For instance, today a transmission is designed for a certain lifetime or mileage, taking into account extreme load cases. However, only a small proportion of drivers (about 2-3%) cause such extreme load cases.
With the help of smart-big-data methods and innovative approaches for real-time prediction of the remaining lifespan, vehicle components can be developed more easily and cost-effectively in the future. An important aspect is the knowledge and consideration of the actual user behavior. Based on measured driving profiles, test cycles are synthesized which better map the load spectum of real users than existing standard cycles. We are pursuing these and other ideas at the IMS as part of Vision Vehicle 5.0. This unites the research projects of several institutes of TU Darmstadt, which deal with the implementation of the future, knowledge-based vehicle.