Search Results

To date, model validation metric is prominently designed for non-dynamic model responses. Though metrics for dynamic responses are also available, they are specifically designed for the vehicle impact application and uncertainties are not considered in the metric. This paper proposes the validation metric for general dynamic system responses under uncertainty. The metric makes use of the popular U-pooling approach and extends it for dynamic responses. Furthermore, shape deviation metric was proposed to be included in the validation metric with the capability of considering multiple dynamic test data. One vehicle impact model is presented to demonstrate the proposed validation metric.

Effects of DOF and subjective method on evaluations of ride quality on the Ford Vehicle Vibration Simulator were studied. Seat track vibrations from 6 vehicles were reproduced on the 6 DOF seat shaker in a DOE with pitch and roll as factors. These appeared in two evaluations of ride/shake; semantic scaling by 30 subjects of 6 vehicles, and paired comparisons by 16 of the subjects on 3 of the vehicles. Both methods found significant vehicle, pitch and roll effects. Order dependence was shown for semantic scaling. The less susceptible paired comparison method gave a different ordering, and is thus preferred.

A new inflator specification, the “inflator thrust variable,” was developed to better explain measured mid-sized male, instrumented test dummy responses in the chest-on-module test condition. Specifically, controlled laboratory experiments were conducted with non-production, driver airbag modules with inflators of various outputs and gas constituents in an effort to assess their effects on a pertinent occupant response. Regression analyses showed that the inflator thrust variable is a better predictor of the observed variation in peak viscous criterion responses than either peak tank pressure or the related pressure rise rate when inflators of differing gas composition were compared.

Since their inception, the design of airbag sensing systems has continued to evolve. The evolution of air bag sensing system design has been rapid. Electromechanical sensors used in earlier front air bag applications have been replaced by multi-point electronic sensors used to discriminate collision mechanics for potential air bag deployment in front, side and rollover accidents. In addition to multipoint electronic sensors, advanced air bag systems incorporate a variety of state sensors such as seat belt use status, seat track location, and occupant size classification that are taken into consideration by air bag system algorithms and occupant protection deployment strategies. Electronic sensing systems have allowed for the advent of event data recorders (EDRs), which over the past decade, have provided increasingly more information related to air bag deployment events in the field.

This paper will discuss the various tools used to measure the steering and suspension properties of a vehicle. Measuring the kinematic and compliance properties of the steering and suspension systems is an important part of the vehicle development process. Some of the ways these measurements are used include confirmation of vehicle design and build, to create and correlate CAE models, and for diagnosis of steering and handling concerns. Understanding exactly how the steering and suspension systems are performing is an important step in the development process. We have found that by employing the proper tools and methods, plus having a defined vehicle dynamics fingerprint process, that most issues and concerns can be successfully resolved.