A Parametric Study of Vehicle Interior Geometry, Delta-V, and Instrument Panel Stiffness on Knee Injury and Upper Kinetic Energy

摘要

Previous experimental and theoretical studies on isolated human knees have shown that increasing the contact area over the knee during blunt impact can prevent serious knee injury (i.e. joint fracture). Because large contact areas are typically associated with lower stiffness impact interfaces, this suggests that instrument panels could provide some protection to the knee during a car accident. Further, the knee-to-IP contact is one of the first contact events which occur during a head-on crash, thus, one optimal scenario might be to dissipate as much energy as possible at the knee without causing serious knee injury. This would help minimize the kinetic energy in the upper body, possibly reducing the need for more aggressive countermeasures (i.e. air bags) later in the impact event. Our objective in the current study was to determine how different car interior geometries and crash pulses would affect specific occupant responses during a head-on car crash. To study a 'worst-case scenario', the occupant was unbelted and there was no airbag. An experimentally validated MADYMO-Pamcrash model was used to study the effect of the following 'input parameters' on the risk of knee injury and the kinetic energy of the upper body: instrument panel stiffness, seat height, knee-instrument panel distance, knee flexion angle, toe-pan angle, instrument panel angle, and crash pulse delta-v. It was found that the risk of knee injury was most sensitive to the IP stiffness, crash pulse delta- V, and the precrash distance between the knee and IP. The kinetic energy of the upper body, however, was sensitive to the seat height and initial knee flexion angle, as well as the delta-V and initial distance between the knee and IP. Regression models were developed which predicted the MADYMO-Pamcrash femur loads, knee contact areas, and upper body kinetic energy as a function of the input parameters described above. These statistical models provide the advantage of a first generation estimate of some key occupant responses I without expending resources associated with computer modeling or experimental tests. These data may prove helpful in the future design of multi-component injury prevention systems (air bags and knee bolsters) because one may anticipate specific loads, energies, and injury risks associated with the crash event. In conclusion, the current study identifies key vehicle design and crashworthiness parameters which affect the risk of knee injury and the kinetic energy of the upper body.