A computational process to predict and mitigate liftgate gap noise

Noise comfort significantly influences vehicle purchasing decisions. With wind noise being a primary contributor to the overall cabin experience vehicle manufacturers must focus on optimizing the exterior shape of their models to minimize wind noise while balancing fuel efficiency and aesthetic appeal. High-speed airflow over gaps in the vehicle’s exterior can generate considerable noise, which often enters the cabin through seals. A good sealing strategy could be very helpful to address these gap noise issues. However, doing this with traditional experimental processes can be challenging, since early stage prototypes may lack detailed gap information. Modifying the seal design after the tooling stage to address these noise issues can be costly for manufacturers, as suppliers often incur expenses related to tool modifications and redesigns. Overdesigning by incorporating multiple layers of seals for all the gaps can inflate part and manufacturing costs, ultimately impacting profit margins. Given these challenges, there is a strong motivation for manufacturers to leverage advanced computational capabilities to identify gap noise issues early in the design process and develop effective sealing solutions. This study introduces a computational approach to evaluate potential noise issues arising from lift gate gaps and their contribution to cabin noise. This computational process uses an extensively-validated Lattice Boltzmann method (LBM) based computational fluid dynamics (CFD) solver to predict the transient flow field and exterior noise sources. Transmission of these noise sources through glass panels and seals were done by a well-validated statistical energy analysis (SEA) solver. Various sealing strategies were investigated to reduce interior noise levels attributed to these gaps, aiming to enhance wind noise performance. The findings emphasize the importance of integrating computational tools in the early design stages to mitigate wind noise issues and optimize sealing strategies effectively.