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The usage of multi-body dynamics tools for the prediction of vehicle system/sub-system loads, has significantly reduced the need to measure vehicle loads at proving grounds. The success of these tools is limited by the quality of the digital representations being used to simulate the physical test roads. The development of these digital roads is not a trivial task due to the large quantity of data and processing required. In the end, the files must be manageable in size, have a globally common format, and be simulation-friendly. The authors present a methodology for the development of high quality 3-dimensional (3-D) digital proving ground profiles. These profiles will be used in conjunction with a multi-body dynamics software package (ADAMS) and the FTire™ model. The authors present a case study below.

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.

A technique to determine which loads or combination of loads that contribute to the fatigue damage of a component is proposed. Knowing critical loads allows a designer the opportunity to better optimize designs. This information also helps accelerate durability evaluation procedures (both analytical and laboratory based). The technique involves the use of a computer-based FEA method incorporating conventional fatigue life prediction algorithms to assess component durability on an element-by-element basis. After a global fatigue analysis of the entire component, the critical element(s) are identified. A statistical approach, based on a factorial design of experiments, is then applied to assess the effect of varying combinations of component input loads on the predicted durability of these elements. This approach provides a methodology for keeping computational time to a minimum whilst developing a comprehensive understanding of the behavior of the critical areas.