Optimizing collision safety restraint systems for diverse drivers using multi-objective analysis.

Abstract

Objective: This study aims to enhance vehicle collision safety by developing and validating a simulation model and optimizing restraint system parameters based on the injury responses of both small-stature female drivers (5th percentile female dummy) and average-sized male drivers (50th percentile male dummy).

Methods: A finite element simulation model of a sedan was established using Hypermesh software, incorporating a Hybrid III 50th percentile male dummy. The model was validated through sled tests and adjusted to include a Hybrid III 5th percentile female dummy, reflecting the posture of small-stature female drivers. Sensitivity analysis and multi-objective optimization were conducted using Isight software and the NSGA-II genetic algorithm, focusing on key restraint system parameters such as seatbelt load limiter, seatbelt pullout amount, seatbelt extension rate, airbag triggering time, airbag vent hole size, and airbag gas mass flow.

Results: Optimized restraint system parameters significantly reduced head and chest injuries for both male and female dummies. The head HIC15 value for the male dummy decreased from 380 to 352, and chest compression from 24.9 mm to 20.4 mm. For the female dummy, the head HIC15 value was reduced from 615 to 426, and chest compression from 23.5 mm to 17.1 mm. All injury indicators met regulatory limits.

Conclusions: Current restraint systems designed for average-sized male drivers are inadequate for protecting small-stature female drivers. The optimized restraint system parameters significantly improve safety performance for both genders, addressing an important gap in existing research. These findings have significant implications for reducing the design cost of vehicle restraint systems and enhancing driver safety.