Multi-objective optimization of gear tooth profiles to improve weight, efficiency, dynamic behavior, and wear performance, focusing on both involute macro-geometry and free-form non-involute profiles. Key results include more than 40% reduction in power losses and 35% reduction in vibration RMS for optimized involute gears. For free-form gears, reductions of up to 55% in average wear depth and 70% in maximum wear depth have been achieved.
Research on plastic gear transmissions at MD-Lab combines material-model development, finite-element and neural-network surrogate modelling, dynamic/NVH simulation, and additive manufacturing technologies. Key results include neural-network surrogates that reproduce finite-element static transmission error curves for polymer gears with 0.49% MAPE, dynamic simulations showing reduced vibration levels compared with metallic gearsets, and additive-manufacturing studies that quantify FDM and other 3D-printing accuracy limits while investigating wear resistance and wear patterns in printed gears.
