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  • Summary & Details

A Strategy for Developing an Inclusive Load Case for Verification of Squeak and Rattle Noises in the Car Cabin

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Author(E)1) Mohsen Bayani Khaknejad, 2) Jonatan Nilsson, 3) Rasmus Blom, 4) Casper Wickman, 5) Rikard Söderberg
Affiliation(E)1) Volvo Car Corporation, 2) Chalmers University of Technology, 3) Chalmers University of Technology, 4) Volvo Car Corporation, 5) Chalmers University of Technology
Abstract(E)Squeak and rattle (S&R) are nonstationary annoying and unwanted noises in the car cabin that result in considerable warranty costs for car manufacturers. Introduction of cars with remarkably lower background noises and the recent emphasis on electrification and autonomous driving further stress the need for producing squeak- and rattle-free cars. Automotive manufacturers use several road disturbances for physical evaluation and verification of S&R. The excitation signals collected from these road profiles are also employed in subsystem shaker rigs and virtual simulations that are gradually replacing physical complete vehicle test and verification. Considering the need for a shorter lead time and the introduction of optimisation loops, it is necessary to have efficient and inclusive excitation load cases for robust S&R evaluation. In this study, a method is proposed to truncate and identify the important parts of the different road profiles that are often used for S&R physical verification and then merge them to develop one representative excitation load case. The criteria for signal truncation were based on the S&R risk and severity metrics calculated from the vibration response at the critical interfaces for S&R. the method was used in a case study involving the instrument panel of a passenger car. Results of the virtual simulation and the rig tests were compared with the complete vehicle test. The proposed synthesised signal generation strategy was validated by physical testing through measuring vibration signals. The results supported the possibility of replacing multiple S&R excitation signals with one single representative inclusive signal, while the quality of S&R risk prediction from the system response was maintained. The outcome of this work can lead to a more efficient physical and virtual S&R verification in the development process of passenger cars.

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