An Experimental and Multiphysics Based Numerical Study to Predict Automotive Fuel Tank Sloshing Noise 2014-01-0888
With significant decrease in the background noise in present day automobiles, liquid slosh noise from an automotive fuel tank is considered as a major irritant during acceleration and deceleration. All major international OEMs and their suppliers try to reduce sloshing noise by various design modifications in the fuel tank. However, most major activities reported in open literature are primarily based on performing various CAE and experimental studies in isolation. However, noise generation and its propagation is a multiphysics phenomenon, where fluid mechanics due to liquid sloshing affects structural behaviour of the fuel tank and its mountings which in turn affects noise generation and propagation. In the present study a multiphysics approach to noise generation has been used to predict liquid sloshing noise from a rectangular tank. Computational Fluid dynamics (CFD), Finite Element Analysis (FEA) and Boundary Element Method (BEM) simulation studies have been performed in a semi-coupled manner to predict noise. VOF based multiphase model along with k-ε turbulence model was used to perform the CFD studies. Sloshing Noise generated due to fluid interaction with structural walls is simulated using Vibro-acoustic model. An integrated model is developed to predict dynamic forces and vibration displacement on tank walls due to dynamic pressure loading on tank walls. Noise radiated from tank walls is modelled by Harmonic Boundary Element Method. Experimental and numerical studies have been performed to understand the mechanics of sloshing noise generation. Images from high speed video camera and noise measurement data have been used to compare with numerical models.
Citation: Jadon, V., Agawane, G., Baghel, A., Balide, V. et al., "An Experimental and Multiphysics Based Numerical Study to Predict Automotive Fuel Tank Sloshing Noise," SAE Technical Paper 2014-01-0888, 2014, https://doi.org/10.4271/2014-01-0888. Download Citation
V. Jadon, G. Agawane, A. Baghel, Venkatesham Balide, R. Banerjee, A. Getta, H. Viswanathan, A. Awasthi
IIT Hyderabad, Mercedes Benz R&D India