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This study focuses on fluctuations in the aerodynamic load acting on a hatchback car model under steady-state conditions, which can lead to degeneration of vehicle motion performance due to excitation of vehicle vibrations. Large eddy simulations were first conducted on a vehicle model based on a production hatchback car with and without additional aerodynamic devices that had received good subjective assessments by drivers. The numerical results showed that the magnitudes of the lateral load fluctuations were larger without the devices at Strouhal numbers less than approximately 0.1, where surface pressure fluctuations indicated a negative correlation between the two sides of the rear end, which could give rise to yawing and rolling vibrations. Based on the numerical results, wind-tunnel tests were performed with a 28%-scale hatchback car model.

Vehicle body movements that occur during cornering have a strong influence on the evaluation of ride and handling. As a first step, we analyze subjective comments from trained drivers and find that the sense of vision played a major part in cornering feel. As a result of quantitative evaluations, we hypothesize that smaller time lag between roll angle and pitch angle made cornering feel better. We perform a human sensitivity evaluation, which confirmed this hypothesis. Given this result, we derive analytical equations for the roll center kinematics and the damping characteristics, in order to find a theoretical condition for the time lag of 0sec (giving a good cornering feel). We verify this by experiment.

Lower extremity injuries in frontal automotive crashes usually occur with footwell intrusion where both the knee and foot are constrained. In order to identify factors associated with tibial shaft injury, a series of numerical simulations were conducted using a finite element model of the whole human body. These simulations demonstrated that tibial mid-shaft injuries in frontal crashes could be caused by an abrupt change in velocity and a high rate of footwell intrusion.

Numerical analyses of head and neck response during side impact are presented in this paper. A mathematical human model for side impact simulation was developed based on previous studies of other researchers. The effects of muscular activities during severe side impact were analyzed with the use of this model. This study shows that the effect of muscular activities is significant especially if the occupant is prepared to resist the impact. This result suggests that the modeling of muscles is important for the simulation of real accident situation.

Previous studies have hypothesized that the shoulder may be used to absorb some impact energy and reduce chest injury due to side impacts. Before this hypothesis can be tested, a good understanding of the injury mechanisms and the kinematics of the shoulder is critical for occupant protection in side impact. However, existing crash dummies and numerical models are not designed to reproduce the kinematics and kinetics of the human shoulder. The purpose of this study was to develop a finite element model of the human shoulder in order to achieve a deeper understanding of the injury mechanisms and the kinematics of the shoulder in side impact. Basic anthropometric data of the human shoulder used to develop the skeletal and muscular portions of this model were taken from commercial data packages. The shoulder model included three bones (the humerus, scapula and clavicle) and major ligaments and muscles around the shoulder.

Accurate prediction of occupant head kinematics is critical for better understanding of head/face injury mechanisms in side impacts, especially far-side occupants. In light of the fact that researchers have demonstrated that muscle activations, especially in neck muscles, can affect occupant head kinematics, a human body finite element (FE) model that considers muscle activation is useful for predicting occupant head kinematics in real-world automotive accidents. In this study, we developed a human body FE model called the THUMS (Total HUman Model for Safety) Version 5 that contains 262 one-dimensional (1D) Hill-type muscle models over the entire body. The THUMS was validated against 36 series of PMHS (Post Mortem Human Surrogate) and volunteer test data in this study, and 16 series of PMHS and volunteer test data on side impacts are presented. Validation results with force-time curves were also evaluated quantitatively using the CORA (CORrelation and Analysis) method.