Multi-Criteria Design Optimization of Ultra Large Diameter Permanent Magnet Generator

  • Ott Pabut Tallinn University of Technology
  • Martin Eerme Tallinn University of Technology
  • Ants Kallaste Tallinn University of Technology
  • Toomas Vaimann Tallinn University of Technology
Keywords: Artificial neural networks, finite element analysis, Pareto optimization, permanent magnet machine.


This paper presents a novel design optimization procedure for an ultra large diameter permanent magnet generator. As the machine features unorthodox electromagnetic and mechanical layouts, basic principles for determining structural loads together with material quantities for cost estimation are described. Finite element modelling with beam elements is used for retrieving stresses and deformations of the novel carrier structure. Mathematical system response model of the generator is created with artificial neural networks, while genetic algorithm with gradient method is utilized for determining the optimal solutions. Input dataset for the model build-up is constructed with a help of a full factorial experimental method. Achieved results are utilized for describing the relationship between the structural response and efficiency values of the generator. As the design of the machine has to fulfil contradicting technical and economical requirements, Pareto optimality concept is employed. As an example, a set of optimal solutions is determined for the particular case.