Browse Publications Technical Papers 2023-01-1060
2023-05-08

NVH Prediction for a Heavy-Duty Truck Vehicle Using Multi-Level FRF Based Sub-Structuring Approach 2023-01-1060

Increase in comfort requirements for noise and vibrations in commercial vehicles, demand for identifying major NVH issues and addressing them at design stages, thereby avoiding cost incurred due to design changes in later stages of the product development. This work majorly focusses on establishing an approach for predicting NVH performance of a heavy-duty truck using frequency response function based sub-structuring (FBS) methodology. This approach helps in reducing the overall solving time, specifically while analyzing for truck finite element models with large number of degrees of freedom. It majorly involves representation of all subsystems of a truck in the form of frequency response functions.
A detailed finite element model of a full truck is evaluated for NVH load cases such as vibration / noise transfer function studies and operational NVH load cases such as vehicle idle and dynamic gear run-ups. Cabin noise and tactile vibrations are the major operational NVH parameters predicted using the detailed model. Also, FRFs and cross-FRFs are evaluated for each of the subsystems of the full truck such as cab, cab suspension, chassis, chassis suspension at the hard points or integration points.
With the information available on FRFs and cross-FRFs of the major subsystems, a simplified model is developed using multi-level FBS, without finite element representation. The operational NVH parameters are predicted with the FBS model for all load cases and the FBS results observed to be in good agreement with detailed FE model results. Also, significant reduction in solving time of the full truck model is achieved.
The benefits of FBS approach can be further extended to a variety of other NVH developments such as mount stiffness optimization, evaluating design changes in the cab or chassis structure for NVH impact, consuming very less solving time.

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