperature variations (which have high influence on speed of sound), manufacturing variations in prototype parts among others. This article aims to demonstrate the relevant steps for acoustics development applied in automotive exhaust systems and present a comparative study between experimental tests and computer simulations results for each process. The exhaust system chosen for this development was intended for a popular car 4-cylinder 1.0-liter engine. It should be noted that the results here presented do not reflect the application, once the engine did not have the final calibration. The study begins with standing waves analysis for the exhaust system proposal and fundamental and harmonic frequencies generated from the engine. Then, Transmission Loss tests were performed for acoustics components (Resonators and Mufflers) designed to mitigate the noise level for the specific frequency ranges. The results clearly demonstrated the differences and difficulties to adjust theoretical models with experimental ones. The assembly constrains, package and underbody layout are among the examples of such difficulties. The ideal system - without packaging constrains - closely correlates with the theoretical conditions, while the final solution had a more complex design to achieve sound pressure level targets. This should not be cause for discouragement, but rather a motivation for engineers, since the need to adapt to the project constrains creates opportunities to expand knowledge.