Multi-Objective Topology Optimization of Electrical Machine Designs using Evolutionary Algorithms with Discrete and Real Encodings
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Classically, designing electrical drives that are (simultaneously) optimal with regard to given criteria e.g., energy efficiency, costs, fault tolerance, etc. is a two step procedure. In the first step, a domain expert defines the complete geometric specifications of future designs. This means that the human expert actually creates/chooses a parametric model that will act as a generic template for any subsequent electrical drive that aims to solve the given task. In the second step, a (usually multi-objective) optimization method is employed to and those sets of parameter combinations that, when applied on the chosen generic template, produce (Pareto-)optimal design instances.