Car manufacturers put large efforts into reducing wind noise to improve the comfort level of their cars. Each component of the vehicle is designed to meet its individual noise target to ensure the wind noise passenger comfort level inside the vehicle is met. Sunroof designs are tested to meet low-frequency buffeting (also known as boom) targets and broadband noise targets for the fully open sunroof with deflector and for the sunroof in vent position. Experimentally testing designs and making changes to meet these design targets typically involves high cost prototypes, expensive wind tunnel sessions, and potentially late design changes. To reduce the associated costs as well as development times, there is strong motivation for the use of a reliable numerical prediction capability early in the vehicle design process.
In the past, a computational approach based on a Lattice Boltzmann Method has been extensively validated for assessing the wind noise performance of mirrors, wipers, underbody designs and buffeting performance of sunroofs and open side windows. This paper presents the use of this computational approach on the Range Rover production vehicle to assess the sunroof buffeting performance with and without a mesh deflector added, which are commonly used to improve the buffeting performance. This approach was extended to assess the broadband noise generated by the deflector up and the sunroof at vent position. Computational predictions were validated against wind tunnel measurements for all these configurations. Also detailed flow analysis was performed to provide insight into the noise generation mechanisms. Accurate prediction of the wind noise performance of the sunroof and the insight provided by the flow analysis prove that this computational approach can be used to make design decisions during the vehicle development process.
