Abstract:

In order to mitigate biomechanical injuries sustained by middle-sized children during frontal collisions of school buses, this study investigated the optimal design of intelligent airbags. Initially, a validated school bus simulation model was constructed based on sled test data. Subsequently, methods for determining head, thorax, and femur injury values for a 10-year-old THUMS dummy were established, and the model, including the school bus restraint system, THUMS dummy and intelligent airbag, was developed. Next, based on NSGA-III, the adaptive propagation factors were proposed, the Gaussian mutation operator and the evolutionary mechanism of the particle swarm optimization method were introduced, and the non-dominated sorting level was improved, thus putting forward the improved NSGA-III. Finally, the design optimization of the intelligent airbag was conducted using the improved NSGA-III to determine the optimal configuration of the airbag. The results demonstrate that the improved NSGA-III outperforms the other three state-of-the-art optimization algorithms. Under normal, 10° forward tilt, 20° forward tilt, 5° right tilt, 10° right tilt and lying sitting postures, the head injury criterion (HIC₁₅), intracranial pressure (IP), liver pressure (LP), left and right femur forces (F_L and F_R, respectively), and weighted injury criterion (WICC) for middle-sized children are significantly reduced when the proportional coefficient of the gas mass-flow rate of the inflation valve, the opening pressure and opening coefficient of the deflation valves, and the installation height of the air bag are set at 1.23, 1.37×10⁵ Pa, 2.10, and 478 mm, respectively.

Key words: middle-sized children, school bus, intelligent airbag, design optimization, total human model for safety(THUMS)dummy, improved non-dominated sorting genetic algorithm-III(NSGA-III)