安全气囊
限制
偏转(物理)
限制器
混合动力III
胸部(昆虫解剖学)
撞车
毒物控制
安全带
结构工程
医学
工程类
计算机科学
解剖
物理
光学
环境卫生
机械工程
程序设计语言
电信
作者
Audrey Petitjean,Matthieu Lebarbé,Pascal Potier,Xavier Trosseille,Jean-Pierre Lassau
出处
期刊:SAE technical paper series
日期:2002-11-11
被引量:31
摘要
Load-limiting belt restraints have been present in French cars since 1995. An accident study showed the greater effectiveness in thorax injury prevention using a 4 kN load limiter belt with an airbag than using a 6 kN load limiter belt without airbag. The criteria for thoracic tolerance used in regulatory testing is the sternal deflection for all restraint types, belt and/or airbag restraint. This criterion does not assess the effectiveness of the restraint 4 kN load limiter belt with airbag observed in accidentology. To improve the understanding of thoracic tolerance, frontal sled crashes were performed using the Hybrid III and THOR dummies and PMHS. The sled configuration and the deceleration law correspond to those observed in the accident study. Restraint conditions evaluated are the 6 kN load-limiting belt and the 4 kN load-limiting belt with an airbag. Loads between the occupant and the sled environment were recorded. Various measurements (including thoracic deflections and head, thorax and pelvis accelerations and angular velocities on the dummies) characterize the dummy and PMHS behavior. PMHS anthropometry and injuries were noted. This study presents the test methodology and the results used to evaluate dummy ability to discriminate both restraint types and dummy measurement ability to be representative of thoracic injury risk for all restraint types. The injury results of the PMHS tests showed the same tendency as the accident study. Some of the criteria proposed in the literature did not show a better protection of the 4 kN load limiter belt with airbag restraint, in particular thoracic deflection maxima for both dummies. The four thoracic deflections measured on the THOR and Hybrid III dummies may allow more accurate analysis of the loading pattern and therefore of injury risk.
科研通智能强力驱动
Strongly Powered by AbleSci AI