Production tolerances, material variations, usage scenarios and other influences lead to uncertainty in the optimal design of electric machines. The first objective of the project is the development, analysis and application of robust optimisation methods for geometry and topology optimisation of electric machines under uncertainty. By using first and second order approximation techniques we plan to develop (distributionally) robust optimisation formulations and efficient adjoint-based solvers invoking reduced order models and error estimators. Moreover, we plan to develop optimisation methods for the optimal design of experiments such that resulting estimates of material parameters by solving inverse problems have minimal variance.
DFG Programme
CRC/Transregios
