Validation of Wind Noise for Class-8 Truck Using Lattice Boltzmann Method

Features
Authors Abstract
Content
The transportation and mobility industry trend toward electrification is rapidly evolving and in this specific scenario, wind noise aeroacoustics becomes one of the major concerns for OEMs, as new propulsion systems are notably quieter than traditional ones. There is, however, very limited references available in the literature regarding validation of computational fluid dynamics (CFD) simulations applied to the prediction of aeroacoustics contribution to the noise generated by large commercial trucks. Thus, in this work, high-fidelity CFD simulations are performed using lattice Boltzmann method (LBM), which uses very large eddy simulation (VLES) turbulence model and compared to on-road physical tests of a heavy-duty truck to validate the approach. Furthermore, the effect of realistic wind conditions is also analyzed. Two different truck configurations are considered: one with side mirror (Case A) and the other without (Case B) side mirrors. The main focus of this work is to assess the accuracy of the commercial CFD software PowerFLOW® to predict greenhouse wind noise analysis for heavy vehicles as a tool to complement or replace physical testing during the vehicle design process. From this study, we found that external microphone measurements at the passenger-side glass demonstrate strong correlation with simulation results, highlighting the importance of including a typical level of on-road free-stream turbulence to achieve accurate sound pressure level (SPL) correlations for the full frequency range available from the physical test (i.e., 100 Hz to 2000 Hz) for both configurations.
Meta TagsDetails
DOI
https://doi.org/10.4271/02-18-03-0021
Pages
18
Citation
Guleria, A., Novacek, J., Ihi, R., Fougere, N. et al., "Validation of Wind Noise for Class-8 Truck Using Lattice Boltzmann Method," Commercial Vehicles 18(3):391-408, 2025, https://doi.org/10.4271/02-18-03-0021.
Additional Details
Publisher
Published
Aug 29
Product Code
02-18-03-0021
Content Type
Journal Article
Language
English