Development of Occupant Restraint System for SUV - Telco Experience

2003 ◽  
Author(s):  
S. Ravishankar ◽  
C. Anil Kumar ◽  
B. S. Praveen
Author(s):  
Di Zhou ◽  
Xianhui Wang ◽  
Qichen Zheng ◽  
Tiaoqi Fu ◽  
Mengyang Wu ◽  
...  

2012 ◽  
Vol 569 ◽  
pp. 795-799
Author(s):  
Liang Hong ◽  
Yun Teng Wu

To study the injury values rear seat occupants sustain in the frontal collision, this paper constructed the simulation model of the rear occupant restraint system of a vehicle model using MADYMO software. The influence of the rear 3-point seatbelt stiffness and retractor locking feature, the rear seat cushion stiffness and angle with the vehicle floor on head injury criterion HIC36, thorax 3ms resultant acceleration T3MS, thorax performance criterion THPC, left and right femur force of rear occupants were analysed through the simulation model. The conclusion shows that HIC36 drops when the seatbelt stiffness increases and retractor locking feature decreases compared to the original values; HIC36, T3MS, left and right femur force become less when the seat cushion stiffness decreases and angle increases compared to the original values.


Author(s):  
Seyed Saeed Ahmadisoleymani ◽  
Samy Missoum

Abstract Vehicle crash simulations are notoriously costly and noisy. When performing crashworthiness optimization, it is therefore important to include available information to quantify the noise in the optimization. For this purpose, a stochastic kriging can be used to account for the uncertainty due to the simulation noise. It is done through the addition of a non-stationary stochastic process to the deterministic kriging formulation. This stochastic kriging, which can also be used to include the effect of random non-controllable parameters, can then be used for surrogate-based optimization. In this work, a stochastic kriging-based optimization algorithm is proposed with an infill criterion referred to as the Augmented Expected Improvement, which, unlike its deterministic counterpart the Expect Improvement, accounts for the presence of irreducible aleatory variance due to noise. One of the key novelty of the proposed algorithm stems from the approximation of the aleatory variance and its update during the optimization. The proposed approach is applied to the optimization of two problems including an analytical function and a crashwor-thiness problem where the components of an occupant restraint system of a vehicle are optimized.


2010 ◽  
Vol 34-35 ◽  
pp. 111-116 ◽  
Author(s):  
Li Bo Cao ◽  
Chong Zhen Cui ◽  
Ning Yu Zhu ◽  
Huan Chen

In this article, seven frontal impact simulation models with same restraint system and different human body models were established through the use of multi-body kinematics software MADYMO. The injuries in head, chest and femurs of different human models and the differences of these injuries were analyzed in detail. The weighted injury criterion was adopted to evaluate the overall injuries of different human body models. The results shows that the injury risk of smaller human body is much higher than the taller human body, and existing occupant restraint system that protects the 50th percentile American occupant well protects other size occupant poorly.


2000 ◽  
Vol 2000 (0) ◽  
pp. 707-708
Author(s):  
Hideoki YAJIMA ◽  
Naoya KOIZUMI ◽  
Qiang YU ◽  
Masaki Shiratori

Sign in / Sign up

Export Citation Format

Share Document