摘要
为提高小重叠碰撞事故中安全气囊对乘员的保护作用,分析了小重叠碰撞事故类型并获得识别小重叠碰撞的3个特征参数:速度变化量、加速度曲线长度比值和汽车主要受力方向。基于特征参数变量,结合自适应神经模糊推理系统开发了新型二级模糊安全气囊控制算法,来识别小重叠碰撞类型,并根据碰撞类型展开安全气囊。通过训练合适的模糊隶属度函数和模糊规则,该算法的性能得以提高。最后,经台车试验对新型安全气囊算法进行了验证。结果表明:在发生小重叠碰撞事故时,基于ANFIS的新型安全气囊控制算法能准确识别小重叠碰撞类型,及时展开前安全气囊和侧气帘,改善了其对乘员的保护作用。
In order to enhance the protection effects of safety airbag for occupant in small-overlap crash, the accident types of small-overlap crash are analyzed with three characteristic parameters obtained for identifying small-overlap crash, i. e. speed change,acceleration curve length ratio and the principal direction of force. Based on characteristic parameters,combined with adaptive neural fuzzy inference system （ ANFIS） ,a novel two stage fuzzy airbag control algorithm is developed to identify the type of small-overlap crash, according which the safety airbag is deployed. The performance of the algorithm can be enhanced by training appropriate fuzzy membership functions and fuzzy rules. Finally,the new airbag algorithm is validated by sled test. The results show that in the event of small- o-verlap crashes,the new airbag algorithm based on ANFIS can accurately identify the type of small-overlap crash and timely deploy front airbag and side air- curtain,improving their protection effects for occupant.
出处
《汽车工程》
EI
CSCD
北大核心
2017年第5期524-529,523,共7页
Automotive Engineering
基金
国家自然科学基金(51475153)资助
