Whiplash-associated disorder is one of the most common injuries from rear-impact crash scenarios. Knowing the injury mechanism is one of the keys in designing the seat to reduce the risk of injury. Due to the effects of variation, whiplash prevention is one of the most challenging safety-related topics in automotive industry. The test variation can originate from the dummy itself, seat components, materials, assembly tolerance, and as well as typical test setup variations. It is important to understand these variations and take them into account using Computer-Aided Engineering (CAE) analysis in order to identify how to reduce the risk of injury. In this paper, a robust methodology to predict occupant response from CAE simulations is developed by combining a Design of Experiment (DOE) with an Automated Process (AP). A Whiplash Variation Map (WVM) is developed to serve as a seat design aid.
The DOE approach applied in this study is a powerful tool to reveal how various behaviors stem from basic variables. Sensitivities, major contributions, relations and interactions amongst variables can be identified with confidence level determined. The variation of occupant responses can be evaluated. The Automated Process of simulating the variations is a major enabler to use the DOE approach.
From the DOE results, a Whiplash Variation Map (WVM) is developed to quantify effects from different variation parameters. An Optimal Dummy Profile (ODP) of the maximum occupant movement is proposed for whiplash target setting on a conventional seat design, which can be used for future seat applications.