Innovative vehicle technologies

Engine optimization and digital twin

In order for autonomous shuttle buses to be optimally integrated into the traffic flow and achieve maximum range per battery charge, they need engines that are adapted as well as possible to the routes on which they are used. The aim of the research group Small Machines is therefore to map, evaluate and optimize the existing engine in a precise model in order to achieve an optimum compromise between the requirements of the route, the dynamics required from a safety point of view and the design of the engine. In this context, the research group also deals with the question of the extent to which differently designed specialized engines offer an advantage over a variant that is dimensioned for a universal and wide range of applications.

The driving profile of the buses is recorded with the high-precision measurement technology of the research group Automotive Engineering. With the help of satellite navigation data, the route is measured and digitally reproduced, including gradients, slopes and speeds. Based on this driving profile, a simulation of the engine performance is carried out. The aim is to identify the parameters that have the greatest influence on drive performance. The results of this simulation are then compared with measurements on the real engine in the test bench. In this way, the drive can ultimately be optimally designed with regard to the scaled performance requirements.

Instead of working with an additional engine, the research team will equip the provided research vehicle with measurement components to mirror it on a dynamic driving simulator. In this way, the scientists can collect data on driving dynamics (e.g. movements of the vehicle during braking and acceleration as well as changes in driving direction) in order to assess driving safety and comfort and determine relevant influencing variables.