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Automatic Design of PM Motor Using Monte Carlo Tree Search in Conjunction With Topology Optimization

Hayaho Sato, Hajime Igarashi

2022IEEE Transactions on Magnetics22 citationsDOIOpen Access PDF

Abstract

A novel automatic design method for permanent magnet (PM) motors using a Monte Carlo tree search is presented. The optimal motor structures are determined through a tree search, in which the motors with different numbers of poles, current phase angles, PM configurations, and numbers of PMs are simultaneously considered. At the leaf nodes, parameter and topology optimizations are performed to obtain the optimal material shape and distribution. The proposed method was applied to the optimization of a 24-slot motor. It was shown to be effective in finding the optimal motor structure and geometry to maximize the average torque while considering iron loss. The proposed method can be applied not only to the design of PM motors but also to many types of electric apparatus and other systems.

Topics & Concepts

Monte Carlo methodTopology (electrical circuits)Topology optimizationComputer scienceTorqueTree (set theory)Optimal designElectric motorMonte Carlo tree searchInduction motorMagnetMathematical optimizationMathematicsVoltagePhysicsFinite element methodMechanical engineeringEngineeringMathematical analysisElectrical engineeringThermodynamicsMachine learningStatisticsCombinatoricsElectric Motor Design and AnalysisArtificial Intelligence in GamesEvolutionary Algorithms and Applications
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