Application of Surrogate Optimization Routine with Clustering Technique for Optimal Design of an Induction Motor

Aswin Balasubramanian, Floran Martin, Md Masum Billah, Osaruyi Osemwinyen and Anouar Belahcen
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Aswin Balasubramanian: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Floran Martin: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Md Masum Billah: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Osaruyi Osemwinyen: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland
Anouar Belahcen: Department of Electrical Engineering and Automation, Aalto University, 02150 Espoo, Finland

Energies, 2021, vol. 14, issue 16, 1-19

Abstract: This paper proposes a new surrogate optimization routine for optimal design of a direct on line (DOL) squirrel cage induction motor. The geometry of the motor is optimized to maximize its electromagnetic efficiency while respecting the constraints, such as output power and power factor. The routine uses the methodologies of Latin-hypercube sampling, a clustering technique and a Box–Behnken design for improving the accuracy of the surrogate model while efficiently utilizing the computational resources. The global search-based particle swarm optimization (PSO) algorithm is used for optimizing the surrogate model and the pattern search algorithm is used for fine-tuning the surrogate optimal solution. The proposed surrogate optimization routine achieved an optimal design with an electromagnetic efficiency of 93.90 % , for a 7.5 kW motor. To benchmark the performance of the surrogate optimization routine, a comparative analysis was carried out with a direct optimization routine that uses a finite element method (FEM)-based machine model as a cost function.

Keywords: induction motors; surrogate optimization; Box–Behnken design; Latin-hypercube sampling; clustering; particle swarm optimization; pattern search (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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