Acoustic Characteristics Simulation Of Mufflers And Sound Quality Design Of Exhaust Noise

Along with the improvement of industrial technology, the sound power of vehicle noise has been controled effectively, the amelioration of sound quality has been the main aspect in the research of vehicle noise. As one of the main noise source of engine and vehicle, the improvement of exhaust noise sound quality would greatly affect the NVH characteristic of engine or even the finished vehicle. Focus on the vehicle exhaust noise sound quality, this paper is concerned with the acoustic characteristics simulation of mufflers and the sound quality design of exhaust noise. Combine the acoustic characteristics simulation results with the achievement of sound quality subjective evaluation, a method of exhaust noise sound quality design and optimization was advanced, which is proved to be effective by the structure optimization of an applied muffler.In this paper, the acoustic characteristics of a simple expansion chamber muffler and a more realistic non-axisymmetrical muffler are obtained by using the three-dimensional Computational Fluid Dynamics simulation. The CFD results are compared with FEM and experimental results, the CFD simulation shows great advantage in accounting for the dissipative effects of the flow field on the acoustic field in general for the prediction of more complex muffler. Futher more, the influence of mean flow on the acoustic response of muffler is taken into account, calculated result shows that the attenuation level of the muffler is reduced with mean flow in the whole frequency range, and has a trend of shifting to the higher frequency.The subject evaluation of vehicle exhaust noise is processed by the paired comparison jury test, and the proper psychoacoustic parameters are selected among the all to objectively characterize the sound quality of exhaust noise. The relation between sensory pleasantness and objective parameters is achieved through multiple linear regression analysis. The research indicates that the loudness is the most important factor of those affecting the perceptions of people to the vehicle exhaust noise.The sound quality prediction model of vehicle exhaust noise is established based on back-propagation neural network. Sensory pleasantness of exhaust noise samples are obtained through the prediction model, and the results are compared with that obtained through multiple linear regression prediction model. The result shows that the prediction values are close to the measured values, the neural network model is more effective than multiple linear regression model in prediction of individual exhaust noise. The neural network prediction model represent the nonlinear relation between sensory pleasantness and objective parameters exactly, can be used for predicting the sound quality of vehicle exhaust noise.