Optimal design of the transverse flux machine using a fitted genetic algorithm with real parameters

This paper applies a fitted genetic algorithm (GA) to the optimal design of transverse flux machine (TFM). The main goal is to provide a tool for the optimal design of TFM that is easy to use. The GA optimizes the analytic basic design of two TFM topologies: the C-core and the U-core. First, the GA was designed with real parameters. An, objective of the fitted GA is minimization of the computation time, related to the number of individuals, the number of generations and the types of operators and their specific parameters.