FEM Simulation Methodology for Accurately Capturing the Experimental Vibration Response of ECM Assembly on a Commercial Vehicle

Paper #:
  • 2018-01-0467

Published:
  • 2018-04-03
Abstract:
This paper presents an experimental setup and an equivalent FEM simulation methodology to accurately predict the response of Engine Control Module (ECM) assembly mounted on a commercial vehicle subjected to road vibrations. Comprehensive vibration study is carried out. It involved Modal characteristics determination followed by random vibration characterization of the ECM assembly. A hammer impact experiment is first performed in lab to estimate the natural frequencies and mode shapes of ECM assembly. Mounting conditions in test specimen are kept similar to the actual mounting settings on vehicle. Natural frequencies and mode shapes predicted from free vibration experiment are compared with finite element (FE) based modal analysis. The importance of capturing the assembly stiffness more accurately by incorporating pre-stress effects like bolt-pretension and gravity, is emphasized. The ECM assembly is then tested in random vibration field experiment, by mounting it on chassis of a commercial vehicle and running the vehicle on a predetermined road profile. The excitations predicted from random vibration tests are characterized in terms of power spectral density (PSD). Leveraging the learnings from modal analysis, an FE based random vibration analysis is performed on a reduced sub-model of the chassis containing just the ECM assembly. Input PSD loads to the FE sub-model are obtained in the test from sensors at the cut-boundary locations. The output response PSD (RPSD) values are predicted at ECM – bracket bolt locations. FE analysis results are compared with experimental results. A comparison of single point PSD input versus multiple point PSD input is carried out which shows improvement in FE analysis prediction by multiple point input PSD. The FE results after incorporating pre-stress effects and multiple point PSD inputs are found in good correlation with experimental results and useful for making design decisions in ECM.
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