The paper deals with a comparison between different multiobjective optimisation algorithms, namely Adaptive Pareto Algorithm (APA), Genetic Algorithm (GA) and Parameter Space Investigation (PSI). The comparison has been completed by solving a test problem (ZDT1) widely considered in the literature and a real engineering problem concerning the optimisation of traction electric motors. The practical problem is addressed with the help of a specific custom-made tool for the optimisation of electric motors, where Motor-CAD™is used as multi-physics simulation software. Several metrics have been defined to objectively characterize the Pareto-optimal solutions obtained with the different algorithms.
COMPARISON OF MULTI-OBJECTIVE OPTIMISATION METHODS FOR THE DESIGN OF ELECTRIC MOTORS
Barri D.;Soresini F.;Gobbi M.;Mastinu G.
2022-01-01
Abstract
The paper deals with a comparison between different multiobjective optimisation algorithms, namely Adaptive Pareto Algorithm (APA), Genetic Algorithm (GA) and Parameter Space Investigation (PSI). The comparison has been completed by solving a test problem (ZDT1) widely considered in the literature and a real engineering problem concerning the optimisation of traction electric motors. The practical problem is addressed with the help of a specific custom-made tool for the optimisation of electric motors, where Motor-CAD™is used as multi-physics simulation software. Several metrics have been defined to objectively characterize the Pareto-optimal solutions obtained with the different algorithms.| File | Dimensione | Formato | |
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