The prediction of measurement variability in an automotive application by the use of a coherence formulation
journal contributionposted on 11.09.2017 by Amy Dowsett, Daniel O'Boy, Stephen Walsh, Ali Abolfathi, Stephen A. Fisher
Any type of content formally published in an academic journal, usually following a peer-review process.
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 from a series of controlled experiments. In this paper the 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 was shown to agree well with one another over the frequency range of interest.
This work was supported by Jaguar Land Rover and the UK-EPSRC grant EP/K014102/1 as part of the jointly funded Programme for Simulation Innovation.
- Aeronautical, Automotive, Chemical and Materials Engineering
- Aeronautical and Automotive Engineering