Surround sensing methods provide information which can be used in PRECRASH functionalities for advanced control of the passenger protection system. The relevant data (closing velocity (cv), time to impact (tti), and offset of contact point (Δy)) are determined with a Predictive Safety System and transmitted to the airbag control unit for further processing in the PRECRASH algorithm.
The PRECRASH algorithm controls both, the activation of reversible restraints and the deployment of irreversible restraints. Therefore it consists of two components: The PREFIRE and the PRESET algorithm. The PREFIRE algorithm uses the PRECRASH information for the activation of the reversible belt pretensioner in advance of a crash to reduce chest load in the crash phase. The PRESET algorithm calculates the trigger decision for deployment of pyrotechnical restraints. Inputs of the PRESET algorithm are the PRECRASH information as well as the acceleration signal. Due to the combined analysis of the PRECRASH information and the acceleration signals, it is possible to differentiate between different barrier types. This is described in the PRESET algorithm section. Based on the barrier type and the closing velocity, the severity of the crash can be determined. Since the PRESET algorithm computes a precise crash severity, it is capable to determine effectively the strength of an adaptive restraint.
Independent of the PRECRASH information, a purely acceleration based algorithm provides its own trigger decision. The trigger decisions of this algoritm and of the PRESET algorithm are combined in a fusion module to get the final deployment decision for the irreversible restraints.
The advantage of the Predictive Safety System is that it provides crash relevant information in advance of a crash, enabling control of reversible restraints. This leads to a reduced risk and severity of injury in high-speed crashes as well as improved occupant protection even in slow and soft crashes. The robust crash severity classification of the PRESET algorithm particularly enables a precise timing of robust deployment decisions, which can also be used for an efficient control of adaptive restraints.