Method for optimizing the magnetic circuit of a linear generator using FEM simulations
Journal article, 2020

Within the area of permanent magnet electrical machines, there is an ongoing focus on replacing the rare earth permanent magnets with alternatives. An option is hard ferrites, commonly used in other applications. The relatively low coercive field strength of the ferrite magnets makes irreversible demagnetization an area that should not be neglected. In this paper, a methodology is proposed for the optimization of a slow-moving linear generator simulated in a finite element environment. The no-load phase voltage is maximized while accounting for iron saturation and permanent magnet irreversible demagnetization. This demagnetization is considered when the translator is alongside either the stator or air. The inclination angle between magnetization and magnetic field strength is accounted for by adjusting the intrinsic coercivity for each element of the permanent magnets. Characteristics for the magnet grades Y30 and Y40 are used in the optimization process. The velocity of the translator is set to resemble a speed common to wave power applications. Commercial finite element software is used together with two optimization algorithms: the genetic algorithm and the particle swarm optimization. The results of these optimization algorithms reach similar optimal solutions for the considered objective function, assuring a result close to a global maximum. The results also show a great difference in the optimal geometry for the two magnet grades and highlight the need to account for irreversible demagnetization when designing generators with ferrite magnets.

Author

Jonathan Sjölund

Uppsala University

Mats Leijon

Chalmers, Electrical Engineering, Electric Power Engineering

Uppsala University

Sandra Eriksson

Uppsala University

AIP Advances

2158-3226 (ISSN) 21583226 (eISSN)

Vol. 10 3 035312

Subject Categories

Applied Mechanics

Computational Mathematics

Other Electrical Engineering, Electronic Engineering, Information Engineering

DOI

10.1063/1.5129303

More information

Latest update

4/16/2020