Material-Density-Based Topology Optimization With Magnetic Nonlinearity by Means of Stabilized Sequential Linear Programming: SLPSTAB

作者：Okamoto Yoshifumi^*; Matsubayashi Yu; Wakao Shinji; Sato Shuji

来源：IEEE Transactions on Magnetics, 2015, 51(3): 7207804.

DOI：10.1109/TMAG.2014.2361360

• Magnetic nonlinearity
• material-density-based topology optimization (TO)
• stabilized sequential linear programming (SLPSTAB) method

The nonlinear magnetic properties of an iron core should be considered when topology optimization (TO) is applied to a realistic problem. However, a scheme for introduction of the magnetic nonlinearity to material-density-based TO has not been rigorously established. In this paper, TO by using material density with magnetic nonlinearity is proposed. The numerical instability of the sequential linear programming method is a well-known topic. The stabilized sequential linear programming method, which realizes the stabilized convergence characteristics of an objective function, is proposed and investigated in the 3-D design problem of a magnetic circuit.

• 出版日期2015-3