Chassis Loads Prediction using Measurements as Input to an Unconstrained Multi-Body Dynamics Model

James C. Tebbe; Vivek Chidambaram; Jason T. Kline; Sam Scime; Manish P. Shah; Mine Tasci; David Zheng

doi:10.4271/2006-01-0992

2006-04-03

Chassis Loads Prediction using Measurements as Input to an Unconstrained Multi-Body Dynamics Model 2006-01-0992

Automotive engineering development processes are growing more dependent on the use of multi-body dynamic (MBD) models for generating vehicle loads that at one time could only be measured using physical hardware. A certain technique combines these two approaches using a minimal set of physical measurements to excite a vehicle MBD model for predicting loads at various vehicle interfaces. This approach eliminates the use of a tire model, often the roadblock in MBD-based loads prediction simulations. However, for various reasons, the direct application of loads to a model can lead to problems with the simulation. Alternatively, the model can be artificially constrained but this also has its disadvantages.

The purpose of this paper is to present a loads prediction technique that relaxes the use of artificial boundary conditions for applications involving the input of measurements to an MBD model.

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Chassis Loads Prediction using Measurements as Input to an Unconstrained Multi-Body Dynamics Model 2006-01-0992

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