Improvements in material-density-based topology optimization for 3-d magnetic circuit design by fem and sequential linear programming method

Yoshifumi Okamoto, Yusuke Tominaga, Shinji Wakao, Shuji Sato

Research output: Contribution to journalArticle

19 Citations (Scopus)


Topology optimization (TO) makes it possible to obtain new structures for electrical machines. The sensitivity-based method, which can cope with some constraint conditions, is suitable for large-scale three-dimensional TO. However, if the material density is defined by unknown variables in TO, elements with intermediate density (grayscale) occasionally appear. The grayscale cannot clearly show the material allocation within its finite element. Thus, we propose a sigmoid-based filtering function to suppress the generation of grayscale. Moreover, because the constraint condition can be simply taken into consideration, sequential linear programming is occasionally utilized as a topology optimizer. However, the convergence characteristics frequently oscillate and are strongly dependent on the move limit that controls the maximum intensity of the correction vector. To overcome this numerical difficulty, we propose an identification technique for the determination of a quasi-optimal move limit (QOML). This paper demonstrates the performance of both the mathematical function filtering grayscale and QOML.

Original languageEnglish
Article number6749040
JournalIEEE Transactions on Magnetics
Issue number2
Publication statusPublished - 2014 Feb 1



  • Filtering function
  • material density
  • quasi-optimal move limit
  • sequential linear programming
  • topology optimization

ASJC Scopus subject areas

  • Electronic, Optical and Magnetic Materials
  • Electrical and Electronic Engineering

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