Browse Publications Technical Papers 2007-01-1155
2007-04-16

Future Truck Steering Effort Optimization 2007-01-1155

In an endeavor to improve upon historically subjective and hardware-based steering tuning development, a team was formed to find an optimal and objective solution using Design For Six Sigma (DFSS). The goal was to determine the best valve assembly design within a hydraulic power-steering assist system to yield improved steering effort and feel robustness for all vehicle models in a future truck program. The methodology utilized was not only multifaceted with several Design of Experiments (DOEs), but also took advantage of a CAE-based approach leveraging modeling capabilities in ADAMS for simulating full-vehicle, On-Center Handling behavior. The team investigated thirteen control factors to determine which minimized a realistic, compounded noise strategy while also considering the ideal steering effort function (SEF) desired by the customer. In the end, it was found that response-dependent variability dominated the physics of our valve assembly design concept. This meant that it would be difficult with this design and its specific set of control factors to achieve both the ideal SEF and a consistent SEF with minimal variation (i.e. a high Signal-to-Noise Ratio) through Parameter Design optimization only. It was also found that a certain ideal SEF was indeed desired by the customer when determined in conjunction with other key vehicle performance parameters, and that steering effort robustness, though also important, was nearly an order of magnitude lower in value to the customer in terms of dollars that they would spend. Finally, it was learned through Tolerance Design optimization that designs approaching this ideal SEF could further benefit from tolerance control on specific design parameters and processes. As a result of this study, it became apparent that different strategic competitors tune their valve assembly designs decidedly different - along the lines of either a high-satisfaction or a high-value strategy.

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