Scaling algorithms in modelling of power loss in soft magnetic composites

Najgebauer, Mariusz; Szczygłowski, J.; Ślusarek, B.; Przybylski, Marek

doi:10.1108/compel-10-2018-0412

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…The main task of an electric motor designer is, for a given set of objective functions, to find the optimal shape design (Jabbari et al , 2010), getting the best possible motor performance at the least material usage, while satisfying given criteria and prescribed physical or technical limitations. In the literature, there is plenty of contributions, which at a first glance could be categorized in two broad classes, namely, papers dealing with the magnetic analysis of a given motor comparing the effect of various materials and under several load conditions (Najgebauer et al , 2019; Przybylski et al , 2020), on the one hand and papers focused on the automated optimal design of a class of motors, on the other hand (Yan et al , 2019; Putek et al , 2017).…”

Section: Introductionmentioning

confidence: 99%

Optimal shape design of a class of permanent magnet motors in a multiple-objectives context

Barba

Mognaschi

Petkovska

et al. 2022

COMPEL

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Purpose This paper aims to deal with the optimal shape design of a class of permanent magnet motors by minimizing multiple objectives according to an original interpretation of Pareto optimality. The proposed method solves a many-objective problems characterized by five objective functions and five design variables with evolution strategy algorithms, classically used for single- and multi-objective (two objective functions) optimization problems. Design/methodology/approach Two approaches are proposed in the paper: the All-Objectives (AO) and the Many-Objectives (MO) optimization approach. The former is based on a single-objective optimization of a preference function, i.e. a normalized weighted sum. In contrast, in the MO a multi-objective optimization algorithm is applied to the minimization of a weight-free preference function and simultaneously to a maximization of the distance of the current solution from the prototype. The optimizations are based on an equivalent circuit model of the Permanent Magnet (PM) motor, but the results are assessed by means of finite element analyses (FEAs). Findings An extensive study of the solutions obtained by means of the different optimization approaches is provided by means of post-processing analyses. Both the approaches find non-dominated solutions with respect to the prototype that are substantially improving the initial solution. The points of strength along with the weakness points of each solution with respect to the prototype are analysed in depth. Practical implications The paper gives a good guide to the designers of electric motors, focussed on a shape design optimization. Originality/value Considering simultaneously five objective functions in an automated optimal design procedure is challenging. The proposed approach, based on a well-known and established optimization algorithm, but exploiting a new concept of degree of conflict, can lead to new results in the field of automated optimal design in a many-objective context.

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