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• W2888536487 abstract "This paper presents the application of two classes of Evolutionary Algorithms (EA) to determine optimum design of Single-Phase Switched Reluctance Machine (SPSRM). The EA used is Genetic Algorithms (GA) and Differential Evolution (DE). Due to sensitivity of the output torque to the stator and rotor pole arcs, these are selected as design variables for a multi-objective optimization with the objective of maximizing average torque and torque density, and minimizing copper loss. The proposed optimization is tested on a 4/4 1,25 kW SPSRM, and the results of both algorithms are compared. The performance of the optimized motor is compared to the initial motor through the finite element analysis. The results show improvement in both efficiency and output torque." @default.
• W2888536487 created "2018-08-31" @default.
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• W2888536487 date "2018-06-01" @default.
• W2888536487 modified "2023-10-16" @default.
• W2888536487 title "Evolutionary Algorithms for Optimization of 4/4 Single Phase Switched Reluctance Machine" @default.
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• W2888536487 doi "https://doi.org/10.1109/tla.2018.8444387" @default.
• W2888536487 hasPublicationYear "2018" @default.
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