Taguchi-EM-AI Design Optimization Environment for SynRM Drives in Traction Applications

摘要

Multi-objective design optimization environmentsare used for electric vehicles and other traction applications toarrive at efficient motor drives. Typically, the environmentincludes characterization modules that involve the use ofElectromagnetic Finite Element and State-Space models thatrequire large number of iterations and computational time. Thiswork proposes the utilization of a Taguchi orthogonal arraysmethod in conjunction with a Particle Swarm Optimization searchalgorithm to reduce computational time needed in the designoptimization of electric motors for traction applications. Theeffectiveness of the Taguchi method in conjunction with theoptimization environment is demonstrated in a case studyinvolving a prototype of a Synchronous Reluctance Motor drivesystem.