Some results on the design of brushless DC wheel motor using SQP and GA

Issue title: OIPE 2006

Article type: Research Article

Authors: Moussouni, F.^{a; *} | Brisset, S.^a | Brochet, P.^a

Affiliations: [a] L2EP, Ecole Centrale de Lille, Cité Scientifique, BP 48, 59651 Villeneuve d'Ascq, France

Correspondence: [*] Corresponding author. E-mail: [email protected]

Abstract: The sequential quadratic programming and genetic algorithms are finely tuned on the optimal design of a brushless DC wheel motor. Combining both methods, a hybrid approach is tested. Multiobjective optimizations are performed using Nondominated Sorting Genetic Algorithm, Strength Pareto Evolutionary Algorithm, and a variable weighted sum of objectives with the sequential quadratic programming. The Pareto fronts are compared in term of accuracy, uniformity, and coverage criteria using some quality indicators.

Keywords: Sequential quadratic programming, genetic algorithms, mixed-integer optimization, multiobjective optimization

DOI: 10.3233/JAE-2007-913

Journal: International Journal of Applied Electromagnetics and Mechanics, vol. 26, no. 3-4, pp. 233-241, 2007