A large number of plastic clips are used in an automotive vehicle to connect the trim to the structure. These are small clips with very small masses compared to the structural elements that they connect together; however, the uncertainty in their properties can affect the dynamic response. The uncertainty arises out of their material and manufacturing tolerances and more importantly the boundary conditions. A test rig has been developed that can model the mounting condition of the clips. This allows measurement of the range of their effective stiffness and damping. Initially, the boundary condition at the structure side is replicated. The variability is found to be 7% for stiffness and 8% for damping. In order to simulate the connection of the trim side, a mount is built using a 3D printer. The variability due to the boundary condition on both sides was as large as 40% for stiffness and 36% for damping. A Monte Carlo simulation is used in order to assess the effect of the uncertainty of the clips’ properties on the vibration transfer functions of a door assembly. A simplified connection model is used in this study where only the axial degree of freedom is considered in connecting the trim to the door structure. The uncertainty in the clip stiffness and damping results in a variability in the vibration transfer function which is frequency dependent and can be as high as 10% at the resonant peaks with higher values at some other frequencies. It is shown that the effect of the uncertainty in the clips effective damping is negligible and the variability in the dynamic response is mainly due to the uncertainty in the clip’s stiffness. Furthermore, it is shown that the variability would reduce either by increasing or decreasing the effective stiffness of the clips.
Variability between nominally identical vehicles is an ever-present problem in automotive vehicle design. In this paper, it is shown that it is possible to quantify and, therefore, separate the measurement variability arising from a number of tests on an individual vehicle from the vehicle-to-vehicle variability arising from the manufacturing process with a series of controlled experiments. In this paper, coherence data is used to identify the measurement variability and, thus, to separate these two variability sources. In order to illustrate the methodology, a range of nominally identical automotive vehicles have been tested for NVH (noise, vibration and harshness) variability by exciting the engine mount with an impact hammer and measuring the excitation force and corresponding velocity responses at different points on the vehicle. Normalised standard deviations were calculated for the transfer mobility data, giving variability values of 25.3%, 33.5% and 37.3% for the responses taken at the suspension strut, upper A-pillar and B-pillar, respectively. The measurement variability was determined by taking repeat measurements on a single vehicle, and was found to be 2.9%. The measurement variability predicted by the coherence data on the multi-vehicle tests was compared with the directly taken repeat measurements taken on a single vehicle and these were shown to agree well with one another over the frequency range of interest.
An experimental investigation carried out on a luxury sedan door observed the effect of making small changes to trim boundary conditions by removing and replacing a series of small polymer clips that held the trim to the aluminium door. Structural testing was carried out by exciting the system with a shaker and recording the response with accelerometers placed at three different locations about the door. Acoustic response measurements were also taken with the use of a sound intensity probe. The study found that the removal of even a single clip could vary the response significantly for certain clip locations. The spread of structural data was also found to range by more than 15 dB for certain frequency bands. Similar large deviations were observed for the noise transfer response measurements. This is significantly large spread of data for what might be perceived as a relatively small change to the structure, highlighting the importance of reduced variability at material joints.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.