Advanced Permanent Magnet Generator Topologies Using Multimaterial Shape Optimization and 3D Printing

Latha Sethuraman, Andrew Glaws, Miles Skinner, Parans Paranthaman

Research output: NRELPresentation

Abstract

A vast majority of utility-scale wind turbine generators in the United States depend on foreign-sourced rare-earth permanent magnets that are vulnerable to supply chain uncertainties. Many small wind original equipment manufacturers are motivated to pursue continuous improvements to the generator design to lower the material and production costs and improve performance by lowering cogging torque and increasing efficiency. Traditional design and manufacturing offer limited opportunities. In this work, we demonstrate advanced design approaches for a 15-kW baseline wind turbine generator by making use of recent progress in three-dimensional (3D) printing of polymer-bonded magnets and electrical and structural steel. We explore three methods of magnet parametrization using Bezier curves resulting in symmetric, asymmetric and multimaterial magnet designs. We employ a multiphysics approach combining parametric computer-aided-design modeling, finite-element analysis, and targeted sampling to identify novel designs with more opportunities for reducing rare-earth material, improving efficiency and minimizing cogging torque. The results show that asymmetric-pole design and multimaterial-pole designs offer a greater opportunity to minimize rare-earth magnet materials by up to 35% with similar performance as the baseline generator, suggesting newer opportunities with design freedom beyond traditional limits of symmetry and as allowed by 3D printing.
Original languageAmerican English
Number of pages19
StatePublished - 2023

Publication series

NamePresented at the 12th International Conference on Power Electronics, Machines and Drives (PEMD), 23-24 October 2023, Brussels, Belgium

NREL Publication Number

  • NREL/PR-5000-87649

Keywords

  • Bezier curves
  • multiphysics design
  • polymer-bonded magnets
  • shape optimization
  • targeted sampling

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