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Continuous improvement of side airbag safety performance is an important step because it is associated with many public domain tests and regulations. Thus, occupant restraint with a side airbag is critical and it is necessary to develop tools that can be utilized to help in design of side airbags. Though many papers on side impact safety have been published, only a few papers are related to MADYMO simulations of side airbags. This paper describes an improved injury prediction and optimization approach using a MADYMO model for side impact. This model consists of 3 parts: dummy, trim and airbag in FEM. In this study, a side impact with a ES-2, EuroSID-2, was simulated in MADYMO as follows: First, component tests were conducted for trim and airbag respectively to establish correlation. Second, these component models were then integrated into a MADYMO model, which has high correlation with a crash simulator that is capable of replicating physical vehicle tests.

Driver fatality rate of a passenger vehicle is considerably high when struck on the side by an LTV (light truck and van). Aggressivity of LTVs, particularly in side crashes, needs to be reduced to improve this incompatible situation. Crash energy absorption share of a passenger car struck on the side by an LTV was measured through component tests. As a result, B-pillar of the struck passenger car was found to receive most of the crash energy intensively. This intensive energy triggered large B-pillar deformation. Computer simulation proved that B-pillar deformation was closely related to occupant injury. The key to mitigate the injury of side-struck car occupant, therefore, is to disperse crash energy to other structural parts than B-pillar. Front-end structures of LTVs that realize crash energy dispersion were designed and examined. The structures include (a) optimization of the vehicle height, and (b) adoption of a forward-extended sub-frame.

To reduce real world fatal/serious/minor injuries, factors causing such injuries should be investigated in depth from wider perspectives. The aim of this paper is to clarify the factors based on Japanese accident database compiled by ITARDA (Institute for Traffic Accident Research and Data Analysis). ITARDA database has data for injury rates, seatbelt use rate of driver and age of driver involved in crashes, etc. by vehicle model. As a result of an elaborate statistical analysis, the most influential and essential factors on all injuries including fatality were quantitatively found to be seatbelt use rate and vehicle weight. The increase by 1% in seatbelt use rate makes injury rate decrease by 7%. The influence of vehicle weight is 1.7 times higher than seatbelt use rate. Multiple regression analysis on these two parameters was also conducted. The present analysis successfully predicted all injury rates by model per 10,000 units.