Tatur, M., Tomazic, D., Sonntag, H., Wiehagen, N. et al., "Developing Drivetrain Robustness for Small Engine Testing," SAE Technical Paper 2013-01-0400, 2013, doi:10.4271/2013-01-0400.
The increased demand in fuel economy and the reduction of CO₂ emissions results in continued efforts to downsize engines. The downsizing efforts result in engines with lower displacement as well as lower number of cylinders. In addition to cylinder and displacement downsizing the development community embarks on continued efforts toward down-speeding. The combination of the aforementioned factors results in engines which can have high levels of torsional vibrations. Such behavior can have detrimental effects on the drivetrain particularly during the development phase of these. Driveshafts, couplings, and dynamometers are exposed to these torsional forces and depending on their frequency costly damages in these components can occur.To account for these effects, FEV employs a multi-body-system modeling approach through which base engine information is used to determine optimized drivetrain setups. All mechanical elements in the setup are analyzed based on their torsional behavior. Bending and axial vibration are considered in the analysis as well. During the early stages of engine development, very little information is available to ensure proper drivetrain layout. To ensure highest possible usefulness of the modeling tool, the developed algorithms can function with very limited input data. The moments of inertia, stiffness, and dampening of the five major groups - crankshaft, piston assembly, flywheel, driveshaft, dynamometer - are required to ensure successful processing. A large database with known components can support the process in case precise target data is not available. Cylinder pressure information allows to further increase the accuracy of the results. All available information is processed and the natural frequencies and Eigen modes are determined. This basis allows further optimization of the drivetrain through modifications of the critical parameters of flywheel and driveshaft. The optimized result allows robust and reliable engine testing under all operating conditions.