Abstract

The paper deals with a comparison between different multi-objective 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.

Volume Subject Area:
24th International Conference on Advanced Vehicle Technologies (AVT)
Keywords:
Pareto optimality, multi-objective optimisation, artificial intelligence, electric motors design, genetic algorithms
Topics:
Design, Electric motors, Genetic algorithms, Pareto optimization
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