Possibilities for Speeding Up the FE-Based Optimization of Electrical Machines-A Case Study

This paper deals with accelerating typical optimization scenarios for electrical machine designs. Besides the advantage of a reduced computation time, this leads to a reduction in computational power and thus to a lower power consumption when running the optimization. If machines of high power density are required, usually highly utilized assemblies that feature nonlinear characteristics are obtained. Optimization scenarios are considered where the evaluation of a potential design requires computationally expensive nonlinear finite element (FE) simulations. Improving the speed of optimization runs takes top priority and various measures can be considered. This paper is about basic and easily achievable measures, and techniques for a time-wise and computationally efficient exploration of the design space. Suggested improvements comprise sophisticated emerging techniques for modeling machine characteristics by paring the number of required FE simulations down to the minimum and nonlinear modeling of the targets of the optimization scenario as functions of the design parameters to further reduce the number of FE evaluations. In the case study, the analysis of a typical optimization task is given, and achievable speed improvements as well as still present issues are discussed.