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Estimation of vehicle roll angle, lateral velocity and side slip angle for the purpose of crash sensing is considered. Only roll rate sensor and the sensors readily available in vehicles equipped with ESC (Electronic Stability Control) systems are used in the estimation process. The algorithms are based on kinematic relationships, thus avoiding dependence on vehicle and tire models, which minimizes tuning efforts and sensitivity to parameter variations. The estimate of roll angle is obtained by blending two preliminary estimates, each valid in different conditions, in such a manner that the final estimate continuously favors the more accurate one. The roll angle estimate is used to compensate the gravity component in measured lateral acceleration due to vehicle roll or road bank angle. This facilitates estimation of lateral velocity and side slip angle from fundamental kinematic relationships involving the gravity-compensated lateral acceleration, yaw rate and longitudinal velocity.

During the past decade, there has been a steady increase in studies addressing rollover crashes and injuries. Though rollovers are not the most frequent crash type, they are significant with respect to serious injury and interest in rollovers has grown with the introduction of SUVs, vans, and light trucks. A review of Occupant and Vehicle Responses in Rollovers examines relevant conditions for field roll overs, vehicle responses, and occupant kinetics in the vehicle. This book edited by Dr. David C. Viano and Dr. Chantal S. Parenteau includes 62 technical documents covering 15 years of rollover crash safety, including field crash statistics, pre- and rollover dynamics, test procedures and dummy responses.

A complete system approach to power semiconductor analysis and selection is set forth in this paper. In order to address design overkill, a suitable power profile across the desired drive schedule is obtained through vehicle simulation in lieu of worse case operating conditions. The representative profile is then applied to detailed models of the inverter, power device, and power device thermal stack-up in order to predict worse case, silicon junction temperature rise. The simulation stream includes a closed silicon thermal loop that leads to more accurate power loss and junction temperature calculations. The models are combined and exercised in a single platform for ease of integration and fast simulation. Herein, the methods will be applied to a working example of an inverter for motor drives, and analytical results will be reviewed.