TY - JOUR
T1 - Multi-objective free-form shape optimization of a synchronous reluctance machine
AU - Gangl, Peter
AU - Köthe, Stefan
AU - Mellak, Christiane
AU - Cesarano, Alessio
AU - Mütze, Annette
N1 - Funding Information:
Alessio Cesarano has been funded by the Austrian Science Fund (FWF) Project P 32911.
Publisher Copyright:
© 2022, Emerald Publishing Limited.
PY - 2022/8/26
Y1 - 2022/8/26
N2 - Purpose: This paper aims to deal with the design optimization of a synchronous reluctance machine to be used in an X-ray tube, where the goal is to maximize the torque while keeping low the amount of material used, by means of gradient-based free-form shape optimization. Design/methodology/approach: The presented approach is based on the mathematical concept of shape derivatives and allows to obtain new motor designs without the need to introduce a geometric parametrization. This paper presents an extension of a standard gradient-based free-form shape optimization algorithm to the case of multiple objective functions by determining updates, which represent a descent of all involved criteria. Moreover, this paper illustrates a way to obtain an approximate Pareto front. Findings: The presented method allows to obtain optimal designs of arbitrary, non-parametric shape with very low computational cost. This paper validates the results by comparing them to a parametric geometry optimization in JMAG by means of a stochastic optimization algorithm. While the obtained designs are of similar shape, the computational time used by the gradient-based algorithm is in the order of minutes, compared to several hours taken by the stochastic optimization algorithm. Originality/value: This paper applies the presented gradient-based multi-objective optimization algorithm in the context of free-form shape optimization using the mathematical concept of shape derivatives. The authors obtain a set of Pareto-optimal designs, each of which is a shape that is not represented by a fixed set of parameters. To the best of the authors’ knowledge, this approach to multi-objective free-form shape optimization is novel in the context of electric machines.
AB - Purpose: This paper aims to deal with the design optimization of a synchronous reluctance machine to be used in an X-ray tube, where the goal is to maximize the torque while keeping low the amount of material used, by means of gradient-based free-form shape optimization. Design/methodology/approach: The presented approach is based on the mathematical concept of shape derivatives and allows to obtain new motor designs without the need to introduce a geometric parametrization. This paper presents an extension of a standard gradient-based free-form shape optimization algorithm to the case of multiple objective functions by determining updates, which represent a descent of all involved criteria. Moreover, this paper illustrates a way to obtain an approximate Pareto front. Findings: The presented method allows to obtain optimal designs of arbitrary, non-parametric shape with very low computational cost. This paper validates the results by comparing them to a parametric geometry optimization in JMAG by means of a stochastic optimization algorithm. While the obtained designs are of similar shape, the computational time used by the gradient-based algorithm is in the order of minutes, compared to several hours taken by the stochastic optimization algorithm. Originality/value: This paper applies the presented gradient-based multi-objective optimization algorithm in the context of free-form shape optimization using the mathematical concept of shape derivatives. The authors obtain a set of Pareto-optimal designs, each of which is a shape that is not represented by a fixed set of parameters. To the best of the authors’ knowledge, this approach to multi-objective free-form shape optimization is novel in the context of electric machines.
KW - Electrical machine
KW - Multi-objective optimization
KW - Shape optimization
KW - Synchronous reluctance machine
UR - http://www.scopus.com/inward/record.url?scp=85131360082&partnerID=8YFLogxK
U2 - 10.1108/COMPEL-02-2021-0063
DO - 10.1108/COMPEL-02-2021-0063
M3 - Article
AN - SCOPUS:85131360082
SN - 0332-1649
VL - 41
SP - 1849
EP - 1864
JO - COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
JF - COMPEL - The International Journal for Computation and Mathematics in Electrical and Electronic Engineering
IS - 5
ER -