Crash sensors for the dosed deployment of multi-stage restraint systems

Boran, Colm; Feltgen, Christian

doi:10.1007/bf03226424

Cited by 1 publication

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“…Trigger time (Tt): Trigger time is the time between when the airbag sensor senses the accident and the time when the airbag starts to inflate. In this paper, according to the average of trigger time, three different times including 15, 25 and 35 ms are considered for different levels of this factor (Boran and Feltgen, 2001).…”

Section: Design Of Experimentsmentioning

confidence: 99%

Sensitivity analysis and optimization for occupant safety in automotive frontal crash test

Asadinia

Khalkhali

Saranjam

2018

Lat. Am. j. solids struct.

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Nowadays, safety is a competitive advantage for automotive products and therefore receives considerable attention by automotive research centers. In this paper, a frontal crash test of sedan product of an under development platform is simulated and occupant head injuries are investigated based on ECE R94 regulation. First, an initial evaluation of the crash behavior of the sedan car is carried out and then airbag, dummy and seat belt are added to the model to study occupant head injuries under crash test. In this study, peak head acceleration and head injury criteria (HIC36) are considered as two output parameters based on ECE R94 regulation. Considering these two output parameters, sensitivity analysis and optimization are performed using Taguchi and analysis of variance (ANOVA) methods. In this way, airbag distance to dummy, trigger time, initial inflator gas temperature and tank pressure are considered as input parameters. Obtained results show that in all computer experiments designed by Taguchi responses values satisfy the requirements of ECE R94. Two different out-of-position conditions are considered by reducing the distance between dummy and airbag relative to the optimum design obtained by Taguchi. The worst case of design and its response values are also predicted using Taguchi. Finally, re-evaluating finite element analyses are performed based on the optimum and the worst cases. The results of these simulations show the validity of approach of this paper.

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Section: Design Of Experimentsmentioning

confidence: 99%